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Canopy structure dynamics constraints and time sequence alignment for improving retrieval of rice leaf area index from multi-temporal Sentinel-1 imagery

文献类型：期刊论文

作者Liu, Yu2; Wang, Bo2; Tao, Junfeng2; Tian, Sijing2; Sheng, Qinghong2; Li, Jun2; Wang, Shuwei3; Liu, Xiaoli4; He, Honglin1
刊名COMPUTERS AND ELECTRONICS IN AGRICULTURE
出版日期2024-12-01
卷号227页码:23
关键词Canopy structure dynamics Dynamic time warping Hierarchical linear model Leaf area index Multi-temporal Sentinel-1 Radar vegetation index Rice
ISSN号0168-1699
DOI10.1016/j.compag.2024.109658
产权排序4
英文摘要Due to the limited availability of in-situ observation data, most existing leaf area index (LAI) inversion models do not fully leverage temporal information. Furthermore, the phenological evolution of crops can result in unstable and inaccurate retrieval outcomes. To address these challenges, this study proposes a novel framework for LAI inversion based on Sentinel-1. First, the constrained canopy structure dynamic hierarchical linear model (CSDHLM) is constructed, which integrates canopy dynamics information and temporal constraints. Second, the microwave scattering characteristics at various crop growth stages used to develop the phenological segment dynamic time warping (PSDTW). The PSDTW aims to address the challenges posed by inconsistent phenological dynamics across different plots. The quantitative evaluation results indicate that CSDHLM more accurately captures the temporal changes of LAI (R2 = 0.7688, RMSE = 0.8742) compared to hierarchical linear model (R2 = 0.7234, RMSE = 0.9561) and gaussian process regression (R2 = 0.7143, RMSE = 0.9717). Additionally, the LAI inversion results obtained by combining CSDHLM and PSDTW have greater robustness (R2 = 0.7332, RMSE = 1.4032) across diverse agricultural scenarios. This study emphasizes the importance of phenological information in estimating rice LAI, and the proposed framework is capable of generating long-term rice LAI maps with high resolution, demonstrating significant potential for agricultural applications at the regional scale.
WOS关键词VEGETATION PHENOLOGY ; LAI ; ALGORITHM ; OPTIMIZATION ; PRODUCTS ; SAR ; INFORMATION ; MULTISOURCE ; MODEL ; CORN
资助项目Theory and Method of Satellite Dynamic Photogrammetry for Near-earth Space Object from the National Natural Science Foundation of China[42271448] ; China's National Space Administration[D040307]
WOS研究方向Agriculture ; Computer Science
语种英语
WOS记录号WOS:001360524300001
出版者ELSEVIER SCI LTD
资助机构Theory and Method of Satellite Dynamic Photogrammetry for Near-earth Space Object from the National Natural Science Foundation of China ; China's National Space Administration
源URL[http://ir.igsnrr.ac.cn/handle/311030/210639]  
专题生态系统网络观测与模拟院重点实验室_外文论文
通讯作者Wang, Bo
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
2.Nanjing Univ Aeronaut & Astronaut, Coll Astronaut, Nanjing 211106, Peoples R China
3.Chinese Acad Sci, Inst Soil Sci, Changshu Natl Agroecosystem Observat & Res Stn, Nanjing 210008, Peoples R China
4.Chinese Acad Sci, Inst Soil Sci, Yingtan Natl Agroecosystem Observat & Res Stn, Nanjing 210008, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Yu,Wang, Bo,Tao, Junfeng,et al. Canopy structure dynamics constraints and time sequence alignment for improving retrieval of rice leaf area index from multi-temporal Sentinel-1 imagery[J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE,2024,227:23.
APA Liu, Yu.,Wang, Bo.,Tao, Junfeng.,Tian, Sijing.,Sheng, Qinghong.,...&He, Honglin.(2024).Canopy structure dynamics constraints and time sequence alignment for improving retrieval of rice leaf area index from multi-temporal Sentinel-1 imagery.COMPUTERS AND ELECTRONICS IN AGRICULTURE,227,23.
MLA Liu, Yu,et al."Canopy structure dynamics constraints and time sequence alignment for improving retrieval of rice leaf area index from multi-temporal Sentinel-1 imagery".COMPUTERS AND ELECTRONICS IN AGRICULTURE 227(2024):23.

入库方式： OAI收割

来源：地理科学与资源研究所

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