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Journal of Applied Remote Sensing

Improving sampling efficiency of crop acreage estimation using wheat planting rule from historical remote sensing
Author(s): Jinshui Zhang; Shuang Zhu; Xiufang Zhu; Guanyuan Shuai; Dengfeng Xie
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Paper Abstract

The technology of remote sensing combining sampling is an effective way to estimate crop acreage (CA) at large scale. Previous research proved that if the crop proportion within a sampling unit is sufficiently stable from year to year, pixels classified from historical remote sensing images could offer reliable regression estimators for current CA. However, previous works explored various approaches for CA estimation using one-year historical data, which makes it difficult to determine which year has the highest correlation to the targeted year, especially for a region where background information about the cultivated planting system is scarce. We estimated the winter wheat acreage of Beijing in 2009 by using two stratification variables including the coefficient of variance and the mean CA of the sampling units via a two-stage stratified sampling method with multiple historical remotely sensed data. Results show that: (1) our method has higher sampling average accuracy and lower standard errors of sample averages than simple random sampling or the one-stage stratification method with CA as the auxiliary variable, which are the usual methods employed in the previous studies. (2) Fewer samples are required to get the predefined accuracy, which reduces costs. (3) Generally, using mean CA derived from multiyear historical remotely sensed data as the auxiliary variable has a higher accuracy than those data using CA derived from one-year historical remote sensing images as the auxiliary variable in one-stage sampling.

Paper Details

PDF: 13 pages
J. Appl. Remote Sens. 8(1) 083663 doi: 10.1117/1.JRS.8.083663
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1, January 2014
Show Author Affiliations
Jinshui Zhang, Beijing Normal Univ. (China)
Shuang Zhu, Beijing Normal Univ. (China)
Xiufang Zhu, Beijing Normal Univ. (China)
Guanyuan Shuai, Beijing Normal Univ. (China)
Dengfeng Xie, Beijing Normal Univ. (China)

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