A new framework to map fine resolution cropping intensity across the globe: Algorithm, validation, and implication

Accurate estimation of cropping intensity (CI), an indicator of food production, is well aligned with the ongoing efforts to achieve sustainable development goals (SDGs) under diminishing natural resources. The advancement in satellite remote sensing provides unprecedented opportunities for capturin...

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Bibliographic Details
Published in:	Remote sensing of environment Vol. 251; no. C; p. 112095
Main Authors:	Liu, Chong, Zhang, Qi, Tao, Shiqi, Qi, Jiaguo, Ding, Mingjun, Guan, Qihui, Wu, Bingfang, Zhang, Miao, Nabil, Mohsen, Tian, Fuyou, Zeng, Hongwei, Zhang, Ning, Bavuudorj, Ganbat, Rukundo, Emmanuel, Liu, Wenjun, Bofana, José, Beyene, Awetahegn Niguse, Elnashar, Abdelrazek
Format:	Journal Article
Language:	English
Published:	New York Elsevier Inc 15.12.2020 Elsevier BV Elsevier
Subjects:	Agricultural land Algorithms Cloud computing Crop phenophase cropland Cropping intensity Cropping systems environment ENVIRONMENTAL SCIENCES Food Food production Food security Internet Land cover Mapping Multiple cropping Multiple sensors Natural resources NDVI time series normalized difference vegetation index Normalized difference vegetative index Phenology Pixels Remote sensing Satellite imagery satellites Seasonal variations Spatial discrimination Spatial resolution Spectroradiometers Sustainable development time series analysis Vegetation Vegetation index NDVI time series Crop phenophase Multiple sensors Cropping intensity Remote sensing
ISSN:	0034-4257, 1879-0704
Online Access:	Get full text
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