ALL-RUSSIA OPEN ANNUAL CONFERENCES ON
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE
Principal physics, methods and techniques for monitoring the environment, potentially dangerous phenomena and objects
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Proceedings of the 16th Conference (November 12-16, 2018, Moscow, Russia)
Using Crowdsourcing Datasets and Landsat Satellite Data for Cropland Mapping in Different Agrosystems of Global JECAM Network
Dmitry E. Plotnikov1, Diego de Abelleyra2, Santiago R. Veron2, Miao Zhang3, Vladimir A. Tolpin1, Sergey A. Bartalev1, Mykola Lavreniuk4, Francois Waldner5, Aly Ziad6
- Space Research Institute, Russian Academy of Sciences, Moscow, Russia
dmitplot@d902.iki.rssi.ru
- Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria (INTA), Buenos Aires, Argentina
- Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China
- Department of Space Information Technologies, Space Research Institute NAS and SSA (SRI), Kyiv, Ukraine
- Earth and Life Institute - Environment, Croix du Sud, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
- Agriculture and Agri-Food Canada, Ottawa, Canada
DOI 10.21046/rorse2018.177
The study explores the reference information obtained by photo-interpretation of satellite images by an international team of volunteers for accurate cropland mapping over large areas based on Landsat remote sensing data and supervised classification. JECAM teams from Argentina, Belgium, Canada, China, Russia and Ukraine had arranged the crowdsourcing campaign and in situ data collection, used to assess the accuracy of the cropland maps derived. Vega-Geoglam system was set to collect distributed reference crowdsourcing dataset of controlled accuracy over each JECAM site, which was used to map cropland for the target growing season in six contrasted agroregions of the globe.
Keywords: cropland mapping, JECAM, Landsat, spectro-temporal features, crowdsourcing, VGI
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Section 3. Evaluation of accuracy and verification of the algorithms for remote sensing data processing
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