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26 August 2020 A Sentinel based agriculture monitoring scheme for the control of the CAP and food security
Vasileios Sitokonstantinou, Antonios Koutroumpas, Thanassis Drivas, Alkiviadis Koukos, Vassilia Karathanassi, Haris Kontoes, Ioannis Papoutsis
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Proceedings Volume 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020); 1152407 (2020) https://doi.org/10.1117/12.2571721
Event: Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), 2020, Paphos, Cyprus
Abstract
Effective and efficient control of the agrarian obligations imposed by the Common Agricultural Policy (CAP) and the high-level decision making for national and global food security, requires systematic and timely monitoring of the agricultural land. In this study we focus on rice paddy monitoring in South Korea to ultimately deliver food security related information. Food security monitoring demands knowledge at large scales to allow for decision making at the highest level. In this work, we monitor the growth of rice using the TIMESAT solution on a time-series of Normalized Difference Vegetation Index (NDVI), extracting useful metrics with reference to the phenological phases of the crop, but also biomass and yield indicators. TIMESAT requires user provided parameters to define the start and the end of season to then compute the relevant metrics. In order to automate this procedure, the vegetation indices Normalized Difference Water Index (NDWI) and Plant Senescence Reflectance Index (PSRI) are used to develop a data based parameter tuning for TIMESAT.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vasileios Sitokonstantinou, Antonios Koutroumpas, Thanassis Drivas, Alkiviadis Koukos, Vassilia Karathanassi, Haris Kontoes, and Ioannis Papoutsis "A Sentinel based agriculture monitoring scheme for the control of the CAP and food security", Proc. SPIE 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), 1152407 (26 August 2020); https://doi.org/10.1117/12.2571721
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Cited by 2 scholarly publications.
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KEYWORDS
Agriculture

Vegetation

Clouds

Satellites

Data modeling

Earth observing sensors

Climatology

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