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Double-Rice System Simulation in a Topographically Diverse Region-A Remote-Sensing-Driven Case Study in Hunan Province of China

文献类型：期刊论文

作者Zhang, Jing1; Zhang, Zhao1; Wang, Chenzhi3; Tao, Fulu2
刊名REMOTE SENSING
出版日期2019-07-01
卷号11期号:13页码:19
关键词topography landform double rice crop model MCWLA remote sensing
DOI10.3390/rs11131577
通讯作者Zhang, Zhao(zhangzhao@bnu.edu.cn)
英文摘要Few studies have focused on the potential impacts of topography on regional crop simulation, which might constrain the development of crop models and lead to inaccurate estimations for food security. In this study, we used remote sensing data to calibrate a regional crop model (MCWLA-Rice) for yield simulation in a double-rice crop rotation system in counties of Hunan province dominated by three landforms (plain, hill, and mountain). The calibration scheme with coarse remote sensing data (Global LAnd Surface Satellite, GLASS) greatly improved model accuracy for the double-rice system and is a promising method for yield estimation in large areas. The average improvement in relative root mean square error (RRMSE) was at most 48.00% for early rice and 41.25% for late rice. The average improvement in coefficient of determination (R-2) value was at most 0.54 for early rice and 0.19 for late rice. Estimation of yield in counties dominated by different landform types indicated that: (1) MCWLA-Rice tended to be unstable in areas of complex topography and resulted in unbalanced proportions of overestimations and underestimations. (2) Differences in yield simulation between early rice and late rice varied among counties; yield estimates were highest in predominantly hilly counties, followed by counties dominated by plains, and lowest in predominantly mountainous counties. The results indicated that the topography might harm the accuracy of crop model simulations. Integration of topographic factors into crop models may enable yield estimation with enhanced accuracy to promote social development.
WOS关键词LEAF-AREA INDEX ; CLIMATE-CHANGE ; WINTER-WHEAT ; TEMPERATURE STRESS ; CROP PRODUCTIVITY ; DATA ASSIMILATION ; YIELD ESTIMATION ; ELEVATED CO2 ; LOWLAND RICE ; MODEL
资助项目National Key Research and Development Program of China[2017YFD0300301] ; National Key Research and Development Program of China[2016YFD0300201] ; National Natural Science Foundation of China[31761143006] ; National Natural Science Foundation of China[31561143003] ; National Natural Science Foundation of China[41571493] ; National Natural Science Foundation of China[41571088] ; State Key Laboratory of Earth Surface Processes and Resource Ecology
WOS研究方向Remote Sensing
语种英语
WOS记录号WOS:000477049000069
出版者MDPI
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; State Key Laboratory of Earth Surface Processes and Resource Ecology
源URL[http://ir.igsnrr.ac.cn/handle/311030/68887]  
专题中国科学院地理科学与资源研究所
通讯作者Zhang, Zhao
作者单位1.Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Key Lab Environm Change & Nat Hazards, Fac Geog Sci, Beijing 100875, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
3.Peking Univ, Coll Urban & Environm Sci, Sino French Inst Earth Syst Sci, Beijing 100871, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Jing,Zhang, Zhao,Wang, Chenzhi,et al. Double-Rice System Simulation in a Topographically Diverse Region-A Remote-Sensing-Driven Case Study in Hunan Province of China[J]. REMOTE SENSING,2019,11(13):19.
APA Zhang, Jing,Zhang, Zhao,Wang, Chenzhi,&Tao, Fulu.(2019).Double-Rice System Simulation in a Topographically Diverse Region-A Remote-Sensing-Driven Case Study in Hunan Province of China.REMOTE SENSING,11(13),19.
MLA Zhang, Jing,et al."Double-Rice System Simulation in a Topographically Diverse Region-A Remote-Sensing-Driven Case Study in Hunan Province of China".REMOTE SENSING 11.13(2019):19.

入库方式： OAI收割

来源：地理科学与资源研究所

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