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Journal of Applied Remote Sensing

Optimization of spatial sampling schemes for maize acreage estimation
Author(s): Di Wang; Qingbo Zhou; Zhongxin Chen; Jia Liu
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Paper Abstract

Sampling fraction, sample layout, and sampling unit scale are the three basic elements of a spatial sampling scheme. Optimizing these factors plays an important role in decreasing the sampling cost and improving the extrapolation accuracy of survey sampling. Spatial analysis, “3S” techniques, and traditional sampling methods are employed to optimize the three basic elements. Dehui County in Jilin Province, China was chosen as the study area, maize sown acreage as the study object, and square grids as the shape of the sampling units. The experimental results demonstrate that the spatial autocorrelation of sampling unit increases with its scale. When the scale is 500×500  m, there is almost no spatial autocorrelation among sampling units, so 500×500  m is selected as the optimal sampling unit scale. The spatial stratified heterogeneity of sampling units decreases with increasing scale. When the sampling unit scale is 500×500  m, it must be stratified to improve the sampling efficiency. The cultivated land area in one sampling unit can be selected as a stratification criterion due to the significant linear correlation relationship between it and the maize area in all sampling units. Stratified system isometric sampling and 1% are the optimal sample layout pattern and sampling fraction, respectively. This research provides a theoretical basis for improving the spatial sampling efficiency to estimate crop acreage.

Paper Details

Date Published: 26 May 2015
PDF: 12 pages
J. Appl. Remote Sens. 9(1) 097092 doi: 10.1117/1.JRS.9.097092
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Di Wang, Key Laboratory of Agri-Informatics (China)
Institute of Agricultural Resources and Regional Planning (China)
Qingbo Zhou, Key Laboratory of Agri-Informatics (China)
Institute of Agricultural Resources and Regional Planning (China)
Zhongxin Chen, Key Laboratory of Agri-Informatics (China)
Institute of Agricultural Resources and Regional Planning (China)
Jia Liu, Key Laboratory of Agri-Informatics (China)
Institute of Agricultural Resources and Regional Planning (China)


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