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Geospatial technologies are becoming increasingly important in today's world, as they allow us to better understand and manage the complex spatial relationships that shape our environment and society. From tracking natural disasters and wildlife habitats, to analyzing urban sprawl and demographic trends, to guiding precision agriculture and transportation systems, geospatial tools have a wide range of applications and implications for individuals, communities, and nations.
Yet, despite their growing relevance, many people still perceive geospatial technologies as complex, expensive, or intimidating. This is especially true for high school teachers, who may not have had the opportunity to learn or use such tools during their own education or professional development. As a result, they may struggle to integrate geospatial concepts and skills into their curricula, or miss the opportunity to inspire their students to explore and engage with the geospatial field.
This handbook aims to address this gap by providing a practical guide for high school teachers who want to map our world with open geospatial tools. By "open", we mean tools that are freely available, interoperable, and supported by vibrant communities of users and developers. Such tools include web mapping platforms, desktop GIS software, mobile apps, data portals, and online tutorials, among others. By "practical", we mean tools that are accessible, adaptable, and relevant to diverse contexts and subjects. Such tools can be used in science, math, social studies, art, language, and other disciplines, as well as in extracurricular activities and community projects.
Geospatial technologies offer a unique opportunity for high school teachers to incorporate STEAM methodology into their classrooms. By integrating geospatial tools and concepts, teachers can provide students with a hands-on and interdisciplinary approach to learning, which can help students develop critical thinking, problem-solving, and technical skills. In addition, geospatial technologies provide an excellent platform for engaging students in real-world issues, encouraging them to become active participants in their communities and to explore potential career paths.
Welcome to the handbook "Mapping Our World With Open Geospatial Tools: A Practical Guide for High School Teachers'', which is based on the results of a comprehensive questionnaire filled out by teachers on their skills, experiences, needs, and challenges related to teaching geospatial concepts and mapping in high school classrooms. This handbook aims to provide educators with practical and accessible guidance on how to incorporate geospatial tools and concepts into their curricula, with the ultimate goal of fostering a STEAM-literate and geospatially-aware generation of learners.
We hope that this handbook will inspire and empower high school teachers and their students to explore and engage with the fascinating world of geospatial tools, and to contribute to the development of a more informed, connected, and sustainable society. We also welcome feedback, suggestions, and contributions to this handbook, which is meant to be a dynamic and evolving resource for the geospatial community. Let's map our world together!
Jana Michalková
Chapter II provides an overview of the concept of Citizen Science and Volunteer Geographic Information, highlighting their importance in promoting public participation in data sharing. It further discusses OpenStreetMap, which is a community mapping initiative that allows individuals to contribute to the creation of a comprehensive map of the world. The chapter describes the licensing structure, community overview, and data availability of the OpenStreetMap platform, along with practical guidance on how to access the platform. Finally, it concludes with a discussion on UN Mappers, an inclusive mapping initiative that uses citizen science and volunteer geographic information to support UN activities in promoting peace and security through open mapping.
This chapter focuses on mapping activities, specifically open field mapping tools that are utilized to analyze environmental and humanitarian topics. Open field mapping tools such as Vespucci or GoMap give access to the OpenStreetMap database, allowing the public to contribute and access and edit environmental information. This helps to better understand and utilize climate change and find solutions. The public accessibility of the database has a broad range of uses, such as disaster relief, humanitarian aid, and environmental conservation efforts. Also we will learn Field Papers which provides analog field mapping with possibilities of digitizing paper maps. So, in this chapter, we will deal with such tools and learn how to use them in mapping local environmental issues.
This chapter provides a brief explanation and importance of organizing a humanitarian event „Mapathon“. It's a modern digital form of volunteering that is accessible to everyone, regardless of age. Through the organizing of the „Mapathon“ event, we can improve the quality of the world's data on maps, as well as meet people from around the world and exchange knowledge. We think it's important to spread awareness about this form of volunteering, so that even more people can get involved. In this case, we have prepared a detailed step-by-step manual that will explain how to organize „Mapathon“ and how to map on the Teach OSM humanitarian platform using the iD editor. This step-by-step manual is supplemented by instruction images taken from task #1148 Mapping Tartus created by the student community PoliMappers from Politecnico di Milano.
Chapter I provides an introduction to the fundamentals of mapping and geospatial concepts for high school teachers. It starts with an overview of why mapping and geospatial concepts are important, followed by a discussion of the fundamentals of data processing, including data collection, organization, analysis, and visualization. Next, the chapter explains geospatial data, including an understanding of geodata and geographic information systems (GIS) together with examples of its usage. Finally, the chapter delves into the open source philosophy and its applications in mapping, including the use of open source software, open data, and open mapping initiatives. It also describes the most popular open source geotools that can be useful in the high school educational process. This chapter is designed to equip educators with the knowledge and tools necessary to incorporate mapping and geospatial concepts into their curriculum, ultimately helping students to better understand and analyze the world around them.
This chapter provides practical guidance to begin preparing pupil-led projects in each school. Teacher teams will first diagnose their school contexts and opportunities (teachers involved, subjects, school ongoing projects, strategic lines, coordination requirements, etc.). Then, they will define and evaluate two possible challenges that will be presented to the pupils later. Finally, the pupils will select the school challenge through a participatory process. The results of this work seek to enhance coordination and participation of teachers and pupils, being the starting point for the next module.
We would like to express our gratitude to the authors and contributors of the handbook "Mapping Our World With Open Geospatial Tools: A Practical Guide for High School Teachers," which is licensed under a Creative Commons Attribution-ShareAlike (CC-BY-SA) license. Our special thanks go to the following individuals for their valuable contributions:
Jana Michalková, Miloslav Michalko
UNIVERSITY OF PREŠOV
Miloslav Michalko miloslav.michalko@unipo.sk;
Jana Michalková jana.michalkova@unipo.sk;
Daniela Vavreková daniela.vavrekova@smail.unipo.sk;
Katarína Korfantová katarina.korfantova@smail.unipo.sk
Štefan Koco stefan.koco@unipo.sk;
POLITECNICO DI MILANO
Maria Antonia Brovelli maria.brovelli@polimi.it;
Alberta Albertella alberta.albertella@polimi.it;
Alberto Vavassori alberto.vavassori@polimi.it;
Rodrigo Cedeno jesusrodrigo.cedeno@polimi.it;
Lorenzo Stucchi lorenzo.stucchi@polimi.it;
Angelly Pugliese angellyde.pugliese@polimi.it;
Juan Pablo Duque juanpablo.duque@polimi.it;
Federica Gaspari federica.gaspari@polimi.it;
Vasil Yordanov vasil.yordanov@polimi.it;
UNIVERSIDAD POLITECNICA DE MADRID
Miguel Marchamalo miguel.marchamalo@upm.es;
Susana Sastre susana.sastre@upm.es;
Alexandra Míguez alexandra.miguez@upm.es;
Ana Jiménez-Rivero Ana.jimenez@upm.es;
University of Presov Prešovská univerzita v Prešove Ul. 17. novembra 15 080 01 Prešov Slovakia
We also acknowledge and appreciate the efforts of Euronike as the main partner and coordinator of the Erasmus+ project "EUthMappers – open and collaborative mapping for pupils-led projects in Secondary Schools through innovative teaching methodology and fostering STEAM education and Environmental engagement" with code KA220-SCH-8A47B4C2. This project is co-funded by the Erasmus+ programme of the European Union.
The validation process plays a critical role in maintaining high standards and improving the quality of data in a mapping project. Mapping work performed on a voluntary basis by non-professionals must undergo validation to ensure accuracy and consistency, which are essential for reliable information on the map. The validator's responsibility is to ensure that the mapping work meets the project's specifications and is executed correctly. In evaluating each task, completeness and correctness are the two crucial aspects that must be considered. Completeness refers to identifying all the elements accurately, while correctness entails ensuring that mapped entities are geometrically and semantically correct. Therefore, during the validation process, errors must be detected and corrected. However, for teaching purposes, it is also essential to encourage mappers to correct their own work and become aware of the project's overall goals, rather than just correcting errors during validation.
Mapping and geospatial concepts have become increasingly important in our modern world. As our societies become more complex and interconnected, the ability to understand and interpret spatial data has become a critical skill.
Both terms are closely linked, as mapping often involves the use of geospatial data and technology. Mapping is a process of representing geospatial data on a two-dimensional surface, such as a paper map or digital map. Maps can provide a visual representation of geospatial data, such as the distribution of population, land use, or natural resources. Geospatial concepts refer to the use of spatial data, including location and other geographic information, to analyze and understand real-world phenomena.
Geospatial concepts and tools, such as geodata, GIS, and open source geotools, are essential for understanding and creating maps. Geodata refers to any data that has a geographic or spatial component, such as information about physical features like terrain, water bodies, and buildings, as well as human-made features like roads, cities, and other infrastructure. GIS, or Geographic Information System, is a tool that allows users to visualize, analyze, and interpret geospatial data. It can be used to create maps, perform spatial analysis, and solve real-world problems. Open source geotools are software tools that are freely available for anyone to use, modify, and distribute. They are a powerful resource for educators and students who want to learn more about mapping and geospatial concepts.
Geospatial concepts are a fundamental part of modern technology and play a crucial role in understanding and managing the complex relationships between different geographic phenomena. As a high school teacher, it is important to introduce students to these concepts and tools, as they will likely encounter them in various fields and industries such as urban planning or environmental science, where accurate geospatial data is essential for making informed decisions. Here are some reasons why mapping and geospatial concepts are important:
Understanding complex issues: Maps and geospatial data can help us understand complex issues such as climate change, population growth, urbanization, and environmental degradation. By visualizing data in a spatial context, we can gain insights that might not be immediately apparent from other forms of data analysis.
Decision-making: Maps and geospatial data can be used to inform decision-making in a variety of contexts. For example, policymakers can use maps to identify areas that are vulnerable to natural disasters or to determine where to invest in infrastructure. Businesses can use geospatial data to identify new markets or to optimize supply chains.
Communication: Maps are a powerful tool for communication. They can be used to convey information about a wide range of topics, from the location of public services to the spread of disease. By visualizing data in a spatial context, maps can make complex information more accessible to a wider audience.
Education: Maps and geospatial concepts are increasingly being used in education at all levels, from primary school to university. By teaching students to use maps and spatial data, educators can help them develop critical thinking skills and an understanding of complex issues.
By incorporating these concepts into their teaching practices, educators can introduce their students to the world of mapping and geospatial concepts, preparing them for the increasingly digital and spatially-aware world we live in.
Geospatial concepts and mapping have become an integral part of our daily lives. From finding directions using navigation apps to tracking weather patterns and predicting natural disasters, geospatial technology has a wide range of applications.
In this chapter, we have provided an introduction to mapping and geospatial concepts for high school teachers, with a focus on understanding geodata, GIS, and open source geotools. We discussed the fundamentals of data processing, and also explored geospatial data and geographic information systems, which allow us to analyze and visualize spatial data. Finally, we discussed the benefits of the open source philosophy, which promotes the use of open source software, open data, and open mapping platforms. We have also brought an overview of the most popular open source geotools.
Everything mentioned can be widely applied in the high school educational process as well and help students to better understand and analyze the world around them. It is therefore essential that educators have the necessary knowledge and skills to incorporate these concepts into their teaching, and to prepare their students for the challenges of the 21st century.
