Remote sensing products are widely used for scientific and societal purposes like weather prediction, ecological monitoring, or disaster management. However, they are not often used for teaching purpose and if so they are in most cases narrowed down to simple image interpretation. In fact, the technical equipment in schools is often limited. Therefore, it is challenging and in most cases impossible to work with large satellite images like Sentinel-2. Still there are several implications in the field of Earth observation making it a useful teaching method: it connects physical and mathematical background with environmental application areas; it fascinates by the overview effect; it fosters digital competencies. The presentation shows how smartphone-based augmented reality apps makes it possible to bring the fascination of Earth observation to school lessons without the need of extensive computer equipment. Simultaneously, it introduces the field of remote sensing from the International Space Station (ISS), the biggest scientific experiment in the history of humankind. The NASA “High Definition Earth Viewing” (HDEV) experiment includes four commercial off-the-shelf HD cameras installed aboard the Columbus External Payload Facility at the ISS observing the Earth 24/7. A unique archive of HDEV comprises of more than 40 TB of footage over a timespan of four years showing interesting places and phenomena all over the world. With the technique of augmented reality objects of the real world are “augmented” by computer-generated perceptual information. This presentation shows how classical working sheets can be enhanced using augmented reality. The teaching unit “Earth at Night – Light Pollution in Central Europe” includes a Sentinel-2 false-colour image as well as observation footage from the ISS. The data is used to compare the metropolitan regions of the Ruhr Area as well as the so-called Flemish Diamond. The satellite image is augmented by the ISS video taken by night. An extension mediates the structure of the energy industry in Germany and Belgium dealing with brown coal and nuclear power plants and their environmental risks. Furthermore, augmented reality apps on desertification and tidal effects by gravitation are presented. Finally, it is shown how other Earth observation sensors aboard the ISS are mined and their data included in learning materials. Here, the Hyperspectral Imager for the Coastal Ocean (HICO) sensor provides the possibility to detect algae bloom in the Great Lakes. Hence, pupils get to know the physically highly elaborated field of hyperspectral remote sensing and upcoming sensor missions like EnMAP.

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Earth observation is one of the key technologies of the 21st century. By using the great educational potential of satellite images for teaching environmental topics, the competences of young talents and pupils can be developed as well as careers in natural sciences and technology sector promoted. Despite huge potentials and the importance of remote sensing in science, industry and the general public, the topic has still not been integrated into many school curricula in Germany. Within the framework of the project “Living Earth – Utilization of satellite data for Earth observation of habitats by adolescents” and based on the existing e-learning platform geospektiv (www.geospektiv.de), we developed an interactive learning module on Earth observation to discover, explore and explain climate and environmental protection.
The learning module is established based on the former project Space4Geography. The platform provides a responsive design for a wide range of user devices and offers a browser interoperability. Geospektiv is already used by hundreds of school classes and is regularly evaluated. Furthermore, the platform is linked with the easy-to-use web-based remote sensing application BLIF. By using the integrated application, pupils can edit, analyze and classify satellite images independently. The application offers a wide range of common processing functions like true- and false-color composites, indices such as the NDVI or RVI, unsupervised and supervised classification as well as change detection functions.
The web-based learning module is specifically designed for 9th and 10th grade pupils (with an age of about 14 - 15) and their teachers. The module offers a target group and theme-oriented introduction to Earth observation and image processing. Different age groups and educational levels can use the learning module due to the adaptability of the platform. This important feature offers personalization of the learning modules content depending on the abilities or interests of the user. By using the bird’s eye perspective, pupils get new impressions and knowledge about the distribution, characteristics and potential threats of selected ecosystems. Due to the variability of usable satellite data (e.g. Landsat, Sentinel, RapidEye), pupils can choose an individual case study, depending on their interest. By analyzing and processing satellite images in an interactive format from their own region, pupils have a reference to their everyday life. The assessment and classification of ecosystems or habitat types with varying spatial scales facilitate the pupils to evaluate how their own region changes over the years. During the class, teachers have the option to manage, monitor and evaluate the process of learning. Later, results can be illustrated and compared if desired.
The developed problem-oriented learning module and practical application offer a considerable contribution to the competence development of pupils and support the promotion of young talents in the space sector in general.

