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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Veröffentlicht in:	Remote sensing of environment 2020-12, Vol.251 (C), p.112095, Article 112095
Hauptverfasser:	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:	Artikel
Sprache:	eng
Schlagworte:	Agricultural land Algorithms Cloud computing Crop phenophase Cropping intensity Cropping systems ENVIRONMENTAL SCIENCES Food Food production Food security Land cover Land use Mapping Multiple cropping Multiple sensors Natural resources NDVI time series Normalized difference vegetative index Phenology Pixels Remote sensing Satellite imagery Satellites Seasonal variations Spatial discrimination Spatial resolution Spectroradiometers Sustainable development Vegetation Vegetation index
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