We hope that this chapter has provided a useful foundation for high school teachers to explore mapping and geospatial concepts further, and that it will inspire them to incorporate these concepts into their teaching and will help their students develop the necessary skills to navigate and understand our complex world, and so will empower the next generation of geospatial professionals.
Open source software is a type of computer software that is developed collaboratively and made freely available for anyone to use, modify, and distribute. In recent years, open source software has become increasingly popular in high school education, as it provides teachers and students with access to powerful tools for learning and creativity without the high costs typically associated with proprietary software.
Open source software is particularly valuable in STEAM education, as it allows students to gain hands-on experience with a wide range of tools and technologies used in science, engineering, and mathematics. One of the main advantages of open source software is its flexibility and customizability. Teachers and students can modify and adapt open source software to suit their specific needs and interests, making it a valuable tool for project-based learning and exploration. Open source software also provides opportunities for students to collaborate on software development projects, improving their teamwork and communication skills.
Examples of open source software that are commonly used in high school education include:
LibreOffice: a free and open source office suite including word processing, spreadsheet, and presentation software.
GIMP: an image editing software similar to Adobe Photoshop
Inkscape: a vector graphics editor
Blender: a 3D modeling software
Audacity: an audio editing software
Open source software has become increasingly popular in the field of geospatial data analysis and mapping due to its flexibility, affordability, and accessibility. This allows for a collaborative and community-driven approach to geospatial concepts, which can be a valuable learning experience for students who want to explore the world of geospatial data.
Many open source geospatial tools are available for analyzing, visualizing, and managing geospatial data, providing opportunities for students to develop valuable skills in these areas. Here is a list some popular open source geospatial tools:
QGIS is a powerful free and open source cross-platform GIS software that provides a wide range of tools for data analysis, visualization, and mapping and it is widely used by professionals and educators alike.
GRASS GIS is another open source GIS software that provides a wide range of tools for data analysis, modeling, and visualization.
GeoServer is an open source server software that allows users to share and publish geospatial data on the web, and is an excellent tool for creating interactive maps and web-based applications.
OpenLayers is an open source JavaScript library for displaying and manipulating maps on the web.
Leaflet is the leading open source JavaScript library for mobile-friendly interactive maps.
PostGIS is a free and open source spatial database extender for PostgreSQL that enables advanced geospatial queries and analysis.
By using open source geospatial tools in high school education, students can learn important skills and knowledge that are relevant to various fields, such as geography, environmental science, urban planning, and more. Additionally, they can gain exposure to the principles of open source software and the benefits of collaborative knowledge sharing. Another reasons why open source geospatial tools are beneficial for high school education include:
Cost-effectiveness: Open source geospatial tools are free, which makes them accessible to schools with limited budgets.
Customizability: Open source geospatial tools can be customized and adapted to meet specific needs and learning objectives, which allows for greater flexibility and creativity in the classroom.
Openness and transparency: Open source geospatial tools are open for everyone to access, study, and modify. This encourages collaboration, innovation, and knowledge sharing.
Real-world applicability: Many open source geospatial tools are used by professionals in the field, which means that students can gain practical skills and knowledge that can be applied in real-world situations.
Community support: Open source geospatial tools have active communities of users and developers who contribute to their development and provide support for new users.
In conclusion, open source software and geotools provide an accessible and cost-effective way to introduce high school students to the world of geospatial data analysis and mapping. This experience can be enhanced by the use of open data sources and voluntary geographic information (VGI), which provide real-world examples and opportunities for students to engage in meaningful mapping projects.
This chapter provides an overview of the concept of Citizen Science and Volunteer Geographic Information, highlighting their importance in promoting public participation in data sharing. It further discusses OpenStreetMap, which is a community mapping initiative that allows individuals to contribute to the creation of a comprehensive map of the world. The chapter describes the licensing structure, community overview, and data availability of the OpenStreetMap platform, along with practical guidance on how to access the platform. Finally, it concludes with a discussion on UN Mappers, an inclusive mapping initiative that uses citizen science and volunteer geographic information to support UN activities in promoting peace and security through open mapping.
Open source philosophy is a set of principles and practices that promote the free and open distribution, access, and modification of software, data, and other forms of creative work. This philosophy is based on the belief that by sharing knowledge and resources openly, we can foster collaboration, innovation, and social good.
The term "open source" was originally coined in the context of software development, where it referred to software that is freely available to use, modify, and distribute, with the source code openly available for inspection and modification. However, the open source philosophy has since expanded to include other domains, such as data, education, government, and even art and culture.
In the next part, we will take a closer look at open source software, open data concepts and open mapping initiatives for use in high school education and how they can be used to enhance learning in this context.
Open data refers to data that is freely available to use, modify, and distribute, without the need for a license or other restrictions. This approach to data sharing can help break down barriers to accessing information, and promote the development of new tools and insights based on the data.
In the context of high school education, open data can be a valuable resource for students to develop their data literacy skills, learn about current events and issues, and engage in projects that are relevant to their local communities. Open data can also help students develop critical thinking skills and the ability to analyze and interpret data to make informed decisions.
Open data can come from a variety of sources, including government agencies, non-profit organizations, and citizen scientists. In the context of mapping and geospatial analysis, open data can be particularly useful for creating maps and visualizing spatial patterns.
One type of open data that is particularly useful in mapping is voluntary geographic information (VGI). VGI is geographic information that is collected and shared by individuals, rather than by professional surveyors or mapping agencies. VGI can include data such as GPS tracks, photos, and text descriptions, and it can be used to create detailed, up-to-date maps of specific locations. More about VGI in Chapter II.
Using open data and VGI in high school education can help to make learning more engaging and relevant to students' lives. They can learn how to create maps that reflect real-world situations and problems, such as climate change, environmental degradation, or urbanization, and also develop important skills in data analysis, data visualization, and communication.
In addition, the use of open data and VGI can help to foster a culture of openness and collaboration among students, encouraging them to contribute to shared databases and to engage with broader communities of practitioners. This can help to promote critical thinking, problem-solving, and digital literacy skills, and can also help to prepare students for future careers in fields such as data science, environmental management, and urban planning.
There are many sources of open data and VGI that can be used in high school education. Here is a list the most popular of them:
OpenStreetMap is a global community-driven mapping project that provides free and editable maps of the world. The platform allows users to contribute data on streets, buildings, landmarks, and more, making it a valuable resource for learning about geography and mapping.
Natural Earth Data is a public domain map dataset that provides vector and raster maps at various scales and levels of detail.
World Bank Open Data provides access to a wealth of data on development, including data on education, health, poverty, and environment. These data can be used in classroom activities to help students understand global issues and how they can be addressed.
The European Union Open Data Portal provides access to a wide range of data from the European Union and its member states, including economic and social indicators, environmental data, and statistics on agriculture, transport, and energy.
Copernicus Open Access Hub is a European Union initiative that provides free and open access to a range of environmental data, including data on land, oceans, atmosphere, climate, and emergency management. This data can be used in classroom activities to teach students about environmental science, climate change, and natural disasters.
NASA Earth Observations provides access to a range of satellite data on the Earth's atmosphere, land surface, and oceans. These data can be used in classroom activities to help students understand topics such as climate change, natural disasters, and environmental monitoring.
UNICEF Data provides access to a range of data related to children and young people, including data on education, health, nutrition, and child protection. These data can be used in classroom activities to help students understand the challenges facing young people around the world.
Open data provides access to a wealth of information that can be used to create interactive and engaging educational materials. The concept of open data has also facilitated the rise of VGI, which allows for the collection of data by volunteers to create more detailed and accurate maps. By combining open data with open mapping, educators and students have a powerful set of tools at their disposal to explore complex geospatial concepts and engage in meaningful projects that address real-world problems. Let's take a look more in detail on the open mapping.
The terms geospatial data and geodata can be used interchangeably to refer to any data that is tied to a specific location or geographic area. Both terms are commonly used in the field of GIS and geospatial analysis to describe data that has a spatial component, such as GPS coordinates, satellite imagery, and maps. Geodata may be more commonly used in the context of data management and storage, while geospatial data may be used more frequently in the context of analysis and visualization.
Overall, the important thing is to understand that both terms refer to the same concept: data that has a geographic or spatial component and can be analyzed using GIS tools and techniques.
Geodata, also known as geographic data, can be represented as points, lines, polygons, or raster images. Geodata principles refer to the methods and techniques used to collect, store, analyze, and visualize geodata. The principles are based on the concept of spatial relationships and include spatial data infrastructure, spatial analysis, and spatial visualization.
Geospatial data refers to the information that is associated with a specific location on the earth's surface. This data can be used to create maps, visualize data trends, and analyze spatial patterns. Geospatial data can be obtained from a variety of sources such as satellite imagery, GPS devices, remote sensing, and field surveys, including publicly available data, proprietary data, and crowdsourced data. Publicly available data includes information from government agencies and other organizations that is made available for public use. Proprietary data is owned by a specific company or organization and may require a fee or license to access. Crowdsourced data is collected by individuals and organizations who contribute data voluntarily, often through online platforms like OpenStreetMap.
There are different types of geospatial data, including vector and raster data (Fig. 5). Vector data represents geographic features as points, lines, or polygons, and is commonly used to represent roads, buildings, and land parcels. Raster data represents geographic features as pixels, and is commonly used to represent satellite imagery, elevation data, and weather data.
Geospatial data can be used in a variety of applications, including environmental management, urban planning, emergency response, transportation, and agriculture. It helps us to better understand and manage the complex spatial relationships that shape our environment and society. For example, GPS navigation systems use geospatial data to provide directions and information about traffic conditions. Emergency response teams use geospatial data to identify areas at risk during natural disasters. Urban planners use geospatial data to plan transportation networks and allocate resources. Agricultural scientists use geospatial data to optimize crop yields and manage natural resources.
Effective visualization of geodata is crucial for communicating information and insights. This can include creating maps, charts, graphs, and other visualizations that highlight patterns, trends, and other insights in the data. One common approach to geospatial data processing is to use GIS software, which enables users to analyze and manipulate geospatial data in a variety of ways.
Geographic Information System (GIS) is a powerful tool for working with geospatial data, providing a range of tools for collecting, analyzing, and visualizing spatial information. In education, GIS can be used across a wide range of subjects, including geography, environmental science, urban planning, and more.
GIS can be defined as a system that organizes its data sets in layers, allowing for a more comprehensive and straightforward approach. These layers comprise maps of the same geographic area, where each location has identical coordinates across all the maps in the system (Fig. 6). By doing so, it is possible to analyze the thematic and spatial attributes of the zone and obtain a better understanding of it. By presenting this information in layers that can be superimposed, users can visualize a real phenomenon and better comprehend the relationships between various elements in a geographic area.
GIS can be extremely useful also in addressing climate change challenges by helping to analyze, visualize, and manage a wide range of geospatial data related to climate change. Here are a few examples of GIS usage:
Mapping climate change vulnerability: GIS can be used to map areas that are particularly vulnerable to the impacts of climate change, such as areas prone to flooding, drought, or wildfires. By identifying these areas, policymakers can develop targeted adaptation strategies to help communities prepare for and respond to the impacts of climate change.
Analyzing land use change: GIS can be used to track changes in land use over time, such as deforestation or urbanization. This can help researchers understand the impact of land use change on carbon sequestration, biodiversity, and other important ecological processes.
Managing renewable energy resources: GIS can be used to identify and map areas with high potential for renewable energy development, such as solar or wind power. This information can be used to guide decision-making around energy policy and investment.
