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About the Authors
Tatiana I. Enbaeva
Kurgan Region, Russia
Polina L. Pavlova
Moscow Region, Russia
Olga V. Kutuzova
Sverdlovsk Region, Russia
Aisen A. Vasiliev
Republic of Sakha Yakutia, Russia
Daria A. Ignatenko
33, 10th line of Vasil’evsky island, St. Petersburg, 199178, Russia
Evgeny A. Panidi
33, 10th line of Vasil’evsky island, St. Petersburg, 199178, Russia
E-mail: panidi@ya.ru, e.panidi@spbu.ru
Abstract
The development of methods and techniques for project-based teaching has become an urgent task for the development of education in recent decades, both in general and in narrow domains, in particular, in such areas as geography, cartography, geoinformatics, remote sensing, and unmanned technologies. The paper discovers and discusses some results of the educational and experimental work elaborated by the authors in the framework of organizing and conducting project-based research with secondary school students (grades 8, 9 and 10) during the “Big Challenges” Scientific and Technological project-based educational program (Ecology and Climate Change Studies section) at the Sirius Educational Center in July 2024. The project title was “Development of a samples catalog for satellite imagery interpretation for environmental studies”. Freely distributed software and libraries (QGIS, SAGA GIS, Orfeo ToolBox, GDAL, etc.), publicly available online platforms (GitHub and Zenodo), publicly available satellite imagery data (Meteor, Landsat-8–9, Sentinel-2) were used. A catalog prototype for the satellite imagery interpretation has been created and published online in the form of a website. The catalog incorporated the samples for visual interpretation of a number of objects and situations significant in the meaning of environmental studies and the samples of datasets for automated detection of these objects and situations in satellite images. The catalog contains samples for visual interpretation (fragments of images with textual explanations), samples for automated interpretation (spectral signatures), and samples for automated interpretation by machine learning methods (tiles with markup of the objects of interest).
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References
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For citation: Enbaeva T.I., Pavlova P.L., Kutuzova O.V., Vasiliev A.A., Ignatenko D.A., Panidi E.A. Basics of remote sensing and geoinformatics in a context of project-based learning of secondary school students. InterCarto. InterGIS. Moscow: MSU, Faculty of Geography, 2025. V. 31. Part 3. P. 446–459. DOI: 10.35595/2414-9179-2025-3-31-446-459 (in Russian)









