An index of non-sampling error in area frame sampling based on remote sensing data

Agricultural areas are often surveyed using area frame sampling. Using non-updated area sampling frame causes significant non-sampling errors when land cover and usage changes between updates. To address this problem, a novel method is proposed to estimate non-sampling errors in crop area statistics...

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Bibliographic Details
Main Authors: Mingquan Wu, Dailiang Peng, Yuchu Qin, Zheng Niu, Chenghai Yang, Wang Li, Pengyu Hao, Chunyang Zhang
Format: Article
Language:English
Published: PeerJ Inc. 2018-11-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/5824.pdf
Description
Summary:Agricultural areas are often surveyed using area frame sampling. Using non-updated area sampling frame causes significant non-sampling errors when land cover and usage changes between updates. To address this problem, a novel method is proposed to estimate non-sampling errors in crop area statistics. Three parameters used in stratified sampling that are affected by land use changes were monitored using satellite remote sensing imagery: (1) the total number of sampling units; (2) the number of sampling units in each stratum; and (3) the mean value of selected sampling units in each stratum. A new index, called the non-sampling error by land use change index (NELUCI), was defined to estimate non-sampling errors. Using this method, the sizes of cropping areas in Bole, Xinjiang, China, were estimated with a coefficient of variation of 0.0237 and NELUCI of 0.0379. These are 0.0474 and 0.0994 lower, respectively, than errors calculated by traditional methods based on non-updated area sampling frame and selected sampling units.
ISSN:2167-8359