Monitoring greenhouse gas emissions: GIS can be used to track emissions of greenhouse gasses from different sources, such as transportation, industry, or agriculture. This information can be used to develop policies and strategies for reducing emissions and mitigating the impacts of climate change.
Visualizing climate data: GIS can be used to create visualizations of climate data, such as temperature, precipitation, and sea level rise. These visualizations can help policymakers, researchers, and the public better understand the impacts of climate change and the need for action.
Geospatial data and GIS technology play a critical role in understanding and managing our environment and society. One of the key benefits of using GIS in education is that it enables students to explore complex relationships between different geographic phenomena. For example, students can use GIS to analyze the relationship between land use and water quality, or to examine patterns of migration and population distribution. By working with geospatial data in this way, students can develop a deeper understanding of the world around them and the interconnectedness of various phenomena. GIS can be used to teach a wide range of subjects, including geography, earth science, environmental science, biology, and social studies.
As high school teachers, it is important to introduce geospatial data and its principles to students, and demonstrate how it is used in everyday life. Incorporating GIS into the curriculum can help to make learning more engaging and interactive. By using GIS to create dynamic maps and visualizations, educators can help to bring the subject matter to life and capture students' interest. This can lead to greater student engagement, improved retention of information, and a deeper understanding of the subject matter.
By understanding geospatial data and GIS students can also develop skills needed to succeed in a wide range of fields, from environmental science to urban planning and beyond, as well as important STEAM skills and contribute to the development of a more informed, connected, and sustainable society.
Open mapping refers to the concept of using open source tools and open data to create and share maps. This approach is based on the principles of transparency, collaboration, and community participation, and allows for the creation of maps that are accessible, up-to-date, and relevant to the needs of various users. Open mapping initiatives often involve volunteer mapping, where individuals or groups contribute their time and expertise to create or update maps.
There are some differences between open mapping and voluntary mapping. Open mapping is a more general and a broader concept that encompasses a wide range of efforts to create and share geospatial data openly, while volunteer mapping is a specific type of mapping that relies on voluntary contributions from individuals or organizations. This can involve tasks such as digitizing and tagging satellite imagery, identifying features and land use from aerial photos, collecting data through ground surveys, and updating maps based on current events. Volunteer mapping initiatives often rely on open source mapping tools and platforms and can engage communities and individuals from all over the world.
The use of open mapping can have a significant impact in various fields such as disaster management, environmental conservation, urban planning, transportation, and social development, and can empower individuals and communities to take an active role in shaping their environments. One of the most popular open mapping projects that addresses these challenges is OpenStreetMap (OSM).
OpenStreetMap (OSM) is a collaborative project that aims to create a free and editable map of the world. The project was launched in 2004 and has since grown to become one of the largest and most detailed maps available, with over over 10 million registered users. Anyone can contribute to the project by adding or editing map data, and the resulting map can be used for a wide range of applications, from navigation to disaster response. The availability of open data and the collaborative nature of the project make it a valuable tool for education, allowing students to learn about geography, mapping, and collaboration in a real-world context. More about OSM in Chapter II.
OpenStreetMap (OSM) is a project that makes free maps of the world available to everyone. These maps can be used for all kinds of purposes without any restrictions, like exploring new places, creating travel plans, or building apps. The project began because many other maps that people think are free have rules that limit how they can be used. By providing unrestricted access to geographic data, OSM enables people to use maps in creative, productive, and unexpected ways.
OpenStreetMap is a great tool that allows you to use maps and data for free. However, two conditions must be followed. Firstly, you need to give proper credit to OpenStreetMap for any use of their maps or data. Secondly, if you make any corrections or improvements to the maps, you need to share them back with the project.
OpenStreetMap has experienced rapid growth over time due to its openness and availability of information and data. This is evident from Fig. 2, which shows the number of registered users over time. The graph displays an exponential increase in the number of users. This growth can be attributed to the fact that OpenStreetMap provides a valuable resource for many different types of users, including researchers, developers, and everyday people who need access to accurate and up-to-date geographic information. With the continued growth of OpenStreetMap, we can expect even more exciting developments and innovations in the future. More information about OSM and statistics about its use can be found at the WikiOSM Stats website.
OpenStreetMap is open, licensed under the Open Data Commons Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF). You are free to copy, distribute, transmit and adapt OSM data, as credit is given to OpenStreetMap and its contributors. If data is altered or built upon, the result has to be distributed only under the same license (see Fig. 3). For more information access the following link: https://www.openstreetmap.org/copyright.
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Haklay, M. (2010). How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets. Environment and Planning B: Urban Analytics and City Science, 37(4), 682-703.
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Maguire, D. J., Batty, M., & Goodchild, M. F. (2005). GIS, Spatial Analysis, and Modeling. ESRI Press.
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Understanding Geodata, GIS, and Open Source Geotools
Mapping plays a crucial role in the education process as it provides a visual representation of data and information that helps students to understand complex concepts and relationships. By creating and analyzing maps, students can explore patterns and connections that are not immediately apparent from raw data. Maps can also help students to identify and solve problems, such as identifying areas of high pollution in a city or analyzing the distribution of natural resources.
In addition, mapping can be used to teach students valuable skills in data analysis, critical thinking, and spatial reasoning. Students can learn to manipulate and analyze geospatial data to gain insights into real-world issues. These skills are highly valuable in many fields, including urban planning, environmental science, or transportation planning.
Chapter I aims to introduce the fundamental concepts of mapping and geospatial data processing to high school teachers. It starts with an overview of why mapping and geospatial concepts are important, followed by a discussion of the fundamentals of data processing, including data collection, organization, analysis, and visualization. Next, the chapter explores geospatial data, including an understanding of geodata and geographic information systems (GIS). Finally, the chapter delves into the open source philosophy and its applications in mapping, including the use of open source software, open data, open mapping initiatives, and with overview of the most popular open geotools. This chapter is designed to equip high school teachers with the knowledge and tools necessary to incorporate mapping and geospatial concepts into their curriculum, ultimately helping students to better understand and analyze the world around them.
By the end of the chapter, readers will have a solid understanding of the key concepts and tools used in mapping and geospatial analysis, and be able to apply this knowledge to their own classroom instruction.
Data processing is a critical component of working with geospatial data, as it enables users to transform raw data into meaningful information that can be used for a wide range of applications.
In order to understand geospatial data, it is important to understand the basics of data processing. In this section, we will cover the fundamentals of data processing, including data collection, organization and analysis, and provide some examples of how data processing can be used in mapping and geospatial analysis.
Data processing is the process of collecting, organizing/transformation, and analyzing data. The first step in data processing is collecting data. There are many different ways to collect data, depending on the type of data you are collecting and the resources available to you. Some common methods of data collection include:
Surveys: Surveys are a common method of data collection, particularly for social and environmental data. They can be conducted in person, over the phone, or online, and can collect a wide range of data, from demographic information to opinions and attitudes.
Remote sensing: Remote sensing refers to the collection of data from a distance, using tools like satellites or drones. It can be used to collect data on the Earth's surface, such as land cover, temperature, and vegetation.
Field data collection: Field data collection involves collecting data in the field, often using specialized equipment like GPS devices or environmental sensors. It can be used to collect data on physical features like elevation, soil characteristics, and water quality.
Existing data sources: Existing data sources, such as government databases or scientific studies, can also be used as sources of data. This can be particularly useful when collecting data on a large scale, such as when analyzing global trends.
Once data has been collected, it needs to be organized in a way that makes it useful for analysis. This involves several steps, including:
Cleaning: Cleaning involves removing any errors or inconsistencies in the data. This can include removing duplicate entries, fixing spelling errors, and checking for missing values.
Formatting: Formatting involves organizing the data in a way that is consistent and easy to read. This can include converting data to a standard format, such as CSV or Excel, and creating labels or categories for the data.
Storing: Storing involves saving the data in a secure and accessible location. This can include saving data to a local computer, a cloud storage platform like Google Drive or Dropbox, or a specialized database.
In education, understanding how to process and analyze data can help both teachers and students make informed decisions, draw conclusions from complex information, and gain insights into various subjects.
One common type of data in the education process is tabular data. Tabular data is organized into rows and columns, much like a spreadsheet. Each row represents an individual record, and each column represents an attribute, or characteristic, of that record. For example, a table of student information might have columns for student ID, name, grade level, and test scores.
Understanding attributes is important for organizing and analyzing data. Attributes can be numerical (e.g., age or test score), textual (e.g., name), or categorical (e.g., gender or class subject). By properly categorizing and analyzing attributes, teachers can identify trends, make comparisons, and evaluate progress.
There are different ways to process and analyze tabular data, such as:
Sorting: Organizing data in ascending or descending order based on a specific attribute, like sorting students by their test scores.
Filtering: Selecting records that meet certain criteria, such as displaying only students who scored above a specific threshold on a test.
Aggregating: Combining records to generate summary statistics, like calculating the average test score for a class.
Pivot tables: Rearranging and summarizing data in a more compact and organized format, which can help identify patterns or relationships between attributes.
By understanding the fundamentals of data processing and incorporating them into the classroom, teachers can better analyze student performance, identify areas for improvement, and tailor their instruction to meet the diverse needs of their students.
To illustrate the concepts discussed in this chapter, let's consider a table representing the population and area of different cities:
Now, let's apply the sorting and filtering techniques to this table:
Sorting: To sort the table by Population in descending order, we would rearrange the rows as follows:
Filtering: To filter the table to display only cities with an Area greater than 1,000 sq km, we would keep only the following rows:
By applying these data processing techniques, we can easily organize and analyze the information in the table to answer various questions or identify patterns. For instance, sorting by population can help us understand which cities have the largest populations, while filtering by area can help us focus on cities with specific characteristics, such as a larger landmass.
To present the population table on a map, it should include geographic coordinates (latitude and longitude) or other location-based attributes (e.g., addresses, postal codes, or administrative boundaries) that can be geocoded or linked to spatial data. We can modify the previous city population table by adding latitude and longitude columns to represent the city locations:
Tabular data with geographic attributes will thus become the spatial data, which can then be visualized on a map (Fig. 1).
Data processing is essential for creating effective maps and understanding geospatial data. Here are some examples of how data processing can be used in mapping and geospatial analysis:
Data visualization: Data processing can be used to create maps that visualize the effects of climate change on a specific region. For example, a map could show the extent and vulnerability of permafrost (Fig. 2). Permafrost is thawing at an alarming rate, releasing greenhouse gasses into the atmosphere and creating hazards such as collapsing infrastructure and increased wildfire risk. Mapping can help policymakers and scientists better understand the risks and plan for adaptation strategies.
Spatial analysis: Spatial analysis can be used to identify areas that are vulnerable to natural disasters or humanitarian crises. By analyzing population density, topography, and other factors, a map could identify areas that are at high risk of flooding, landslides, or other hazards. For example, a map could show the predicted impact of sea level rise on coastal communities in the next 80 years (Fig. 3). This can help policymakers and residents understand the potential risks and plan for adaptation measures.
Modeling: Data processing can be used to create models that simulate the impact of environmental challenges on ecosystems. For example, a model could simulate the effects of climate change on coral reefs in a specific region (Fig. 4). This can help researchers and policymakers understand the potential impact of environmental changes and develop strategies to protect and preserve vulnerable ecosystems.
