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HIDYM: A high-resolution gross primary productivity and dynamic harvest index based crop yield mapper

文献类型： 外文期刊

作者： Yu, Weiguo 1 ; Li, Dong 1 ; Zheng, Hengbiao 1 ; Yao, Xia 1 ; Zhu, Yan 1 ; Cao, Weixing 1 ; Qiu, Lin 2 ; Cheng, Tao 1 ; Zhang, Yongguang 3 ; Zhou, Yanlian 3 ;

作者机构： 1.Nanjing Agr Univ, Natl Engn & Technol Ctr Informat Agr NETCIA, MOE Engn Res Ctr Smart Agr, MARA Key Lab Crop Syst Anal & Decis Making,Jiangsu, One Weigang, Nanjing 210095, Jiangsu, Peoples R China

2.Jiangsu Acad Agr Sci, Inst Agr Informat, Nanjing 210014, Jiangsu, Peoples R China

3.Nanjing Univ, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Key Lab Land Satellite Remote Sensing Applicat, Sch Geog & Ocean Sci,Minist Nat Resources, Nanjing 210023, Jiangsu, Peoples R China

关键词： Google Earth Engine; Sentinel-2; LUE; Rice; Winter wheat; Estimation

期刊名称：REMOTE SENSING OF ENVIRONMENT （ 影响因子：11.1； 五年影响因子：12.7 ）

ISSN： 0034-4257

年卷期： 2024 年 311 卷

页码：

收录情况： SCI

摘要： Reliable prediction of field-level crop yield over large regions is a prerequisite for informed decision-making in precision crop management. One of common Earth observation approaches is to predict crop yield through the estimation of gross primary productivity (GPP) and a fixed crop-specific harvest index (HI), but few studies have considered the spatio-temporal dynamics of HI. Although some studies have used two-leaf light use efficiency (TL-LUE) models to reduce GPP estimation uncertainties by distinguishing sunlit and shaded leaves, it remains unclear about the physical mechanism underlying the incorporation of environmental regulations into TL-LUE. This study proposed a high-resolution GPP and dynamic HI based yield mapper (HIDYM), which incorporated the generation of 10-m resolution GPP product via a modified TL-LUE (mTL-LUE) model and the estimation of dynamic HI from Sentinel-2 imagery. The mTL-LUE was developed to account for the effect of environmental factors on GPP. Dynamic HI was estimated per pixel and per year by combining the phenological difference ratio and tasseled cap transformation of Sentinel-2 imagery at three critical stages of crop growth. The results demonstrated that HIDYM could capture the spatial and interannual variations of field-level rice and winter wheat yields. The improvement of HIDYM over the fixed HI strategy was more pronounced for rice (R2: 0.64-0.72 vs 0.34-0.48 for 2019-2022) than for winter wheat (R2: 0.72 vs 0.66 for 2021-2022 and 0.71 vs 0.57 for 2022-2023). The proposed methodology has great potential for the routine prediction of crop yields over large-scale croplands, especially in smallholder farming systems.

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