Sampling methods of soil erosion at county scale based on spatial autocorrelation

CHEN Chao, QI Fei, XU Yannan, LI Jiazuo, ZHAO Chuanpu, SU Xinyu

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2022, Vol. 46 ›› Issue (3) : 177-184.

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南京林业大学学报（自然科学版）
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JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2022, Vol. 46 ›› Issue (3) : 177-184. DOI: 10.12302/j.issn.1000-2006.202103028

Sampling methods of soil erosion at county scale based on spatial autocorrelation

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Abstract

【Objective】Soil erosion is one of the main ecological and environmental problems in China. To take effective measures to control soil erosion, field investigations must be undertaken. It is important to maintain the ecological balance and promote sustainable development of the social economy. 【Method】In China, the method of soil erosion investigation combining sampling surveys and a Chinese soil loss equation (CSLE) experience model is one of the most important methods to obtain the soil erosion status at different scales. Stratified sampling with unequal probability and the CSLE experience model were used in the First National Water Census from 2010 to 2012. To further explore the influence of different spatial sampling methods and spatial interpolations on estimation precision in soil erosion areas, and to provide technological support for fast regional evaluation of soil erosion, this paper uses Mengyin County of Yimeng Mountain as the study area. Based on the spatial autocorrelation theory, using GF-1 and GF-6 satellite images, a CSLE model, 1∶10 000 topographic map and other data, three spatial sampling methods of spatial random sampling, spatial systematic sampling, spatial stratified sampling and four spatial interpolation methods of inverse distance weight, spline function method, ordinary Kriging, and co-Kriging was applied to predict the soil erosion area in Mengyin County in the Yimeng Mountain area. 【Result】(1) According to the global Moran’ I index, Z score and average pattern type, 400 m × 400 m square is the optimal size for sampling units. (2)The efficiency and accuracy of the sampling survey were affected by the sampling methods. Compared with spatial random samples and spatial systematic sampling, which had more than 250 units, spatial stratified sampling by slope had the highest sampling efficiency with the minimum sample size (150 units) and the highest sampling accuracy (96.69%). (3) Using spatial stratified sampling, the percentage of the soil erosion area for both ordinary Kriging and co-Kriging was similar to the grid calculation with a relative error of 8.25% and 9.85%, while that of the inverse distance weight and the spline function method were quite different from the grid calculation with a relative error of more than 25%. The spatial distribution of soil erosion-based co-Kriging was more detailed and is mainly influenced by the slope, but there were some differences between the spatial interpolation and the grid calculation. 【Conclusion】In view of the precision and workload in soil erosion surveys at the county scale in Yimeng Mountain area, stratified sampling, ordinary Kriging or co-Kriging are advisable for rapid prediction of soil erosion to provide an important data support for regional ecological environment protection.

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soil erosion / spatial autocorrelation / spatial sampling method / spatial interpolation / sampling unit size / Yimeng Mountain area

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CHEN Chao , QI Fei , XU Yannan , et al . Sampling methods of soil erosion at county scale based on spatial autocorrelation[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2022, 46(3): 177-184 https://doi.org/10.12302/j.issn.1000-2006.202103028

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