For high school teachers and students, it's important to emphasize the practical applications of data processing in mapping and geospatial analysis. For example, data processing can be also used to create maps of a school campus or local community, analyze patterns in traffic flow or pedestrian activity, or track the spread of a disease. It's also important to highlight the various tools and platforms available for data processing, and to encourage students to experiment with these tools in order to develop their data analysis and visualization skills.
City
Population
Area (sq km)
New York
8,398,748
783.8
Los Angeles
3,990,456
1,302
Chicago
2,705,994
606
Houston
2,325,502
1,651
Phoenix
1,660,272
1,340
Philadelphia
1,584,138
347
City
Population
Area (sq km)
New York
8,398,748
783.8
Los Angeles
3,990,456
1,302
Chicago
2,705,994
606
Houston
2,325,502
1,651
Phoenix
1,660,272
1,340
Philadelphia
1,584,138
347
City
Population
Area (sq km)
Los Angeles
3,990,456
1,302
Houston
2,325,502
1,651
Phoenix
1,660,272
1,340
City
Population
Area (sq km)
Latitude
Longitude
New York
8,398,748
783.8
40.7128
-74.0060
Los Angeles
3,990,456
1,302
34.0522
-118.2437
Chicago
2,705,994
606
41.8781
-87.6298
Houston
2,325,502
1,651
29.7604
-95.3698
Phoenix
1,660,272
1,340
33.4484
-112.0740
Philadelphia
1,584,138
347
39.9526
-75.1652
UN Mappers is a community of mapping enthusiasts who collaborate to gather, verify and distribute geospatial open data in regions where the United Nations conducts field operations. The community is very diverse, including UN personnel, academia (high schools and universities), local communities, NGOs, and volunteers around the globe. The goal of this initiative is to provide more precise location-based data to support decision-making processes. Mapping the world, supporting peace, and serving humanity are their motto.
As a part of the UN Maps project, UN Mappers seek to enhance topographic and operational data in UN missions. This includes providing peacekeeping and humanitarian actors with better maps, operational geo-information, search and navigation tools, as well as imagery and street-level base maps.
UN Mappers uses the OpenStreetMap (OSM) platform to support their initiatives. They create OSM projects where members can contribute by mapping topographic features. Topographic features which are easy to map include residential areas, villages, highways, and waterways, while the more complex ones include the land cover and land use. Therefore, both beginners and advanced mappers can contribute. UN Mappers is an inclusive community that welcomes participation from anyone who wishes to contribute to the cause of promoting peace and security through open mapping.
UN Mappers supports collaborative events which are fundamental for the production of open data. Collaborative events include mapathons and training. Mapathons are mapping 'hackathons' where beginner or advanced mappers meet up to map together. Training consists of structured presentations to acquire specific editing skills while editing on the mapping projects, for example, basic OSM skills, advanced editing topics, and field mapping (Fig. 9 displays a photo of training performed with university students in Italy).
Anyone can participate in UN Mappers and contribute to promoting peace and security through open mapping. You can find out how to start contributing and becoming a mapping expert using UN Maps Learning Hub, the UN Mappers educational platform that offers courses on OSM editing, tests, and certificates. Join the community today!
The term Citizen Science was first reported in Wikipedia in 2005 and entered the Oxford English Dictionary in 2014 as: “scientific work undertaken by members of the general public, often in collaboration with or under the direction of professional scientists and scientific institutions”.
It emerged as a concept in the mid-1990s as a response to several factors, including the increasing availability of technology and the growing interest among the public in participating in scientific research.
There were also concerns among scientists that the sheer scale of some research projects, particularly in fields such as ecology and environmental science, made it difficult for individual researchers or small teams to collect enough data to draw meaningful conclusions. By involving members of the public in the research process, citizen science projects collect much larger datasets, often covering larger geographic areas, than would be possible with traditional research methods.
The citizen science projects can be distinguished into three different classes:
Long-running citizen science, which are the traditional ones, the projects similar to those run in the past, like birdwatching;
Citizen cyberscience, connected with the use of technologies and can be subclassified in:
Volunteer computing: citizens offer the unused computing resources of their computers;
Volunteer thinking: citizens offer their cognitive abilities for performing tasks difficult for machines;
Passive sensing: citizens use the sensors integrated into mobile computing devices to carry out automatic sensing tasks.
Community science (Fig. 1) involves a more significant commitment of citizens also in designing and planning the project activities in a more egalitarian (if not bottom-up) approach between scientists and citizen scientists, which can be divided into:
Participatory sensing, where citizens use the sensors integrated into mobile computing devices to carry out sensing tasks;
Do It Yourself (DIY) science, which implies participants create their scientific tools and methodology to carry out their research;
Civic science, “which is explicitly linked to community goals and questions the state of things”.
Volunteered Geographic Information (VGI) refers to the geographical data that is created and contributed voluntarily by individuals or groups of people. This can include data such as location-based social media posts, GPS traces, photographs with geotags, and other forms of digital content that have a location component.
VGI is often collected and shared using web-based platforms, such as OpenStreetMap, which allow users to create, edit, and share geographic information in a collaborative and decentralized way. This can help to fill gaps in official geographic data, as well as provide more detailed and up-to-date information on specific areas or features.
VGI has a wide range of applications, including urban planning, disaster response, environmental monitoring, and cultural heritage preservation. For example, in disaster response, VGI can help to provide real-time information on the location and extent of damage, as well as on the needs and priorities of affected communities.
Overall, VGI is a powerful tool for enabling citizen engagement in the creation and sharing of geographic data and has the potential to enhance our understanding of the world around us.
OpenStreetMap uses three basic data structures to represent physical features on the ground: nodes, ways, and relations. Nodes are the most basic data structure and represent a single point in space. They can be used to represent things like individual streetlights, fire hydrants, or trees. Ways are used to represent linear features, such as roads or rivers. A way is a series of connected nodes that create a line or path. For example, a road might be represented as a way made up of multiple nodes that define its shape and length. Relations are used to represent more complex features that cannot be easily represented as a single way or node. A relation can be thought of as a container that holds multiple nodes and ways and describes the relationship between them. For example, a park might be represented as a relation that contains multiple ways for the different paths and roads within the park, as well as nodes for various features like benches, fountains, or playgrounds. The following are examples of these data structures:
Node: This example shows the representation of a node, indicating where a public bench is present (Fig. 6a)
Way: This example shows the representation of a way, indicating where a building is present (Fig. 6b)
Relation: This example shows the representation of a relation, indicating the grouping of buildings with elements inside it (Fig. 6c)
More information can be found at the WikiOSM website.
The historical development of OSM data can be accessed through the . This webpage generates accurate statistics about the evolution of OSM data for custom or predefined regions worldwide.
For example, we can have a look at the temporal evolution of OSM building data in the area of Prešov (Slovakia) by applying the following filters in the ohsome Dashboard interface (figure 7): (1) Choose the study area by selecting the administrative boundaries of Prešov in the interactive map. (2) Choose the tags of interest by typing “building” as the Key and “yes” as Value. (3) Specify all three OSM types, i.e., “node”, “way”, and “relation”. (4) Specify as Measure type “count”. (5) Define the result grouping as “none”. (6) Keep the default period (start date: 2007-10-08, end date: current day) and temporal aggregation, i.e., “monthly”. (7) Finally, press Send Request to query the database.
The result will be displayed in the Result Log section, below the Filter section. Specifically, a summary of the request filters is displayed (8) as well as a graph representing the evolution of the OSM building count (9). Finally, there is the possibility to export the result in CSV and Ohsome JSON formats (10).
In OSM, tagging is the process of assigning descriptive metadata to geographic features (such as roads, buildings, and natural features) drawn before on the map. This metadata is used to describe the attributes and characteristics of the feature, such as its name, type, size, and other relevant information.
Every feature must be described at least by one tag. The number of tags needed to describe a feature in OSM varies depending on the complexity of the feature and the level of detail required. Some features may only require a few basic tags to describe their type, while others may require dozens of tags to accurately capture all of their attributes.
The correct way to tag features in OSM involves using a specific syntax and following established conventions for each type of feature. This ensures consistency and compatibility with other OSM data and helps to maintain the quality and accuracy of the map.
To tag a feature in OSM, you need to specify the feature's type (e.g. highway, building, natural), and then add a series of key-value pairs that describe the feature's attributes. For example, to tag a secondary school in OpenStreetMap, you can use the following key-value pairs:
amenity=school
school=secondary
This assigns the key "amenity" with the value "school" to indicate that the feature is a school, and the key "school" with the value "secondary" to indicate that it is a secondary school.
In addition to these basic tags, you can also include other key-value pairs to provide more detailed information about the school, such as its name, address, telephone number, website, and so on:
amenity=school
school=secondary
name=Name of the Secondary School
address=Address of the School
phone= phone number of the School
website=http://www.secondaryschool.com
To tag a building:
building=yes
This assigns the key "building" with the value "yes" to indicate that the feature is a building. In addition to this basic tag, other key-value pairs to provide more detailed information about the building can be added, such as its name, type, address, and so on:
building=yes
building:levels=4
building:material=brick
name= name of the building (if any)
address= address of the building
The "building:levels" tag specifies the number of levels or stories in the building, and the "building:material" tag specifies the material of which the building is constructed. The "name" tag specifies the name of the building, and the "address" tag specifies its address. It is also possible to add more detailed information about specific parts of the building, such as entrances, windows, and so on. This can be done using tags such as "entrance", "window", "roof", and so on.
To tag a road as a primary highway, you would use the following syntax:
highway=primary
and then you can add much more specifications.
There are many established conventions for how to tag different types of features in OSM, and these are documented in the OSM Wiki. The conventions cover everything from basic features like roads and buildings to more complex features like transit systems and land use.
It is important to follow the established conventions as closely as possible when tagging features in OSM. This helps to ensure that your data is accurate, consistent, and compatible with other OSM data, making it more useful for everyone who uses the map.
For questions related to tagging, the best way to get help is to use the OSM community resources available online.
Here are some of the most popular websites where you can find information about how to tag in OSM:
The OpenStreetMap Wiki: This is the official wiki for OpenStreetMap and contains a wealth of information on how to tag various features in OSM. The wiki is constantly updated by the OSM community and is a great resource for learning about tagging conventions, best practices, and other aspects of mapping in OSM. You can access the OSM Wiki at https://wiki.openstreetmap.org.
Taginfo: This is a website that provides a simple interface for searching and browsing OSM tags. You can search for a specific tag or browse by tag category to learn more about how to tag different types of features in OSM. It also provides statistical information about OSM tags, including how often they are used and which features they are used to tag. Taginfo is a useful tool for understanding the prevalence and popularity of different tags in OSM. You can access OSM Tags at https://taginfo.openstreetmap.org/.
Map Features: This is another website that provides information about how to tag different types of features in OSM. Map Features provides a comprehensive list of feature types, along with recommended tags and descriptions for each type. You can access Map Features at https://wiki.openstreetmap.org/wiki/Map_Features.
Another option is to use the OSM mailing lists, which are email-based discussion forums where OSM contributors can ask questions, share information, and discuss various topics related to mapping in OSM.
The most appropriate mailing list to contact for questions related to OSM tagging is the Tagging mailing list. This list is dedicated to discussions about OSM tagging and is a great resource for getting help with specific tagging questions, discussing tagging conventions and standards, and staying up-to-date with changes to OSM tagging.