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As a versatile and multidisciplinary field of scientific research with diverse applications for everyday life, satellite technologies present a particularly suitable context for STEM education. Many studies show significantly the high potential of context based learning in order to foster students' motivation and to make learning more meaningful. Moreover, satellite remote sensing offers many opportunities for a modern interdisciplinary science education. E.g., it connects the school subjects geography, physics, data sciences, mathematics and even art and foreign languages.
To date, there are a variety of pedagogical approaches based on remote sensing technologies, most of which focus on geography. They are based on free satellite data that can easily be accessed via the internet. These approaches therefore mainly deal with data evaluation and applications rather than the technology of the data acquisition itself.
In this presentation a short overview is provided demonstrating how self-acquired infrared remote sensing data can be applied in individual remote sensing projects conducted by high school students in their own environments. The Projects are based on a simple and cost-effective technology that offers the students the opportunity not only to analyze data available in online data bases but also to create their own remote sensing data. Thus it can easily be replicated, and schools can implement these projects related to their home region.
As a pilot scheme, a joint international project with students from Beer-Sheva, Israel, and Munich, Germany was conducted. The students were tasked with acquiring and analyzing remote sensing measurements in the field. The educational program was evaluated through a questionnaire and by observation of the students. Our analysis of 32 student projects showed that the educational program was suitable for fostering a variety of important science competencies. From the students' point of view, the program was considered to be interesting and meaningful.

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Today, space technologies have become crucial to many areas of daily life. Satellite remote sensing data applications like precise mapping, surface classifications, disaster monitoring and report have become as natural in our awareness as the daily weather forecast. We use satellite navigation for traffic, in smartphones and many other applications such as precision farming, fleet management, search and rescue services and many more. Satellite communication is the basis for a worldwide fast data access and is already used in many areas of communication.
Despite the obvious importance for everyday life, satellite technologies play only a minor role in school education. Yet, as an interdisciplinary, versatile context satellite technologies offer lots of connections to school subjects like geography, physics, mathematics and many more.
There is plain evidence from many studies on education that context based learning can not only foster students' motivation but also their cognitive skills and avoids inert knowledge. Other international studies on the interests of young people, such as the ROSE study (Relevance Of Science Education), show that science as a school subject in many developed countries is neither considered interesting nor relevant to daily life. The results also highlight some big differences between boys and girls, with one exception: space-related issues attract both sexes equally.
In the project "SatTec - satellite technologies for school classes" of Ludwig Maximilan University many different teaching material related to satellite remote sensing, navigation and communication was developed. The pedagogical approach of all this material is a context based science education: the attractive topics of different space technologies are used to learn the underlying physics "by the way". In special teacher training courses throughout Germany, the material and the underlying concept of context-based science education were presented and improved. In addition to lesson suggestions and tips, experimental hardware for remote sensing and satellite navigation in the classroom was also developed and made available to schools. The project was accompanied by a student competition for remote sensing with stratospheric balloons.
The poster presentation gives an overview of the main activities and results of the project. In addition, some hands-on experiments will be demonstrated.

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The SAMI (SAtellite MIssion Editor & Player) is a software application for visualization of high-resolution 3D satellite mission scenarios distributed by the ESA-ESTEC EOP System Support Division to users part of the ESA Earth Observation Earth Explorer and Copernicus satellites community.

SAMI is a freely available application that displays stunning high-resolution 3D and 2D scenarios of ESA Earth Observation satellites. SAMI is a response to the need to visualize ESA EO satellite mission scenarios in high resolution including realistic satellite elements, for example, orbit tracks, ground-tracks and footprints of the instruments on-board. The software also highlights entering and exiting the area of visibility between the satellite and the ground stations. It is possible as well to trigger animations with the deployment sequence of solar arrays and antennas and schedule thruster firing events.

The time window in the application can be configured as real-time or as simulated time (scene set in the past or in the future). In addition an endless loop simulation mode is available, with the objective to replay a given sequence.

With the editing capabilities of SAMI, the user can drive the various camera views (camera attached to the Earth or to the satellite), change the global Earth map images used as layer texture and enable or disable objects in the scene, running standalone animations to display scenes involving the ESA EO satellites e.g. for public relation purposes.

The SAMI embedded capability to export image snapshots or HD video can be exploited to share media content and enhance the demonstration of mission concepts.

