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

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 o...

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Main Authors: M.S. Boori, K. Choudhary, A.V. Kupriyanov
Format: Article
Language:English
Published: Samara National Research University 2020-06-01
Series:Компьютерная оптика
Subjects:
Online Access:http://computeroptics.smr.ru/KO/PDF/KO44-3/440312.pdf
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spelling doaj-b27daaf96e28492f8731bf9e235fd2192020-11-25T03:16:22ZengSamara National Research UniversityКомпьютерная оптика0134-24522412-61792020-06-0144340941910.18287/2412-6179-CO-635Crop growth monitoring through Sentinel and Landsat data based NDVI time-seriesM.S. Boori 0K. Choudhary1A.V. Kupriyanov 2Samara National Research University, Moskovskoye Shosse 34, 443086, Samara, Russia; American Sentinel University, Colorado, USA; University of Rennes 2, Rennes, FranceSamara National Research University, Moskovskoye Shosse 34, 443086, Samara, Russia; The Hong Kong Polytechnic University, Kowloon, Hong Kong; University of Rennes 2, Rennes, FranceSamara National Research University, Moskovskoye Shosse 34, 443086, Samara, Russia; IPSI RAS – Branch of the FSRC "Crystallography and Photonics" RAS, Molodogvardeyskaya 151, 443001, Samara, RussiaCrop 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.http://computeroptics.smr.ru/KO/PDF/KO44-3/440312.pdfcrop phenologyndvi time-seriessentinel-2 & landsatremote sensing
collection DOAJ
language English
format Article
sources DOAJ
author M.S. Boori
K. Choudhary
A.V. Kupriyanov
spellingShingle M.S. Boori
K. Choudhary
A.V. Kupriyanov
Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
Компьютерная оптика
crop phenology
ndvi time-series
sentinel-2 & landsat
remote sensing
author_facet M.S. Boori
K. Choudhary
A.V. Kupriyanov
author_sort M.S. Boori
title Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
title_short Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
title_full Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
title_fullStr Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
title_full_unstemmed Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
title_sort crop growth monitoring through sentinel and landsat data based ndvi time-series
publisher Samara National Research University
series Компьютерная оптика
issn 0134-2452
2412-6179
publishDate 2020-06-01
description 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.
topic crop phenology
ndvi time-series
sentinel-2 & landsat
remote sensing
url http://computeroptics.smr.ru/KO/PDF/KO44-3/440312.pdf
work_keys_str_mv AT msboori cropgrowthmonitoringthroughsentinelandlandsatdatabasedndvitimeseries
AT kchoudhary cropgrowthmonitoringthroughsentinelandlandsatdatabasedndvitimeseries
AT avkupriyanov cropgrowthmonitoringthroughsentinelandlandsatdatabasedndvitimeseries
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