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

• 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: Crops; Landsat; Non-sampling errors; Remote sensing; Crop area statistics
• Online Access: https://peerj.com/articles/5824.pdf

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.