Another more specific use case for this application would be the playback of a scenario within a given time window to observe a particular satellite geometry, e.g. to inspect solar illumination on satellite parts, which is possible due to the realistic Sun illumination and shadow casting.

The missions currently supported are Sentinel 1A/1B, Sentinel 2A/2B, Sentinel 3A/3B, Sentinel5P, SWARM, Cryosat, SMOS, EarthCARE and Aeolus. The capability to seamlessly display several satellites simultaneously is one of the stronger features of SAMI.

The coherence and accuracy of the orbital and geometrical calculations within the SAMI application is ensured by the use of embedded Earth Observation CFI Software libraries (EOCFI SW). The libraries are used to obtain the satellite position, orbit ground-track, attitude and swath footprint.

The application runs on desktop platforms (Mac OS X, Windows) and mobile platforms (iOS based, e.g. iPad).

REFERENCES

[REF 1 ] SAMI website: http://eop-cfi.esa.int/index.php/applications/sami

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Abstract:
Planets in a room (http://www.planetsinaroom.net/) is a DIY kit to build a small, lowcost spherical and planetarium projector that teachers, museum, planetary, Earth observation scientists and other individuals can easily build and use on their own, to show and teach the Earth and other planets. The kit was developed by the italian non-profit association Speak Science (www.speakscience.it) with the collaboration of INAF-IAPS of Rome and the Roma Tre University (Dipartimento di Matematica e Fisica). Starting from September 2018, Planets in a room has been presented and distributed to schools and other education institutions from all over Europe. The distribution phase involved the outreach and research planetology community, but can also include Earth observation scientists, with the aim of bringing Earth science to a larger audience.
Acknowledgements:
We acknowledge Europlanet for having funded "Planets in a Room" with the Europlanet Outreach Funding Scheme, and the vast community of amateur and professionals that is actively working on innovative educational systems for astronomy such as planetarium and virtual reality projects (both hardware and software). Planets in a room is based on the work of this vast community of people and their experiences and results. We also acknowledge scientists, teachers and students who have used (and will use) Planets in a Room.
References:
[1] Giacomini L., Aloisi F., De Angelis I., “Planets in a room”, EPSC Abstracts Vol. 11, EPSC2017-280, 2017
[2] Giacomini L., Aloisi F., De Angelis I., Capretti S. “Planets in a room: a DIY, low cost, educational kit”, EPSC Abstracts Vol. 12, EPSC2018-254, 2018

