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- Title
Production of a Dynamic Cropland Mask by Processing Remote Sensing Image Series at High Temporal and Spatial Resolutions.
- Authors
Valero, Silvia; Morin, David; Inglada, Jordi; Sepulcre, Guadalupe; Arias, Marcela; Hagolle, Olivier; Dedieu, Gérard; Bontemps, Sophie; Defourny, Pierre; Koetz, Benjamin
- Abstract
The exploitation of new high revisit frequency satellite observations is an important opportunity for agricultural applications. The Sentinel-2 for Agriculture project S2Agri (http://www.esa-sen2agri.org/SitePages/Home.aspx) is designed to develop, demonstrate and facilitate the Sentinel-2 time series contribution to the satellite EO component of agriculture monitoring for many agricultural systems across the globe. In the framework of this project, this article studies the construction of a dynamic cropland mask. This mask consists of a binary "annual-cropland/no-annual-cropland" map produced several times during the season to serve as a mask for monitoring crop growing conditions over the growing season. The construction of the mask relies on two classical pattern recognition techniques: feature extraction and classification. One pixel- and two object-based strategies are proposed and compared. A set of 12 test sites are used to benchmark the methods and algorithms with regard to the diversity of the agro-ecological context, landscape patterns, agricultural practices and actual satellite observation conditions. The classification results yield promising accuracies of around 90% at the end of the agricultural season. Efforts will be made to transition this research into operational products once Sentinel-2 data become available.
- Subjects
REMOTE-sensing images; REMOTE sensing; TIME series analysis; RANDOM forest algorithms; DECISION trees; PATTERN recognition systems
- Publication
Remote Sensing, 2016, Vol 8, Issue 1, p55
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs8010055