Crop growth monitoring through Sentinel and Landsat data based NDVI time-series

Автор: Boori Mukesh Singh, Choudhary Komal, Kupriyanov Alexander Victorovich

Журнал: Компьютерная оптика @computer-optics

Рубрика: Обработка изображений, распознавание образов

Статья в выпуске: 3 т.44, 2020 года.

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Crop growth monitoring is an important phenomenon for agriculture classification, yield estimation, agriculture field management, improve productivity, irrigation, fertilizer management, sustainable agricultural development, food security and to understand how environment and climate change effect on crops especially in Russia as it has a large and diverse agricultural production. In this study, we assimilated monthly crop phenology from January to December 2018 by using the NDVI time series derived from moderate to high Spatio-temporal resolution Sentinel and Landsat data in cropland field at Samara airport area, Russia. The results support the potential of Sentinel and Landsat data derived NDVI time series for accurate crop phenological monitoring with all crop growth stages such as active tillering, jointing, maturity and harvesting according to crop calendar with reasonable thematic accuracy. This satellite data generated NDVI based work has great potential to provide valuable support for assessing crop growth status and the above-mentioned objectives with sustainable agriculture development.

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Crop phenology, ndvi time-series, sentinel-2 & landsat, remote sensing

Короткий адрес: https://sciup.org/140250005

IDR: 140250005   |   DOI: 10.18287/2412-6179-CO-635

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