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Digital transformation influences almost all aspects of our daily life, and constitutes both an opportunity and a pressure. It contributes to the new big data paradigm in data collection and analysis as well as to the paradigm shift in learning and knowledge transfer. Technological changes lead to deficiencies in terms of skills and knowledge which requires innovative strategies for the development of new qualifications. The New Skills Agenda, adopted in 2016 by the European Commission, supports efforts made to reduce the mismatch between the skills people are taught and those needed by the public and private sectors, via the Blueprint for Sectoral Cooperation on Skills. The measure specifically targets data-driven disciplines, e.g. Earth Observation (EO) and Geoinformation (GI) sectors. These sectors are of special concern for the European Union as they are considered strategic and transversal in terms of policy and decision-making at the regional, national, and global scales.
The EO/GI industry acquires, integrates, manages, process, analyses, visualises, distributes, and uses spatio-temporal information and knowledge. The industry includes basic and applied research, technology development, education, and applications to address the planning, decision-making, and operational info needs of people and organizations of all types. Spatial data is being acquired more frequently, with better accuracy, and higher resolution. For example, the average daily publication volume of freely available Copernicus Sentinel products was 10.04 TiB at the end of 2017 (Sentinel Data Access 2017 Annual Report). To digest and in particular exploit such amounts of high quality EO data it is required to acquire technological skills towards big data handling, interface programming, machine learning, computer vision, and cloud computing. However, with the current technological changes, which may fundamentally disrupt well established workflows, transversal skills are of increasing importance, such as creative problem solving, design thinking or communication skills. This applies to both the public and the private sector. Moreover, leadership and an entrepreneurial mind-set are also particularly valued, especially for future leaders and changemakers in local and regional administrations or those to develop and commercialize new products and services for an increasingly diverse user community.
The Erasmus+ Sector Skills Alliance flagship project EO4GEO (www.eo4geo.eu) (Towards an innovative strategy for skills development and capacity building in the space geo-information sector supporting Copernicus user uptake) aims to define a long-term and sustainable strategy to fill the gap between supply of and demand for EO/GI education and training. This sectoral cooperation on skills development with 26 partners from 13 countries, from academia, private, and public sector, active in the EO/GI education/training and many included in the Copernicus Academy Network takes into account the current and upcoming changes in this sector. The skills strategy will capture the outlook for EO/GI sectors over the next years, the associated skills issues and priorities, and the solutions will be delivered in line with the EO4GEO project. The skills strategy shall be implemented by: (1) defining the technological and non-technological skills shortages; (2) analysing trends, challenges and opportunities in the field of EO/GI; (3) creating and maintaining an ontology-based Body of Knowledge for the EO/GI sector, i.e. collection of knowledge, skills and competences needed to become an expert in the field of EO/GI; (4) developing and integrating a dynamic collaborative platform with associated existing and new tools, e.g. a tool to design/define job/occupational profiles and their descriptions, a tool for a self-skills-assessment, etc.; (5) developing of a series of curricula and a rich portfolio of training modules directly usable in the context of Copernicus and other relevant programmes.
As part of the EO4GEO preparatory strategy an initial study was carried out on ‘Supply of/Demand for space/geospatial education and training’, mainly based on a comprehensive questionnaire with some 350 responses and semi-structured interviews with sector representatives. The study aimed at (1) collecting EO/GI sector-specific education and training offers, (2) collecting EO/GI sector-specific skills for a growing market and related methodological concerns, (3) identifying potential high-priority profiles that can guide curriculum development in a later phase of the project, and (4) selecting emerging topics to be included in a combined EO/GI Body of Knowledge. The identification of priority profiles includes the opportunities of vocational training (VET) profiles, which hardly exist for the sector at hand. In terms of analysis of trends, challenges and opportunities an exhaustive study was conducted. For example, following recent trends in the geospatial sector were identified: on-demand, web-based mapping and mapping as a service (MaaS), cloud data storage and processing, oblique imagery and city modelling, unmanned aircraft systems, Smart Cities and Internet of Things (IoT), Building Information Modeling (BIM), Virtual Reality (VR), Augmented Reality (AR). These geospatial trends need to be considered for updating academic programmes, government regulators, while professional organizations are attempting to develop appropriate methods of training in necessary skill sets, creating helpful credentials, i.e., licenses, degrees, and certifications. When it comes to the dynamic collaborative platform with associated tools, it will be based on the analysis of existing components and platforms as well as the development of new components and tools, and will make use, among others, of the platforms and components that have already been developed in the context of the Copernicus programme (e.g. PROBA-V Mission Exploitation Platform), generic collaborative education and training platforms such as Moodle, platforms to share source code such as GitHub and Redmine, etc. The aim is not to develop ‘a system’ from scratch but rather identify and assess existing initiatives trying to improve, integrate, and extend them. The approach will be component-based, the developments Agile and the architecture should rely on web services accessible through the Internet. Moreover, the EO4GEO project will develop the training modules. The modules will be focused on three sub-sectors – integrated applications, smart cities, and climate change. The training materials will be designed to inspire and motivate the next generation of scientists and technologists, as well as to catalyse the development of an entrepreneurial culture among researchers in the EO/GI application sector. Special attention will be paid to existing training materials that can be re-used, improved, and turned into material for the case-based learning approach mentioned above. In addition, the training materials will be designed to strengthen ‘green skills’. Finally, a long-term Action Plan will be developed and endorsed to roll-out and sustain the proposed solutions on skills development for the EO/GI sector. The strategy will reference further areas for delivery addressed by organizations working in the partnership and by the stakeholders through the skills agreement. Thus, during the next years of intensive collaboration and coordination activities within the EO4GEO it should be possible to answer some key questions related to the skills development in the EO/GI sector: Where are we now? Where do we want to be? and How can we get there?

