Special Section on Remote Sensing and Sensor Networks for Promoting Agro-Geoinformatics

Spatial evaluation of crop maps by the spatial production allocation model in China

[+] Author Affiliations
Jieyang Tan

Chinese Academy of Agricultural Sciences, Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Beijing 100081, China

Zhengguo Li, Peng Yang, Qiangyi Yu, Li Zhang, Wenbin Wu, Pengqin Tang

Chinese Academy of Agricultural Sciences, Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Beijing 100081, China

Zhenhuan Liu

Sun Yat-sen University, School of Geography and Planning, Guangzhou 510275, China

Liangzhi You

International Food Policy Research Institute, Environment and Production Technology Division, 2033K Street, NW, Washington, DC 20006, United States

J. Appl. Remote Sens. 8(1), 085197 (Nov 11, 2014). doi:10.1117/1.JRS.8.085197
History: Received August 6, 2014; Revised October 4, 2014; Accepted October 7, 2014
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Abstract.  The spatial production allocation model (SPAM) is one of the broadest spatial models of crop distribution and applies a cross-entropy method to downscale the global area and yield for multiple crops in the years 2000 and 2005 with a resolution of 5 arc min. To evaluate the allocation accuracy of SPAM for three staple crops (rice, wheat, and maize) in China, we compared these crop maps with remote-sensed cropland data derived from national land cover datasets. This comparison was conducted using a scheme that accounts for spatial differences at the pixel level. Overall, the map of maize has the highest area accuracy, with 64% reasonable pixels (covering 96% of the total maize area); these values were 57% (90% coverage) and 44% (81% coverage) for the wheat and rice maps, respectively. On the provincial scale, the area accuracies of crop maps in the top 10 provinces are better than those of the other provinces. Furthermore, the crop area consistency in rain-fed cropland is better than that in irrigated cropland. These evaluations provide decision makers with information regarding the strengths and weaknesses of SPAM products. This study also recommends priorities for further work to improve the reliability, utility, and periodic repeatability of crop distribution products.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Jieyang Tan ; Zhengguo Li ; Peng Yang ; Qiangyi Yu ; Li Zhang, et al.
"Spatial evaluation of crop maps by the spatial production allocation model in China", J. Appl. Remote Sens. 8(1), 085197 (Nov 11, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.085197


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