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Article

Assessment of Influencing Factors on the Spatial Variability of SOM in the Red Beds of the Nanxiong Basin of China, Using GIS and Geo-Statistical Methods

1
School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, China
2
Guangdong Key Laboratory of Oceanic Civil Engineering, Guangzhou 510275, China
3
Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519000, China
4
School of Geographical Sciences, Southwest University, Chongqing 400715, China
*
Author to whom correspondence should be addressed.
Academic Editors: Palaiologos Palaiologou, Kostas Kalabokidis and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(6), 366; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10060366
Received: 12 March 2021 / Revised: 23 May 2021 / Accepted: 25 May 2021 / Published: 29 May 2021
(This article belongs to the Special Issue The Use of Geo-Spatial Tools in Forestry)
Understanding the spatial variability of soil organic matter (SOM) is crucial for implementing precise land degradation control and fertilization to improve crop productivity. Studying spatial variability provides a scientific basis for precision fertilization and land degradation control. In this study, geostatistics and classical statistical methods were used to analyze the spatial variability of SOM and its influencing factors under various degrees of land degradation in the red bed area of southern China. The results demonstrate a declining trend for SOM content with increasing land degradation. The SOM content differs profoundly under different land degradation degrees. The coefficient of variation ranges from 13.61% for extreme land degradation to 8.98% for mild land degradation, 7.96% for moderate land degradation, and 5.64% for severe land degradation. A significant positive correlation is displayed between the altitude and the SOM (p < 0.01) under mild and moderate land degradation conditions. Bulk density and pH value have a significant negative correlation with SOM (p < 0.01). It can be observed that terrain factors, as well as physical and chemical soil parameters, have a great influence on SOM. View Full-Text
Keywords: soil organic matter; land degradation; semivariogram; spatial distribution; classical statistics soil organic matter; land degradation; semivariogram; spatial distribution; classical statistics
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MDPI and ACS Style

Yan, P.; Lin, K.; Wang, Y.; Tu, X.; Bai, C.; Yan, L. Assessment of Influencing Factors on the Spatial Variability of SOM in the Red Beds of the Nanxiong Basin of China, Using GIS and Geo-Statistical Methods. ISPRS Int. J. Geo-Inf. 2021, 10, 366. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10060366

AMA Style

Yan P, Lin K, Wang Y, Tu X, Bai C, Yan L. Assessment of Influencing Factors on the Spatial Variability of SOM in the Red Beds of the Nanxiong Basin of China, Using GIS and Geo-Statistical Methods. ISPRS International Journal of Geo-Information. 2021; 10(6):366. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10060366

Chicago/Turabian Style

Yan, Ping, Kairong Lin, Yiren Wang, Xinjun Tu, Chunmei Bai, and Luobin Yan. 2021. "Assessment of Influencing Factors on the Spatial Variability of SOM in the Red Beds of the Nanxiong Basin of China, Using GIS and Geo-Statistical Methods" ISPRS International Journal of Geo-Information 10, no. 6: 366. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10060366

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