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More and more national and international public and private sector protagonists are making open geodata available for unrestricted use. This creates a huge amount of data available for scientific use. The project “Open Data for Teaching and Research in Spatial Studies” (short: OpenGeoEdu) (German: "Offene Daten für Lehre und Forschung in raumbezogenen Studiengängen") aims to demonstrate this potential by means of best-practice examples and, building on this, to provide eLearning offers for the integration into courses of spatial studies. In this way, young researchers should become familiar with the use of open data and platforms as a matter of course. Moreover, OpenGeoEdu is not only for students or academics, but also for all those who want to refresh or deepen their knowledge on the subject of open geodata, either extra-occupationally or privately.
OpenGeoEdu is a joint project coordinated by the Chair of Geodesy and Geoinformatics at the University of Rostock. The Federal Agency of Cartography and Geodesy (BKG), the German Biomass Research Centre and the Leibniz Institute of Ecological Urban and Regional Development are further project partners. Each of the partners creates freely available online learning units on a joint platform, which illustrate the use of open geodata from the respective area of expertise as case studies. They follow the didactic principle of discovery learning. Tasks and resources on geodata and corresponding processing methods are given and should be independently assembled by the learners into their own solutions. The learning units can therefore be used by both beginners and experienced users. The required depth of analysis can be determined by users or defined by lecturers.
The concept of OpenGeoEdu is a massive open online course (MOOC), which is accessible for everybody. The MOOC deals with a variety of subjects related to open geospatial data covering general aspects and highlighting details in terms and definitions. Besides an introduction to geoinformation systems, tutorials will guide the users through cartography topics like creating maps, coordinates systems, data file formats or OGC web services. The open online course comprises several parts, which can be combined freely in different ways. Each part consists of a lecture with a follow-up knowledge test and a practical exercise. The exercises are designed as case studies, in which students or users will go through a geoprocessing chain. This includes where to find open data, to get to know selected analysis functions and to produce results, which the participants will then classify and interpret in the context of the question.
The BKG creates learning units about remote sensing and for the exploitation of Copernicus data. Together with Sentinel satellite data, the use of data products of the Copernicus land monitoring service (e.g. High Resolution Layers) and of BKG Open Data (e.g. CORINE Land Cover 10 ha) is also employed. The first case study deals with the assessment of windthrow detection in forests using Copernicus data. Further possible analyses are urban tree assessment, forest area change analysis, flood mapping or monitoring of agricultural areas.

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The RUS Service aims to promote the uptake of Copernicus data, and supports the scaling up of R&D activities with Copernicus data. RUS Service is configured in a scalable cloud environment that offers the possibility to remotely store and process EO data. The RUS Service offers support from a helpdesk and a team of EO and IT experts who can address any request, coming from beginners or skilled practitioners. Cloud ICT resources are procured with Free and Open-Source Software and are tailored to the user needs. The RUS service proposes also on-site training sessions, webinars, and online materials. The RUS Service is offered at no cost and is available for a large community of users and types of institutions.
The objective of this talk is to present the different aspects of the service, and the latest evolutions of the offer. Particularly, we plan to discuss the recent availability of advanced visualisation tools, the continuous update of the image processing tools, and more importantly the new possibility to set up cloud computing platforms that can be shared across multiple users, in the context of the newly developed European DIAS.
The RUS Service is funded by the EC, managed by ESA, and operated by Communications & Systèmes – Systèmes d’Informations (CS SI) and its partners: Serco SPA, Noveltis, Along-Track, and CS Romania.

