Paper Info
Title
Estimating Crop Area at County Level on the North China Plain with an Indirect Sampling of Segments and an Adapted Regression Estimator.
Abstract
Image classifications, including sub-pixel analysis, are often used to estimate crop acreage directly. However, this type of assessment often leads to a biased estimation, because commission and omission errors generally do not compensate for each other. Regression estimators combine remote sensing information with more accurate ground data on a field sample, and can result in more accurate and cost-effective assessments of crop acreage. In this pilot study, which aims to produce crop statistics in Guoyang County, the area frame sampling approach is adapted to a strip-like cropping pattern on the North China Plain. Remote sensing information is also used to perform a stratification in which non-agricultural areas are excluded from the ground survey. In order to compute crop statistics, 202 ground points in the agriculture stratum were surveyed. Image classification was included as an auxiliary variable in the subsequent analysis to obtain a regression estimator. The results of this pilot study showed that the integration of remote sensing information as an auxiliary variable can improve the accuracy of estimation by reducing the variance of the estimates, as well as the cost effectiveness of an operational application at the county level in the region.
Year
DOI
Venue
2017
10.3390/s17112638
SENSORS
Keywords
Field
DocType
crop area,remote sensing image classification,area frame sampling,stratification,regression estimator
Regression,Crop,China,Cropping,Sampling (statistics),Engineering,Stratum,Contextual image classification,Statistics,Estimator
Journal
Volume
Issue
ISSN
17
11.0
1424-8220
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Qinghan Dong111.11
Jia Liu201.35
LiMin Wang35910.33
Zhongxin Chen46718.05
Javier Gallego541.13