Here is the link for subscribing to the Tagging mailing list: https://lists.openstreetmap.org/listinfo/tagging
Creating an OpenStreetMap account is simple and straightforward. Follow these step-by-step instructions to set up your account:
Visit the OpenStreetMap website: Go to the OpenStreetMap homepage at https://www.openstreetmap.org/.
Click "Sign Up": Locate the "Sign Up" button in the upper right corner of the page and click on it.
Fill out the registration form: You will be directed to the registration page, where you will need to provide some basic information:
a. Display Name: Choose a display name that will be visible to other users on the OSM platform. b. Email: Enter a valid email address. This will be used for account verification and password recovery. c. Password: Create a secure password for your account. Make sure it's a combination of letters, numbers, and symbols for enhanced security.
Click "Sign Up": After completing the form and CAPTCHA, click the "Sign Up" button at the bottom of the registration page to submit your information.
Verify your email address: OSM will send you a verification email to the address you provided. Open the email and click on the verification link to confirm your account. If you don't see the email in your inbox, check your spam or junk folder.
Start contributing: Once you have verified your email address, you can now log in to your OpenStreetMap account using your display name and password. Begin exploring the platform, editing maps, and contributing to the OSM community.
Remember to keep your account information secure and never share your password with anyone. Happy mapping!
OpenStreetMap (OSM) offers a comprehensible web application with several capabilities and functionalities. When opening the website at https://www.openstreetmap.org/ the interface that is displayed in Fig. 4 will appear, showing the main OSM interface. For this tutorial, we will divide the elements of the interface into 2 categories:
In blue, are the platform functionalities and auxiliary links: Authentication buttons (1), Menu Bar (2), and the Editing and exporting bar (3).
In red, map controls: The main map (4), Search bar (5), and Map Controls (6).
OSM is a crowd-sourced map that receives contributions from thousands of users worldwide. To use the map and request data from the database it is not necessary to have an account but to add new features and edit existing ones, it is necessary to be authenticated. The authentication buttons contain the “Log In” button to log in to an existing account, and the “Sign Up” button to create an account.
The “Log In” allows users to be authenticated using existing credentials. Logging in unlocks the Editing capabilities that are going to be explained in point 3.
The “Sign Up” button takes the user to the registration page. After setting your credentials, confirming your email, and accepting the terms of service, you should be ready to Log In and use the editing capabilities of OSM.
The menu bar contains links to different pages within OSM that provide additional functionalities outside of the mapping realm and information related to OSM activities.
GPS Traces: Users can upload GPS traces to OSM from a GPS device. On this page, a list of all the public GPS traces uploaded by users can be found.
User Diaries: Similar to a blog where users can post their user stories and interact with the community via comments.
Communities: Information on the OSM local chapters and groups over the world.
Copyright: Information about copyright and licensing, including information on how to credit OSM, links to the full licenses, and the list of contributors.
Help: Page with links to several resources regarding the OSM functionalities and activities, such as forums, guides, discussions on mapping topics, and the Wiki.
About: General information on what is OpenStreetMap.
This bar contains the editing and exporting functionalities of the OSM platform, as well as the editing history showing all the edits made by OSM users.
Editing: The edition consists in adding or changing the features of the OSM map. This means that anyone can change the look of the OSM map, keeping it updated. The easier way to edit the map is through the in-browser editor directly on the platform map. The editing tool adds to the map a layer containing satellite imagery and activates the editing tools. This allows the user to draw features (points, lines, or polygons) that match real-life objects. Fig. 5 shows the map editing interface.
History: Show the entire list of changes in the OSM database. It includes information on the user that made the edit, the date, and the comments of other users.
Exporting: This tool allows the user to export OSM map features in an area set by the user. By default, OSM downloads data using their format, but it is possible to use other platforms such as Overpass Turbo or Planet OSM to filter and get data in other formats that could be used in different software or on a web page, or to download the whole database.
4. The main map
The main map displays a web map that shows what the user has selected using the map controls that will be shown in point 6.
The Search bar allows users to search places in the OSM database. It works by typing a word and clicking on “Go” or pressing enter. The search then fetches the most similar features on the OSM database and shows them as a list.
The search tool also allows getting routes from one place to another, similar to Google Maps or Waze, using different providers for Foot, Car, or Bicycle such as GraphHopper, OSRM, and Valhalla.
Map controls contain several additional map functionalities to navigate and change the map visualization.
Zoom controls: Zoom in and zoom out of the map;
Show my location: Inserts a marker on the map in your position (provided by the device you are using), and centre the map to the position;
Layers: Allow users to change the base map and add additional layers provided by OSM. The base maps provided are the Standard OSM map, CyclOSM and Cycle Map contain data on cycling paths all over the world, the Transport Map and ÖPNVKarte show public transport facilities and the Humanitarian focuses on resources useful for citizens and humanitarian organizations in emergencies. Other interesting layers include the “map notes” which show notes added by the community, and “map data”, which loads the map features as vectors;
Map Key: Map legend. Only available for some map layers;
Share: Options for exporting and sharing the map. The map can be exported as a link to the OSM map, an embedded web page, and an image;
Add a note to the map: Allow users to insert map notes for pointing out mistakes in the map or report that something is missing;
Query Features: Allows to obtain vector features from the OSM database. It queries the database looking for features near a selected point;
This chapter provides a brief explanation and importance of organizing a humanitarian event "Mapathon". It is a modern digital form of volunteering that is accessible to everyone, regardless of age. Through the organizing of Mapathon event, we can improve the quality of the world's data on maps, as well as meet people from around the world and exchange knowledge. We think it is important to spread awareness about this form of volunteering, so that even more people can get involved. In this case, we have prepared a detailed step-by-step manual that will explain how to organize Mapathon and how to map on the TeachOSM humanitarian platform using the iD editor. This step-by-step manual is supplement by instruction images taken from task #1148 Mapping Tartus created by the student community PoliMappers from Politecnico di Milano.
Mapathon event, well known as a "mapping marathon" is a modern digital form of volunteering. It is an event, which is accessible to everyone, regardless of age. All what participants need to have is a computer device with a mouse, an internet connection, created account on OpenStreetMap and a willingness to help.
The mapathons used to be usually face-to-face meetings, but due to the COVID-19 pandemic situation were completely all sessions taken to online space. After the COVID-19 pandemic people realized that it is great to organize mapathons in both ways, face-to-face and online at the same time. The reason is that people from around the world could also get an opportunity to join (Fig. 1).
The main aim of mapathon is to map buildings, roads, waterways etc. in areas that are blank on maps or areas that have been damaged by natural disasters (e.g hurricanes, tornadoes, floods, earthquakes) or pandemics. For the purpose of mapping is used the Tasking Manager platform, such as HOT OSM, or Teach OSM).
We will work with the Teach OSM humanitarian platform. The projects ready for mapping are divided on this platform into smaller tasks that can be collaboratively completed by various people at the same time (Fig. 2). In this way, mapathon participants are helping, for example, international humanitarian organizations such as the Red Cross or the Doctors without borders to deliver healthcare or other services to these areas and give assistance to people in need. Besides that, all created changesets and improvements in maps made by volunteers during mapathons help to remote areas in the world with development of disaster risk management and energy management. The brand-new data become open and it means that everyone can use them.
Organizing events of this kind helps to build a stronger community of mappers in the whole world. We would like to mention as an example the global student network YouthMappers created in 2016 in the USA (Fig. 3). This organization already succeeded in building a stronger community of mappers from universities. They currently have more than 5 000 members from 72 countries.
The members of YouthMappers community are also European universities, for example University of Prešov as UNIPO Mappers, Politecnico di Milano as PoliMappers (Fig. 4, 5). It is important to mention that OpenStreetMap currently has more than 8 million contributors. It is a great number, but on the other hand, it is still not enough when we imagine the planet Earth with 7 billion inhabitants. Joining or hosting a mapathon is a fantastic way to meet people of many nationalities from other countries, share ideas, get some more experiences and learn something new.
For your first mapping with iD editor it is very useful to complete the provided Walkthrough (Fig. 21). The walkthrough will explain how to navigate around the map, how to zoom in and out and how to mark points, areas, lines and building into the map. When you are familiar with mapping these features, you are ready to move on to mapping the real objects. Click “Start Editing”.
First of all, it is very important to set the imaginery according to previous instructions. In this case, we need to set imaginery for “Maxar Premium Imagery” (Fig. 22).
You are ready to map! Zoom in so you can see the features clearly.
Click to “Area” to start mapping the buildings.
Start by clicking on the corner of the building and continue to mark other corners. By clicking on the last corner again you can finish the process. Walls of the building will be red (Fig. 23).
Now it’s important to select a feature type. This window will pop-up automatically after marking the building (Fig. 24):
choose “Building” as a feature type
After selecting the feature type you can square the corners of the feature by pressing “Q” on your keyboard (Fig. 25). All other useful shortcuts are visible after clicking on the map with right-click (Fig. 26).
That’s it! After finishing the mapping you can save your changes and upload them to OpenStreetMap (Fig. 27).
Click „Save“ - the window with Changeset Comment and Hashtag will pop-up (Fig. 28)
At the bottom (Fig. 29), there is an option of reviewing the edits. If you are unsure with your edits, check the box and let someone more experienced check your work. Click “Upload” and your changes will be added to OpenStreetMap.
After finishing your mapping session it is important to mark the stage of the task:
if you mapped the task completely, check “Yes”
if there are still some buildings left, or you are not sure, check “No”
if you can not identify the buildings because of poor imaginery, check “The imagery is bad” (Fig. 30)
There is also a possibility of writing a comment about the task. If the task is too big and contains too much features, there is an option to split it and share with other participants by clicking „Split task“ (Fig. 31).
In the previous chapter, we conducted a Mapathon using the TeachOSM platform to map the Tartus task. To remind, Mapathons are collaborative events where volunteers gather to improve and update maps. During a Mapathon, participants focus on mapping of simple and easily visible objects from satellite imagery backgrounds. This is an essential first step in creating new objects on the map and contributing to the OpenStreetMap (OSM) database.
However, sometimes there is a need for more detailed mapping, especially in pupil-led projects. This may include adding new attributes (keys) to the OSM database. Field mapping becomes crucial in these cases, as it allows for the collection of more comprehensive and accurate data. To meet this demand, the current chapter will focus on a workshop that integrates OSM and smartphone mapping tools to facilitate field mapping activities.
The primary objective of this chapter is to introduce high school teachers and their pupils to open field mapping tools and their potential applications in addressing climate change challenges. By providing an overview of popular smartphone tools, real-world examples, and hands-on exercises, we aim to equip teachers with the necessary knowledge and resources to integrate mapping activities into their lesson plans effectively.
Field mapping is the process of collecting geospatial data from the actual location to create more detailed and accurate maps with new information. To help secondary school teachers understand the main concepts and methodology of field mapping, we will break down the process into several key components:
Field Mapping Concepts and Methodology to Secondary School Teachers
Field Mapping Objectives:
Begin by explaining the importance of field mapping in capturing accurate and up-to-date information that may not be available or visible through satellite imagery alone. Field mapping can be used to add new features, update existing data, and verify the accuracy of the map. Proper objectives for the topic could come from Problem statement methodology.
Preparation:
Prior to conducting field mapping, teachers should plan the area to be mapped, establish goals, and determine the required tools and resources. Some common tools used in field mapping include smartphones, paper maps, and field mapping applications.