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Like most fields of Earth Observation, the development of methods for remote sensing of snow cover properties requires adequate methods for quantifying the observed target in order to establish the “ground truth”, and to model its effects on quantities observed by remote sensing (e.g. microwave emission and backscatter, optical reflectance). In the case of snow cover this has been particularly challenging, as conventional methods for quantifying snow physical properties have relied on semi-quantitative observations and classification. The most recent version of the International Classification for Snow (Fierz et al., 2009) differs from the first one (Anonymous, 1954) by an increase in detail, but the standard methods of observations have not changed.
However, with emerging new methods snow science is moving towards a more quantitative, instrument-based science. The past twenty years have seen a massive change in investigating snow properties towards increasingly technically complex methods. Recognizing in a broad community that the three-dimensional structure of snow must be considered for explaining the physical properties, a number of new technologies to measure density, specific surface area, anisotropy and stratigraphy have been developed. These have directed the development of new models for understanding the signatures observed from snow covered terrain by means of remote sensing.
The Snow Science Winter Schools started in 2015 in Sodankylä, Finland, with the goal of enabling students to learn and use these new techniques, enabling a new generation of researchers to apply the latest methods for snow physical quantification in their research. The Winter School is a one-week course on field measurements, modeling and remote sensing of snow, aimed at international graduate and post-doctoral students. Since 2015, the school has been organized in Davos, Switzerland (2016), Sodankylä (2017), Col du Lautaret, France (2018). The school of 2019 will be organized in February 2019 in Hailuoto, Finland, focusing on snow on sea ice.
The school has invited international experts as lecturers to teach and demonstrate use of physical models for snow cover evolution, instruct on modern techniques of quantitative snow measurements, and to present on advanced methods for snow cover remote sensing. Sponsors of past schools include the WSL Institute for Snow and Avalanche Research SLF, the Finnish Meteorological Institute, the International Arctic Science Committee IASC, the International Association for Cryospheric Sciences IACS, the Scientific Committee on Antarctic Research SCAR, the European Geosciences Union EGU, and the European Space Agency ESA.
Interestingly, the structural and stratigraphic complexity of a snowpack is still best explored for beginners in the traditional way. The newer methods, often of a more abstract nature, are often hard to understand in their use and power. However, the training in measuring snow properties in a physically meaningful way is highly relevant to remote sensing applications.

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Land cover (LC) maps are models of the Earth’s surface generated through classification of the remotely-sensed satellite imagery. The wide scientific community has recognized from the beginning the valuable information LC maps provide. Hence, these products are used in many fields, such as biodiversity monitoring (i.e. estimating habitat extent and condition), natural resource management (water quality assessment), tracking climate change (i.e. climate modeling), and detecting change in land use (i.e. measuring growth of urban area). Moreover, LC maps are important instruments for the accomplishment of some of the Sustainable Development Goals (SDGs) of the United Nations (UN).
Evidently, the demand for these kinds of maps is large. This has an influence on the recent progress towards high-resolution and global LC maps, besides the technological advances. Indeed, several Earth observation programmes, like Copernicus, have been established recently to provide users with free, high-resolution and frequently updated imagery. “High-resolution” implies more detailed information, while “global” ensures its worldwide availability (including the developing nations).
Practical use of a global LC map is determined by its thematic accuracy (hereafter called accuracy), which is a prerequisite to confirm its reliability before employing it. Accuracy analysis results may possibly serve also for error elimination. However, accuracy assessment of global maps is not trivial. Lack of accurate and up-to-date reference data on a global level, and not well-documented and thus difficult-to-use tools for accuracy assessment are just some of the limitations.

The barriers in accuracy assessment must be removed in order to exploit full capacity of LC maps. One of the ways to cope with accuracy assessment limitations is to spread the current knowledge of this topic and related issues. In this way, it is expected to engage more people into accuracy assessment, eventually leading to solutions and innovations regarding this matter.
To this end, GEOlab of Politecnico di Milano led the “Capacity Building for High-Resolution Land Cover Intercomparison and Validation” project, funded by the International Society for Photogrammetry and Remote Sensing (ISPRS). The project was carried out in collaboration with National Geomatics Center of China. The outcome of this international collaboration is an educational material with a wide range of content: an overview of free and open source software (FOSS) and Web-based capabilities in terms of accuracy assessment, instructions for desktop accuracy assessment procedures, and instructions and an application for facilitating and encouraging on-site LC data collection. The educational material is available under CC BY 3.0 license, and the tools under GNU General Public License or corresponding ones. The openness of the educational material ensures availability to everyone, regardless of their financial situation, while the openness of the tools aims at a development of solutions created using them.

