中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Maize Crop Coefficient Estimated from UAV-Measured Multispectral Vegetation Indices

文献类型:期刊论文

作者Zhang, Yu1,2,5; Han, Wenting1,3; Niu, Xiaotao1,5; Li, Guang4
刊名SENSORS
出版日期2019-12-01
卷号19期号:23页码:17
关键词crop coefficient (K-c) vegetation indices deficit irrigation regression model soil water balance stress coefficient
DOI10.3390/s19235250
通讯作者Han, Wenting(hanwt2000@126.com)
英文摘要The rapid, accurate, and real-time estimation of crop coefficients at the farm scale is one of the key prerequisites in precision agricultural water management. This study aimed to map the maize crop coefficient (K-c) with improved accuracy under different levels of deficit irrigation. The proposed method for estimating the K-c is based on multispectral images of high spatial resolution taken using an unmanned aerial vehicle (UAV). The analysis was performed on five experimental plots using K-c values measured from the daily soil water balance in Ordos, Inner Mongolia, China. To accurately estimate the K-c, the fraction of vegetation cover (f(c)) derived from the normalized difference vegetation index (NDVI) was used to compare with field measurements, and the stress coefficients (K-s) calculated from two vegetation index (VI) regression models were compared. The results showed that the NDVI values under different levels of deficit irrigation had no significant difference in the reproductive stage but changed significantly in the maturation stage, with a decrease of 0.09 with 72% water applied difference. The f(c) calculated from the NDVI had a high correlation with field measurement data, with a coefficient of determination (R-2) of 0.93. The ratios of transformed chlorophyll absorption in reflectance index (TCARI) to renormalized difference vegetation index (RDVI) and TCARI to soil-adjusted vegetation index (SAVI) were used, respectively, to establish two types of K-s regression models to retrieve K-c. Compared to the TCARI/SAVI model, the TCARI/RDVI model under different levels of deficit irrigation had better correlation with K-c, with R-2 and root-mean-square error (RMSE) values ranging from 0.68 to 0.80 and from 0.140 to 0.232, respectively. Compared to K-c calculated from on-site measurements, the K-c values retrieved from the VI regression models established in this study had greater ability to assess the field variability of soil and crops. Overall, use of the UAV-measured multispectral vegetation index approach could improve water management at the farm scale.
WOS关键词WATER-USE EFFICIENCY ; LEAF-AREA INDEX ; WINTER-WHEAT ; SOIL EVAPORATION ; IRRIGATED MAIZE ; DROUGHT STRESS ; EVAPOTRANSPIRATION ; MODEL ; CORN ; TRANSPIRATION
资助项目National Key R&D plan from the MOST of China[2017YFC0403203] ; Synergetic Innovation of Industry-University-Research Cooperation Project plan from Yangling[2018CXY-23] ; 111 Project ; Key Discipline Construction Project of Northwest Agriculture and Forestry University[2017-C03]
WOS研究方向Chemistry ; Engineering ; Instruments & Instrumentation
语种英语
WOS记录号WOS:000507606200193
出版者MDPI
资助机构National Key R&D plan from the MOST of China ; Synergetic Innovation of Industry-University-Research Cooperation Project plan from Yangling ; 111 Project ; Key Discipline Construction Project of Northwest Agriculture and Forestry University
源URL[http://ir.igsnrr.ac.cn/handle/311030/132170]  
专题中国科学院地理科学与资源研究所
通讯作者Han, Wenting
作者单位1.Chinese Acad Sci & Minist Water Resources, Inst Soil & Water Conservat, Yangling 712100, Shaanxi, Peoples R China
2.Minist Agr, Key Lab Agr Internet Things, Yangling 712100, Shaanxi, Peoples R China
3.Northwest A&F Univ, Inst Soil & Water Conservat, Yangling 712100, Shaanxi, Peoples R China
4.Northwest A&F Univ, Coll Mech & Elect Engn, Yangling 712100, Shaanxi, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Yu,Han, Wenting,Niu, Xiaotao,et al. Maize Crop Coefficient Estimated from UAV-Measured Multispectral Vegetation Indices[J]. SENSORS,2019,19(23):17.
APA Zhang, Yu,Han, Wenting,Niu, Xiaotao,&Li, Guang.(2019).Maize Crop Coefficient Estimated from UAV-Measured Multispectral Vegetation Indices.SENSORS,19(23),17.
MLA Zhang, Yu,et al."Maize Crop Coefficient Estimated from UAV-Measured Multispectral Vegetation Indices".SENSORS 19.23(2019):17.

入库方式: OAI收割

来源:地理科学与资源研究所

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