Smartphone Mapping Applications:
Introduce various smartphone mapping applications that can be used for field mapping, such as Go Map!!, Vespucci, StreetComplete, MapComplete, Mapillary, etc. Demonstrate how these tools can be used to collect data, add new features, and edit existing information on the OpenStreetMap platform.
Field Data Collection:
Teach the various methods of collecting data in the field, such as taking notes, making sketches, capturing photographs, and using smartphone mapping applications to collect spatial data (various attributes). Emphasize the importance of accurate and consistent data collection.
Data Validation:
Explain the importance of validating the collected data to ensure its accuracy and completeness. This can be done through cross-referencing with other sources, reviewing and comparing data with peers, or using quality assurance tools within the OpenStreetMap ecosystem.
Before we begin the exercise, we have listed potential objects for future mapping below. OpenStreetMap provides a flexible platform for mapping various objects that can be useful for climate change analysis. These objects can be classified into basic, intermediate, and advanced categories based on their complexity and the level of detail required for mapping. Here are some examples of objects in each category:
Basic Objects:
Land use: Mapping land use categories such as residential, commercial, industrial, agricultural, and green spaces helps in understanding the distribution of urban heat islands and other climate-related risks. We can map type of vegetation or crops; land management practices; land cover quality, etc.
Key: landuse
Tags: landuse=residential, landuse=commercial, landuse=industrial, landuse=agricultural, landuse=greenfield
Water bodies: Mapping rivers, lakes, ponds, and other water bodies provides insights into water availability, flood risks, and potential areas for natural cooling. We can map water quality indicators (e.g., presence of algae or pollutants); flow rate and direction; bank conditions and stability, etc.
Key: natural
Tags: natural=water, water=river, water=lake, water=pond
Trees: Mapping individual trees and groups of trees helps in understanding their role in temperature regulation, shades imapct or humidity retention. We can map tree species; tree age; tree height; health condition, etc.
Key: natural
Tags: natural=tree Additional attributes: species=* (e.g., species=Quercus_robur), height=, age=, health=*
Intermediate Objects:
Urban green infrastructure: Mapping elements such as parks, gardens, green roofs, and green walls provides information on the availability and distribution of green spaces that can help mitigate climate change impacts in urban areas. We can map types of vegetation in parks and gardens; green roof/wall installation details (e.g., depth of substrate, plant species); accessibility and usage patterns, etc.
Key: leisure
Tags: leisure=park, leisure=garden
Additional attributes for green roofs/walls: roof:material=green_roof, wall:material=green_wall
Drainage systems: Mapping stormwater drains, culverts, and retention basins can help assess the capacity of urban areas to manage flooding and heavy rainfall events. We can map material and condition of stormwater drains and culverts; blockages or damage; maintenance practices , etc.
Key: man_made
Tags: man_made=drain, man_made=culvert
Additional attributes: material=, diameter=, condition=*
Coastal infrastructure: Mapping sea walls, dikes, and other coastal protection structures can help identify areas at risk from sea-level rise and storm surges. We can map construction materials and techniques; condition and age of structures; vulnerability to erosion or storm damage, etc.
Key: man_made
Tags: man_made=dyke, man_made=seawall
Advanced Objects:
Climate adaptation measures: Mapping elements such as flood barriers, heat-resistant pavements, and tree planting initiatives can help assess the effectiveness of various climate adaptation strategies. We can map type and effectiveness of flood barriers; heat-resistant pavement materials and installation techniques; tree planting initiatives (e.g., species, planting density, maintenance practices), etc.
Key: barrier,
Tags: barrier=flood_control
Key: surface,
Tags: surface=heat_resistant (note: this is not a standard tag, but can be used for custom mapping)
Key: landuse,
Tags: landuse=forest, landuse=orchard
Vulnerable populations and infrastructure: Mapping the locations of vulnerable populations (e.g., elderly, low-income, poor and segregated populations) and critical infrastructure (e.g., hospitals, emergency shelters) can help identify areas at higher risk from climate change impacts and inform targeted adaptation measures. We can map accessibility and capacity of emergency shelters; condition and resilience of critical infrastructure; support, services and resources available for vulnerable populations, etc.
Key: social_facility,
Tags: social_facility=, social_facility:for=
Key: amenity,
Tags: amenity=shelter, shelter_type=emergency
Key: amenity,
Tags: amenity=hospital, amenity=school, amenity=fire_station
Renewable energy infrastructure: Mapping solar panels, wind turbines, and other renewable energy sources can provide insights into the potential for clean energy generation and reducing greenhouse gas emissions. We can map installation details (e.g., capacity, orientation, age); type and model of equipment; maintenance history, etc.
Key: power
Tags: power=generator
Additional attributes: generator:source=solar, generator:source=wind, generator:output=* (e.g., generator:output:electricity)
Remember that OpenStreetMap is a flexible platform, and additional keys and tags can be used or created as needed to represent specific attributes or objects. Always consult the OSM wiki for guidelines and best practices when mapping and tagging objects.
Browse the wiki pages for better understanding of map features:
Map features – a list of accepted tags grouped by key meaning.
Taginfo – an site to explore current tag usage in the OSM database, including tag values that are not necessarily documented (but it includes links to this wiki if there is a documentation for a tag)
TagFinder – Website providing full text search engine for OSM tags. (Also webservices available).
Smartphone mapping tools are essential for field mapping, as they allow users to collect and edit data on-the-go. In this section, we will introduce and briefly describe four popular smartphone mapping tools that offer offline editing capabilities, which are particularly useful in areas with poor or no signal coverage:
Go Map!! is an iOS-based mapping application that enables users to edit OpenStreetMap data directly on their devices. The app allows users to add and modify map features such as roads, points of interest, and buildings. Go Map!! supports offline mapping, which means users can download map data for a specific area and continue editing even without an internet connection.
Vespucci is an OpenStreetMap editor for Android devices. It provides users with the ability to edit and contribute to OSM while in the field. With its offline editing capabilities, users can download map data for a specific region and work on it without the need for an internet connection. Vespucci supports various types of map features, including points, lines, and areas, allowing users to create detailed maps.
Mapillary is a street-level imagery platform that allows users to contribute geo-referenced photos using their smartphones. These photos can be used to improve and update OpenStreetMap data. The Mapillary app, available for both iOS and Android devices, enables users to capture and upload images while in the field. The app also offers offline capabilities, allowing users to continue collecting images without an internet connection.
Field Papers is a web-based tool that enables users to print and create atlases from OpenStreetMap data. Users can annotate these printed maps in the field and then scan or photograph them to create geo-referenced images. These images can be uploaded to Field Papers' website for further editing and integration into OpenStreetMap. While Field Papers is not a smartphone app per se, it is a valuable tool for field mapping, especially in areas with poor connectivity.
MapComplete is a user-friendly platform designed to make contributing to OpenStreetMap more accessible and enjoyable. It allows users to create custom map themes and offers easy-to-use tools for adding and editing map features. We will provide the step-by-step manual in the next chapter.
By introducing these smartphone mapping tools, participants will be better prepared for open field mapping activities, even in areas where internet connectivity is limited or unavailable. The offline editing capabilities of these applications ensure that users can continue to contribute valuable data to OpenStreetMap, regardless of their location.
Every Door is a 100% independent tool, free from third-party endpoint dependencies. This editor allows you to view all nearby shops and amenities accurately, without geospatial displacement. Utilize the check_date tag to verify the existence of shops, edit buildings, and add entrances with apartment numbers. In micro-mapping mode, you can map every manhole, bench, tree and street lamp, etc. Additionally, pre-load imagery tiles to work offline, ensuring a seamless mapping experience.
In recent years, climate change has emerged as one of the most pressing global challenges, with far-reaching consequences for the environment, economy, and society. Addressing these challenges requires not only a thorough understanding of the underlying issues but also innovative and accessible tools that enable individuals and communities to take action. This is where the power of open field mapping tools can come into play as one of the possible options.
Understanding the relationship between climate change and geospatial data is crucial for developing effective strategies to mitigate and adapt to the impacts of this global challenge. Geospatial data plays a vital role in monitoring, modeling, and managing the complex interactions between human activities and the environment and thus this data helps to track, analyze, and visualize these factors and their impacts on ecosystems, human settlements, and infrastructure. By providing spatial context and insights, geospatial data enables researchers, policymakers, and communities to make informed decisions and implement effective climate change mitigation and adaptation measures.
OSM. ‘OpenStreetMap. OpenStreetMap Organization. Accessed 11 March 2023. More at: https://www.openstreetmap.org/.
‘OpenStreetMap Wiki’. Accessed 09 March 2023. More at: https://wiki.openstreetmap.org/wiki/Main_Page.
Ohsome dashboard’. Accessed 11 April 2023. More at: https://ohsome.org/apps/dashboard/.
‘UN Mappers’. Accessed 11 April 2023. More at https://mappers.un.org/
Welcome to the Mapathon Workshop, where we will introduce you to the exciting world of community mapping!
In this workshop, we will explore the power of open source mapping tools and how they can be used to support humanitarian efforts around the world. We will begin by setting up an OpenStreetMap account, which is a free and open mapping platform that allows anyone to contribute to mapping projects. We will then take a walk around the humanitarian mapping platform, TeachOSM, which is a comprehensive resource for learning about mapping for social good. Next, we will dive into the process of mapping a task, which involves identifying a specific area or issue that needs to be mapped and working together to create a detailed map of that area. You will learn how to use OpenStreetMap's editing tools and how to collaborate with others to ensure accuracy and completeness in your mapping efforts.
By the end of this workshop, you will have the skills and knowledge to contribute to mapping projects and make a positive impact in the world. So let's get started!
Here is a step-by-step guide to using the TeachOSM Tasking Manager:
Go to the TeachOSM website.
Click on the „Log in“ button in right corner (Fig. 7)
Use your already created account from OpenStreetMap and please authorize access to your account by pressing button „Grant Access“ (Fig. 8)
After logging in you’ll see the same interface as in (Fig. 9). Let’s explore together the website TeachOSM.
In this section you will find tasks and projects available for mapping (Fig. 10)
you can sort tasks and project according four criteria:
a) difficulty level - beginner mapper, intermediate mapper, advanced mapper
b) project status - projects to map, projects to validate, any project
c) more filters - you can sort projects according:
o campaign
o organization
o location
o type of mapping
d) sort by - urgent, active, new, old, beginner and advanced projects
e) search project - when you are looking for a specific project and you know its number, you can do it quickly by using search engine (Fig. 11)
We’ll work together on the task Mapping Tartus with number #1148 !
this section provides statistics about your mapping activity such as (Fig. 12):
number of buildings, roads, waterways and points of interests you mapped
overall number of hours you spent mapping
detailed contribution timeline
projects and tasks you worked on
what top 5 countries you already mapped
this section provides quick instructions how to map, how to validate data and how to organize mapping events like mapathon (Fig. 13). We will show you how to map more in deep in the next part.
In this section you will find some more information about Tasking Manager (Fig. 14)
Normally, the same editor is used for validation as for mapping, but it is of course also possible to use more refined editors such as JOSM (JavaOpenStreetMap). This is a non-online editor, so you need to download the data locally, and it is a refined editor because it has the structure of a GIS capable of handling layers of data (https://josm.openstreetmap.de/).
Another useful tool is OSMCHA (OpenStreetMap Changeset Analyser), a web tool to help visualize and analyze edits made by mappers. OSMCHA allows detailed views of individual user operations and is very effective on organized projects (https://osmcha.org/). In this case the process is the so-called a ‘Stage 2’ validation, related to town or city scale, covering the full area of the project (Fig. 8).