Regarding currently available FOSS software, we explored accuracy assessment related functionalities of QGIS, GRASS GIS, Orfeo ToolBox, SAGA GIS and SNAP, and reported the results in the educational material. Each of the software have functionalities for classification of imagery, but not always for accuracy assessment (e.g. SNAP). Moreover, certain accuracy assessment tools (e.g. AccuracyAssessment QGIS plugin) do not contain guidelines or tutorials on how to use them, which certainly makes their exploitation difficult. Overall accuracy, user’s accuracy, producer’s accuracy, kappa, conditional kappa, quantity disagreement and allocation disagreement are the indexes implemented in the available software.
The number of accuracy indexes included in the available software is rather small in comparison to the ones available in the literature (more than 20). Provided that larger number of different indexes might reveal more about accuracy, we created new PyQGIS scripts through which users can compute many more indexes, besides the ones already available in FOSS software (among them: classification success index, ground truth index, Hellden’s and Short’s mean accuracies). The PyQGIS scripts, “pts_lcval” and “raster_lcval”, can be run within QGIS. The difference between the two scripts is in the reference data type. “pts_lcval” input reference data are LC sample points, while in case of “raster_lcval” reference data is an LC raster map. Usage of both PyQGIS scripts is illustrated in the educational material with an example of accuracy assessment of GlobeLand30 (GL30). The educational material includes step-by-step instructions for data download, data processing, accuracy assessment procedure, and analysis of the results.
To deal with the deficit of reference data, a Web-based and mobile (Android and iOS) application for LC data acquisition, “Land Cover Collector”, was developed. The application is available online, as well as on Google Play and Apple Store. All the necessary steps, from registration, LC data acquisition, suggestions and warnings concerning privacy, to data visualization and download are demonstrated in the educational material.
From the practical point of view, online tools are appreciated in overcoming the possible desktop tools issues related to the limited performance of computers. Hence, the educational material also gives an insight into the online accuracy assessment tools, with the example of GL30 validation platform (GLCval). Among other functionalities, GLCval allows users to choose whether to import their own sample points, or to create sample points using some of the provided sampling schemes, and eventually to interpret them taking into consideration different base maps (Bing, OpenStreetMap imagery, Landsat imagery…).

Each of the mentioned procedures (desktop and online accuracy assessment, and LC data acquisition) is documented with screenshots and complemented by textual explanation. The educational material was tested, and well-rated, in workshops in three countries: Kenya, Uganda and the Netherlands. All material is available online at http://geomobile.como.polimi.it/website/ (Capacity Building for High-Resolution Land Cover Intercomparison and Validation).

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The INSPIRE Hackathon is a series of collaborative events for developers, researchers, designers and others interested in open data, volunteered geographic information and citizen observatories. The main driving force of the INSPIRE Hackathon are experts from existing EU projects using Earth observation data or combinations of Earth observation data with other types of open data such as economic,statistical data and more.
The main objective of the INSPIRE Hackathon is to share knowledge and experience between the participants and demonstrate to a wider audience the power of open data and information supported by modern technologies and common standards coming from INSPIRE, Copernicus, GEOSS and other initiatives.
Open data are, and will be, one of the driving elements of the digital society in the European Union. Many funding instruments are put in place to support open data. However, the sustainability of actions triggered by hundreds of European projects is not ensured and many results including tools, data and methods disappear. Too often new projects and initiatives start over from scratch, often with little use of the experience gained in past projects and initiatives. The INSPIRE hackathon model, consisting of both virtual and onsite activities, support a long term sustainability of project results, faciliating their transfer into practice and further research.
In order to make open data useful for society, education and capacity building is necessary at many levels.
An important component of the INSPIRE hackahton is education. As each of the INSPIRE hackathons focus on different aspects of open data technologies and tools, a series of webinars are organized during the virtual part of the hackathon. Typically, introduction to main concepts such as meta data, APIs, standards, etc depending on the theme of the individual hackathon are given by experts in the field. These webinars are at the same time educational and engaging the communities, promoting open data while bringing experts together around concrete problem solving. In addition to educate during the INSPIRE hackathon itself, the recorded educational material are being re-used and made available as open resources easy accessible via Plan4All webpages and social media.
In this presentation the INSPIRE hackathon concept will be explained. The educational component and the way the education is being used as an engagement tool will be demonstrated through examples from the INSPIRE hackathons organized so far. One of the criteria in the INSPIRE hackathon is use of Earth observations from Copernicus. We will show how results based on Earth observation data are being re-used and further advanced through knowledge sharing across projects using educational webinars as part of the strategy.
The integral use of education of various aspects of open data and their applications is key to effective and successful exploitation of open data resources.

