Crop yield estimation based on assimilation of crop models and remote sensing data: A systematic evaluation

Li Luo, Shikun Sun, Jing Xue, Zihan Gao, Jinfeng Zhao, Yali Yin, Fei Gao and Xiaobo Luan

Agricultural Systems, 2023, vol. 210, issue C

Abstract: With the warming trend and the increasing frequency of extreme weather events, accurate crop yield estimation is becoming urgent. Crop yield estimation mainly consists of two methods: crop model simulation and remote sensing observations. Crop models can achieve accurate simulations of crop growth at field scales. However, in regional applications, they are limited by the spatial heterogeneity of certain input parameters. Remote sensing observations can obtain crop status over large areas quickly and conveniently, while lacking knowledge of crop growth processes. By combining the advantages of crop models and remote sensing, crop yield estimation with spatiotemporal continuity can be achieved using data assimilation methods.

Keywords: Data assimilation; Crop model; Remote sensing; Crop yield; Systematic literature review (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:210:y:2023:i:c:s0308521x23001166

DOI: 10.1016/j.agsy.2023.103711

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