Finally, also of note is OSMOSE, which is used for automatic error detection on large datasets. (https://wiki.openstreetmap.org/wiki/Osmose).
In OpenStreetmap Wiki (https://wiki.openstreetmap.org/wiki/Tasking_Manager/Validating_data) the instructions step by step, for different categories, are reported, including the hints for the messages accompanying the validation operation.
As mentioned at the beginning of the paragraph, the final map must be correct in order to be used, so, especially in humanitarian projects, during validation errors must be detected and corrected. However, it is necessary to emphasize that, for a teaching purpose, during validation more than correcting one should push the mappers to correct themselves so that they become aware of the overall work.
After completing the Mapathon, we use MapComplete to conduct field mapping, focusing on collecting additional tree attributes such as height, type of leaves, and tree species. This step complements the data gathered during the Mapathon, ensuring a comprehensive and accurate representation of the tree distribution in the selected area.
Process of the Second step of the Exercise
Introduction to MapComplete: Participants are to be introduced to the MapComplete platform. The platform's purpose, features, and its use in creating custom map themes for specific mapping projects should be explained.
Training and Demonstration: A tutorial on using MapComplete to add, edit, and tag trees with the custom theme should be provided to participants. The key features of the platform, such as searching for specific map elements, adding photos, and using the editing interface, should be highlighted.
Field Mapping: Participants are to be instructed to venture into the selected area and begin mapping trees using MapComplete on their smartphones or tablets. The collection of as much information as possible about the trees, including species, height, and other relevant attributes, should be encouraged.
Data Validation and Integration: Upon completion of the field mapping, participants are to be guided through the process of validating their collected data and integrating it into the OpenStreetMap database. The importance of ensuring data accuracy and adherence to OSM guidelines should be emphasized.
Analysis and Discussion: Following the exercise, the mapped data should be analyzed to gain insights into the distribution of trees within the selected area and their role in mitigating climate risks. Participants should be encouraged to discuss their findings and share their experiences using MapComplete.
By using the MapComplete platform to carry out this tree mapping exercise, participants will not only gain valuable experience with a user-friendly mapping tool but also contribute to a better understanding of the role of trees in addressing local climate risks.
MapComplete is a user-friendly platform designed to make contributing to OpenStreetMap more accessible and enjoyable. It allows users to create custom map themes and offers easy-to-use tools for adding and editing map features. We will provide the step-by-step manual on how to work with MapComplete in your smartphone.
Fig 6: Open the URL https://mapcomplete.osm.be/.
Fig 7: Log in to the OSM platform. This is important because, without an OSM login, you cannot add any feature. Then click on the "Open the map" icon.
Fig 8: Look around the interface. The main navigation tools are located at the bottom of the screen. At the bottom right, you will see the quick switcher (1) between the OSM map and the Satellite map (note: the source of the satellite map is rendered based on your mapping location). Above it is the "Select layers" icon (2), where you can define a specific background layer for a purpose, for example, if you want to see the cyclopaths tracks. You can also go back to the themes browser here. The "Positions" icon (3) finds your location based on your smartphone's GPS signal. There are zoom in and zoom out icons (4). With the "?" icon (5), you can open the theme options, where you can find a description of the topic, create your own topic, and share the map with colleagues.
Fig 9: Click on the tree near "Click here to add a new item" to add a new tree that is missing.
Fig 10: Click on an existing tree object and edit the tags.
Fig 11: Leaf type (key: leaf_type).
Fig 12: Adjust the position if needed.
Fig 13: What species is this tree? (key: species).
Fig 14: What is the circumference? (key: circumference).
Fig 15: What is the height of this tree? (key: height).
Fig 16: How significant is this tree? (key: denotation).
Fig 17: You can now check all the attributes you have added.
Fig 18: In case you did the test mapping, you can delete the feature.
Finally, it is time to map your first task. As mentioned before, we will work with the project Mapping Tartus #1148. Tartus is the second largest port city of Syria, located on the Mediterranean coast. The project is aimed to map the buildings of the port city Tartus in such a way to help humanitarian activities of the World Food Program (WFP) in that area.
it includes essential information about the project and mapped area
when you get familiar with the task click „Contribute“ (Fig. 15)
understanding all instructions is crucial for correct project contribution
in instructions you will find following information (Fig. 16):
what you should map (eg. buildings)
what imaginery you should use (eg. MAXAR Premium Imaginery)
what tags you should add after mapping a feature (eg. #poliMi_WFP_Tartus)
what you should pay attention for (eg. follow accurately the footprint of the building)
in the section „TASKS“ you can check the latest contributors of Mapping Tartus #1148
under the section „CONTRIBUTIONS“ you can see number of changes made by different contributors (Fig. 17)
the project Mapping Tartus #1148 is aimed to map buildings (Fig. 18)
mostly in some available advanced tasks you can meet with mapping other features:
roads, waterways, landuse or more (Fig. 19)
here you can see the tiles that are being mapped at this project
select one of white tiles, which are available for mapping
then click “Map selected task” (Fig. 20)
you can also map a random task. In that case you don’t need to select a tile. Just click “Map a task” and you will be assigned with a random tile which you can map.
This chapter provides practical guidance to begin preparing pupil-led projects in each school. In a dedicated workshop (as defined in Step 1 of this document), teacher teams will first diagnose their school contexts and opportunities (teachers involved, subjects, school ongoing projects, strategic lines, coordination requirements, etc.). Then, they will define and evaluate two possible challenges that will be presented to the pupils later (Step 2). Finally, the pupils will select the school challenge through a participatory process (as part of Step 3). During the workshop (Steps 1 and 2) teacher teams work through different templates in a collaborative whiteboard under the guidance of an expert teacher trainer. The results of this preparatory work seek to enhance coordination and participation of teachers and pupils, being the starting point for the next module.
First step is to conduct a Mapathon using TeachOSM to create a task focused on tree mapping in the given area. The Mapathon will involve volunteers adding visible tree features from satellite imagery, while the field mapping using MapComplete will follow as a second step to complete attributes such as type of leaves, tree species height, and more. This two-step approach ensures that the map data is comprehensive and accurate.
Process of the First step of the Exercise :
Task Creation: Create a new task on TeachOSM focused on tree mapping in the selected area. Define the boundaries of the mapping area, set the task's objective, and provide clear instructions for participants on how to identify and map trees using satellite imagery.
Training and Preparation: Provide participants with training on how to use the TeachOSM platform and its tools to add tree features to OpenStreetMap. Ensure that volunteers are familiar with the mapping process and the specific requirements of the tree mapping task.
Conduct the Mapathon: Organize a Mapathon event, either in-person or virtual, where volunteers can work together to map tree features within the selected area. Encourage participants to communicate and collaborate throughout the event to ensure the best possible results.
Data Validation: Review the mapped data from the Mapathon to ensure its accuracy and completeness. Make any necessary corrections or additions before proceeding with the field mapping using MapComplete.
Ready for Field Mapping
By combining a Mapathon using TeachOSM with field mapping using MapComplete, you can create a detailed and accurate map of tree distribution in a given area, helping to better understand their role in mitigating climate risks and informing urban planning and climate adaptation strategies.
The validation process plays a critical role in maintaining high standards and improving the quality of data in a mapping project. Mapping work performed on a voluntary basis by non-professionals must undergo validation to ensure accuracy and consistency, which are essential for reliable information on the map.
The validator's responsibility is to ensure that the mapping work meets the project's specifications and is executed correctly. In evaluating each task, completeness and correctness are the two crucial aspects that must be considered. Completeness refers to identifying all the elements accurately, while correctness entails ensuring that mapped entities are geometrically and semantically correct. Therefore, during the validation process, errors must be detected and corrected. However, for teaching purposes, it is also essential to encourage mappers to correct their own work and become aware of the project's overall goals, rather than just correcting errors during validation.
This exercise aims to equip participants with the knowledge and skills necessary for detailed mapping using OpenStreetMap and smartphone app. In the following sections, we will explore the steps and guidelines for conducting the field mapping.
Clearly state the issue or challenge that needs to be addressed through field mapping. This could be a lack of data, inaccurate information, or any other problem that can be resolved through the collection of geospatial data.
Example: The distribution of trees within the selected area is not well-documented, and their role in mitigating climate risks is not well-understood.
Describe the importance of addressing the identified problem and how it impacts the community, environment, or any other relevant stakeholders.
Example: Understanding the distribution of trees and their role in mitigating climate risks can inform urban planning and climate adaptation strategies, ultimately contributing to a more sustainable and resilient community.
Clearly outline the goals of the field mapping project, specifying what data needs to be collected and what questions the project aims to answer.
Example: The objective of this field mapping project is to map the distribution of trees within a selected area and collect data on their attributes (e.g., species, height, age, health status) to better understand their role in addressing local climate risks.
Provide an overview of the methods and tools that will be used to collect data in the field, including any specific techniques or technologies that will be employed.
Example: Mappers will combine Mapathon for rapid collection of the visible data and use MapComplete on their smartphones or tablets to collect additional attributes about trees. They will also can take images for validation purposes.
Explain the anticipated results of the field mapping project, including any insights or discoveries that may be made as a result of the data collection.
Example: The expected outcomes of this project include a comprehensive map of the distribution of trees within the selected area, as well as insights into the role of trees in mitigating climate risks such as urban heat islands, humidity retention, and shadowing.
By following this methodological template, mappers can create a well-structured problem statement that clearly defines the purpose and objectives of their mapping (field) project, ensuring that their efforts are focused and impactful.
The good preparation process is important. We offer the tags (key=value) which could be added are listed in the table below.
Key | Value | Description | Wiki Link |
---|
The school teachers involved in the pupil–led projects will work in groups, one per school. Different group dynamics can be used to try to compose a first overview of each school context. School teachers will lead the process and may have the support of other local partners. Table 1 presents a guide to start reflecting on the school context.
Once this starting point phase is completed, each school team will have a better understanding of the opportunities and requirements that the design and implementation of the mapping projects will have.
natural | tree | Identifies a single tree |
leaf_type | broadleaved/needleleaved | The type of leaf for the tree |
species | Scientific name | The scientific name of the tree species |
circumference | Circumference in cm | The circumference of the tree trunk at breast height |
height | Height in meters | The height of the tree |
denotation | Urban/Avenue/Agriculture/Park/Street/Landmark/Garden | Denotation of the location |
leaf_cycle | evergreen/deciduous/mixed/ | Describes the phenology of leaves, for instance evergreen or deciduous |
diameter_crown | Diameter in meters | The diameter of the tree's crown |
genus | Genus name | The genus of the tree |
tree:age | Age in years | The estimated age of the tree |
Upon completion of steps 1 and 2, each school team will continue working on its own on the challenges, to prepare the required scenario for next academic year / module.
The following items can be of help in preparing the school for the challenge:
Pre-design of the rest of the challenges.
Session with the students: They will choose one challenge from the two/three options preselected by the teachers.
Motivation towards the context (engagement question, video, activity, etc.). For example, the teacher could start by asking the students: “Think about the neighbourhood or the school. How would you describe the environmental quality? Would you change anything?” At this point and so that the discussion does not extend beyond 5 minutes, collect the main ideas and tell them that there will be time to analyse the needs later.