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Imaging spectrometers (aka hyperspectral imagers) have been demonstrated to be a source of accurate and quantitative information about terrestrial and aquatic ecosystems required in various application fields. While the current availability of hyperspectral image data is still strongly limited both in temporal and spatial coverage, it can be expected that data availability will substantially increase in the future with the rising number of imaging spectrometers deployed on airborne platforms, the launch of national “target-oriented” space-borne imaging spectroscopy missions, such as the Italian PRISMA and the German EnMAP, upcoming commercial hyperspectral missions and possibly the deployment of global coverage imaging spectrometers into space by ESA and/or NASA in the mid to late 2020s. The latter will open up opportunities for frequent and timely observations and area-wide inventories and, thus, the development of operational services based on information from hyperspectral data.
In view of these developments, an increasing interest in hyperspectral data analysis in research and education is expected in the next few years. The overall need for Earth Observation (EO) education and training activities is currently also reflected by an increasing number of online learning platforms and Massive Open Online Courses (MOOCs) for various EO sensors and application fields. However, hyperspectral remote sensing is not yet well represented in the online learning system.
Therefore, the development of HYPERedu, an online learning platform for hyperspectral remote sensing has started as part of the EnMAP education initiative funded within the EnMAP preparatory science program under the DLR Space Administration with resources from the German Federal Ministry of Economic Affairs and Energy. In the past, the EnMAP preparatory science program already comprised the development of scientific methods and software as well as training of PhD students and community building activities. As part of the program, the EnMAP-Box, a free and open-source software toolbox for visualising and processing imaging spectroscopy data and spectral libraries, has been developed and is now available in the latest version EnMAP-Box 3 as QGIS Plug-in. More recently, the development of HYPERedu will provide presentations and tutorials on principles, methods and applications of imaging spectroscopy on Master level, addressing students as well as people in research, companies, and public agencies. In addition, the development of a MOOC with several modules and certificate is planned.
The poster introduces concept, current status and future perspectives of HYPERedu and provides a brief overview of the EnMAP preparatory science program that it is embedded in.

Area C - Board 355

Keywords: education, open-source, toolbox, Python, QGIS, imaging spectroscopy, HYPERedu, EnMAP

The EnMAP-Box 3 is a toolbox for visualising and processing imaging spectroscopy data and spectral libraries, and is particularly developed to handle data from the upcoming EnMAP (Environmental Mapping and Analysis Program) mission. The integration as a python-based plug-in into the free and open source geographic information system QGIS 3 makes the EnMAP-Box an ideal platform for sharing and distributing algorithms and methods among scientists and potential end-users. The two main goals are to provide (i) state-of-the-art applications for the processing of high dimensional spectral and temporal remote sensing data and (ii) a graphical user interface (GUI) that enhances the GIS oriented visualization capabilities in QGIS by applications for visualization and exploration of multi-band remote sensing data.

The EnMAP-Box GUI provides a multi-window viewer for the simultaneous exploration of spectral images and vector data, spectral libraries or models created with the EnMAP-Box API. The GUI is highly interoperable with that of QGIS and optimizes an interaction between GIS and imaging spectroscopy workflows. Interactive tools allow for data exploration and preparation, a spectral library tool collects, visualizes and labels spectral profiles from different sensors, and a raster image calculator offers the full flexibility of NumPy operations to users. For image processing the EnMAP-Box offers a rich set of functions for (i) machine learning classification, regression, clustering and transformation tasks, (ii) accuracy assessment, (iii) convolution and morphological filtering, (iv) data sampling and random subsampling. They are integrated to the QGIS Processing Framework and thus can be easily used with algorithms provided by other plugin developers.

As a joint initiative of the EnMAP Core Science Team, a set of applications for domain specific data analysis is currently under development. This includes an interactive radiative transfer model for forward/backward simulation of leaf and vegetation canopy reflectance for agricultural and forest applications (LMU Munich and Univ. Trier), the EnSoMAP application for mapping soil properties and EnGeoMAP for mineral mapping (both GFZ), mapping of coastal and inland water (AWI/HZG) or regression based spectral unmixing (HU Berlin). All approaches are implemented as user-friendly applications in the EnMAP-Box. Accompanying test data sets and interactive tutorials for these applications are provided as online resources via HYPERedu, an online learning platform for hyperspectral remote sensing that is currently under development as part of the EnMAP education initiative.

In our presentation we illustrate the novelty of the EnMAP-Box 3 for QGIS and demonstrate advantages and strengths of linking user friendly graphical interfaces with the functionality of python and related packages.

Area C - Board 356