Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/88057
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Title: Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
Authors: Boori, MS
Choudhary, K 
Kupriyanov, AV
Issue Date: 2020
Source: Computer optics, May-June 2020, v. 44, no. 3, p. 409-419
Abstract: 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 tittering, 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.
Keywords: Crop phenology
NDVI time-series
Sentinel-2 & Landsat
Remote sensing
Publisher: Samarskii Natsional'nyi Issledovatel'skii Universitet imeni Akademika S.P. Koroleva
Journal: Computer optics 
ISSN: 0134-2452
EISSN: 2412-6179
DOI: 10.18287/2412-6179-CO-635
Rights: Content is licensed under a Creative Commons Attribution 4.0 International License (Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/)
The following publication Boori MS, Choudhary K, Kupriyanov AV. Crop growth monitoring through Sentinel and Landsat data based NDVI time-series. Computer Optics 2020; 44(3): 409-419 is available at https://dx.doi.org/10.18287/2412-6179-CO-635
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