Short video of students of similar age around the world working toward environment enhancement. Reinforce the idea that similar pupils are capable of diagnosing their surroundings needs and being critical.
Brainstorming of context needs: In teams, students will write down on post-it the problem/s that need to be tackled in the neighbourhood or at school. At this moment, it is important to motivate the students so that they can put all the ideas that they come up with on paper. Be very insistent that the more ideas there are, the better.
Once they have all the ideas written (in disorder), ask them to group the post-its (ideas) into categories or clouds, and they will put a title for each category.
Connect the pupils’ categories with the challenges predesigned by the teachers (probably the categories will include the challenges pre-selected by the teachers).
Challenges to deep understanding: It is important to get a deeper understanding of the challenges. A Problem Tree Analysis can be useful to think of the causes and effects, and also to reflect on the stakeholders to be potentially involved. A SWOT analysis or checklist could also be useful for scoring the different options.
Challenge selection: The pupils will vote on the challenge they want to work on.
Challenge connection with the SDGs (Sustainable Development Goals). A video to introduce the SDGs can be useful, as well as a short work in teams to define connections of the challenge and the SDGs.
Teamwork of teachers: Analyse how the different subjects can be incorporated into the chosen challenge. You can use the 5 Ws (and 1 H) questions:
What: contents of each subject (common topics, complementary topics)
When: timetable or planning (including time to meet and organise the tasks (it may be necessary to ask the school head for a common hour per week to coordinate the actions)
Where: school, streets, parks, etc.
How: organise the activities and resources.
Why: the purpose.
Who: responsible/coordinator(s).
The content provided in this step-by-step manual incorporates materials developed by Politecnico di Milano, Learn OSM and TeachOSM which are licensed under a Creative Commons Attribution (CC-BY) license.
Go Map!!: https://wiki.openstreetmap.org/wiki/Go_Map!!
Vespucci: https://vespucci.io/
Field Papers: http://fieldpapers.org/
Mappilary: https://www.mapillary.com/
Haklay, M., & Weber, P. (2008). OpenStreetMap: User-generated street maps. IEEE Pervasive Computing, 7(4), 12-18.
Neis, P., & Zipf, A. (2012). Analyzing the contributor activity of a volunteered geographic information project — The case of OpenStreetMap. ISPRS International Journal of Geo-Information, 1(2), 146-165. https://www.mdpi.com/2220-9964/1/2/146
TeachOSM: A collaborative platform for teaching OpenStreetMap. Retrieved from https://teachosm.org/
MapComplete: A user-friendly platform for contributing to OpenStreetMap. Retrieved from https://mapcomplete.osm.be/; https://github.com/pietervdvn/mapcomplete
Foody, G. M., Mooney, P., & See, L. (2015). Current status and future trends in crowd-sourced geographic information. In Crowdsourcing Geographic Knowledge (pp. 1-12). Springer, Dordrecht. https://www.mdpi.com/2220-9964/5/5/55
NASA (2023). GISS Surface Temperature Analysis (v4). https://data.giss.nasa.gov/gistemp/maps/index_v4.html
Mapping is a crucial activity that requires accuracy and consistency to ensure the information presented on a map is reliable.
In a perfect mapping scenario, contributors adhere to instructions and accurately map the tile. However, this is not always the case. Therefore, the validation process is in place to maintain a high standard and continuously improve the quality of the data, ensuring its consistency and reliability.
There are two fundamental premises that should be considered when creating a map: the map must describe a reality that is verifiable, and, according to the philosophy of OpenStreetMap (OSM), anyone can check, correct, or integrate any previously mapped data.
Even non-expert users' mapped data is part of a project whose use often goes beyond the project's scope. As such, mapping work that is performed non-professionally but on a voluntary basis by non-professional citizens or students must be checked and validated. The validation process is equally important because it allows the validator to provide comments that help "train" the mapper. The validator can point out inaccuracies that the mapper can avoid in subsequent mappings. Therefore, mapping work requires accuracy and consistency to ensure the reliability of the information presented on a map.
The validation process is critical in ensuring that the mapping work is consistent with the project's specifications and executed correctly. The validator's role is to check the data's consistency entered with the project's requirements. This activity is crucial since it allows all the mapping work done in previous times to be preserved. Without validation, there is a risk of having to discard all the work previously done, which can be detrimental to the project's progress.
Those who create the project generally decide who can map and who can validate the mapping once it is completed. As a rule, these tasks are assigned to specific groups, and the one in charge of validation is an experienced mapper.
Each project has a different level of mapping complexity, ranging from Beginner to Intermediate to Advanced. Project Creators can limit the validation process to those with appropriate expertise for the difficulty level or complexity of the mapping in their project.
The validation operation is almost always done within the Tasking Manager, using the same editor that was used to perform the mapping. More generally, the purpose of the Tasking Manager is to divide a large mapping project into smaller tasks, with many people contributing to the goal set in the project. The areas that need to be mapped, those that need to be reviewed, those that need to be validated, and which areas have been completed are then shown (Fig. 1).
Within TeachOSM (accessed with your OSM account) it is possible to explore existing projects, see what percentage of area has been mapped and what percentage has been validated. In Teachosm.org, areas that have yet to be completed appear yellow, those that need to be validated appear blue. In general, the legend that appears implicitly establishes a priority of tasks to be performed on that area.
The validator sees exactly the instructions that guided the mappers during their work (e.g., mapping only the buildings in this area) and in this way the verification of the work done is well defined (Fig. 2).
Validation begins only when the mapping activity on a certain area is declared finished, whereas, on the other hand, control of the operating users can be carried out at any time. Thus, with validation, all activities are stopped, and when validation is completed, the project is declared completed.
On an open project in the Tasking Manager, it is possible to check the different time levels of mapping contributions: who mapped that area and when. The temporal level is important because with the passage of time it is possible that the actual situation has changed (for example, a new building is built, or another is demolished).
Therefore, before analyzing the data we check the mapping history, that is, how many and which users have operated and any comments they have left. The validation process is carried out on the tasks into which the project itself is divided, which are then validated one at a time. The process starts only when the mapping is declared "completed." The most common issue is a simple mistake that anyone can make, where a task is marked as complete even though it's clear that the majority or entirety of the task still needs to be mapped.
Within each task, two key aspects must be evaluated:
Completeness, that is, whether all the elements (required by the project) have been identified.
Correctness, i.e., whether the mapped entities are geometrically (example buildings should be squared) and semantically (the tag associated with individual elements) correct.
The correctness must be evaluated from several aspects. First, the temporal aspect must be considered. For example, in the mapping of satellite images, if the image was too "old" this could lead to an outdated and therefore not useful result. In this case the validator can intervene by giving feedback to the user who will then use the final map.
Of course, the geometric aspect is also crucial: the geometry of the mapped entities must be correct. In general, regular geometry is required according to standards that depend on what the mapped entities are. For example, buildings must be square, that is, have 90-degree angles even if they appear different in the satellite image. This is because there is a convention in OSM to consider the building object defined in this way. It can of course also be a different geometry (for example, a circular entity is used to describe huts) but always regular (Fig. 3, 4, 5). Regarding linear elements (e.g. roads) the main checks on the geometry that must take place are:
a. lines must join "nodes."
b. lines must not intersect each other,
c. they must consist of as few nodes as possible,
d. intersections must coincide with a node.
For the entities "points" there are no possible geometric inconsistencies but very often semantic inconsistencies, that is, related to the tag that is associated with the point (usually points are mapped in the field and not from satellite imagery).
In checking on the geometry, one must verify that the correspondence between the elements (on the image and on the map being constructed) is always 1:1. So, for example, two neighboring houses should not be grouped together but shown as two adjacent but distinct buildings (Fig. 6).
Control over the semantics (tag) of the input data is critical. At the beginning of the project, the degree of detail to be achieved must also be clearly established: based on this the required tags must be defined. This list of tags is the basis for subsequent validation. There are very detailed tagging guides (see for example WIKI OSM), with specifications that often vary by country (Fig. 7).
This means controlling the tag associated with mapped entities, which must be consistent with OSM guidelines. For example, a building mapped on a satellite image must be tagged as "building=yes" and not otherwise; field mapping is required to include other specifications.
In a mapping to satellite imagery at the time of validation one must check for missing objects and the background image must obviously be the same as that used by the mappers. If the image is different there may be an offset between what is on the image and what is mapped.
Verify base map image.
Check for any missing objects.
Consistency of mapped objects.
The result of the validation can be yes, no or validation suspended.
On satellite imagery, georeferencing is linked to the image itself: you map to the image and then link the mapped object to the image's reference system, regardless of the inherent accuracy of the image. If the mapping is in the field (e.g., in an urban environment), the coordinates that are read on the cell phone and linked to the mapped object may also have considerable errors, but this aspect is not usually considered in validation.
In the presence of an error or inconsistency, the validator has two options: he can report the error and request that the mapping be repeated/integrated, or he can intervene directly and correct it himself.
Van den Beemt, A., van de Watering, G., & Bots, M. (2022). Conceptualising variety in challenge-based learning in higher education: the CBL-compass. European Journal of Engineering Education, 1-18. https://doi.org/10.1080/03043797.2022.2078181
Universidad Politécnica de Madrid. Servicio de Innovación Educativa. (2020). Guía de aprendizaje basado en retos. https://innovacioneducativa.upm.es/sites/default/files/guias/GUIA-ABR.pdf
Universidad Politécnica de Madrid. Servicio de Innovación Educativa. (2020). Guía de aprendizaje servicio (APS). https://innovacioneducativa.upm.es/sites/default/files/guias/Guia-APS-UPM.pdf
Universidad Politécnica de Madrid. Servicio de Innovación Educativa. (2020). Guía de aprendizaje orientado a proyectos. https://innovacioneducativa.upm.es/sites/default/files/guias/AP_PROYECTOS.pdf
School teams will work to pre-define three possible challenges and assess their viability. These challenges (or a fine-tuned conceptualisation of them) will be presented to students afterwards, so they can take part in the decision-making process to select the school challenge through a participatory process. The options are thus previously defined by the teachers, so a prefeasibility study of the opportunities and resources is taken into account. The selected challenge will be further developed in a later stage.
Brainstorming: finding four big challenges
Teachers will participate in a brainstorming dynamic to come up with challenges. They will be asked to think of up to four big challenges and hypothetical contributions to them. Possible challenges will be named as “Challenge 1”, "Challenge 2”, etc.
Testing our first ideas: Selection of two possible challenges
The selection will be based on a checklist for the design of challenge-based learning courses. This framework is inspired by the one by Van den Beemt et al. (2022) for analysing the variety of challenge-based learning characteristics within and between components in an academic curriculum. Questions have been defined based on the experience of the team in project-based learning and service-learning to achieve an adequate selection of pupil-led projects schools.
Teachers will score the four challenges (Challenge 1, Challenge 2, etc.) in Table 2 to obtain the two selected ones—i.e., the two that will be discussed by students so that they choose one—
Pre-design of one challenge
Teachers will define the basic elements for the Top-one challenge (the challenge that scored higher in Table 2), following the scheme:
The challenge (it can be helpful to formulate it as a question)
Target groups (beneficiaries)
Other actors
Final product(s)
Subjects involved
Curriculum content covered (if any; the project can be extracurricular. However, integrative the project as a curricular interdisciplinary project is recommended)
Competences covered
Pupils grouping and organization
Tasks to be done
Assessment plan
Necessary resources (materials, spaces, ICTs)
Diffusion and connections