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Double-Rice System Simulation in a Topographically Diverse Region-A Remote-Sensing-Driven Case Study in Hunan Province of China
Zhang, Jing1; Zhang, Zhao1; Wang, Chenzhi2; Tao, Fulu3
2019-07-01
Source PublicationREMOTE SENSING
Volume11Issue:13Pages:19
Corresponding AuthorZhang, Zhao(zhangzhao@bnu.edu.cn)
AbstractFew 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.
Keywordtopography landform double rice crop model MCWLA remote sensing
DOI10.3390/rs11131577
WOS KeywordLEAF-AREA INDEX ; CLIMATE-CHANGE ; WINTER-WHEAT ; TEMPERATURE STRESS ; CROP PRODUCTIVITY ; DATA ASSIMILATION ; YIELD ESTIMATION ; ELEVATED CO2 ; LOWLAND RICE ; MODEL
Indexed BySCI
Language英语
Funding ProjectNational 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
Funding OrganizationNational Key Research and Development Program of China ; National Natural Science Foundation of China ; State Key Laboratory of Earth Surface Processes and Resource Ecology
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000477049000069
PublisherMDPI
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/68888
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhang, Zhao
Affiliation1.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.Peking Univ, Coll Urban & Environm Sci, Sino French Inst Earth Syst Sci, Beijing 100871, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
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.
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