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[1]FAN Tiancheng,JIA Yunfei,LI Yunfei,et al.Prediction of Gully Distribution Probability in Yanhe Basin Based on Remote Sensing Image and Logistic Regression Model[J].Research of Soil and Water Conservation,2022,29(04):316-321.

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Prediction of Gully Distribution Probability in Yanhe Basin Based on Remote Sensing Image and Logistic Regression Model

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 29 Number of periods: 2022 04 Page number: 316-321 Column: Public date: 2022-06-20

Title:: Prediction of Gully Distribution Probability in Yanhe Basin Based on Remote Sensing Image and Logistic Regression Model

Author(s):: FAN Tiancheng, JIA Yunfei, LI Yunfei, ZHAO Jianlin; (School of Geological Engineering and Surveying and Mapping, Chang'an University, Xi'an 710054, China)

Keywords:: remote sensing image; gully distribution; logistic regression model; multiple-factor; Yanhe Basin; Loess Plateau

CLC:: P208

DOI:: -

Abstract:: In order to study the spatial distribution characteristics of gully landform on the Loess Plateau, remote sensing images and machine learning were used to extract gully landform, and the spatial distribution and environmental control factors of gully landform in the Yanhe Basin were studied. We estimated the probability of gully distribution based on a large number of gully samples extracted manually from Google Earth Pro platform and the logical regression model. Based on the Landsat8-OLI image, we established 10 environmental and spectrum factors, including the first three variables of principal component analysis, the first three variables of Landsat8-OLI transform, NDVI, elevation, slope as well as aspect, to calibrate the logistic regression method. Then, the model was used to predict the probability distribution of gullies in the entire Yanhe Basin. The results show that:(1)among the 10 variables, the most important factor is brightness with the R²_McF of 0.158, while elevation has the lowest contribution with the R²_McF of 3.6×10^-5;(2)the optimal logistic regression model is determined by the combined factors of Brightness, PCA₁, Greenness, Wetness, PCA₃ and slope, and its overall R²_McF is 0.206;(3)the accuracy of the optimal logistic regression model is 73.72% and the AUC value of the ROC curve is 0.80, which indicates that the model has relatively higher accuracy to estimate the distribution of gully on the Loess Plateau;(4)the gully landform accounts for 52.05% of the total areas of Yanhe Basin. The study shows that the distribution of gullies in Yanhe Basin gradually concentrates from northwest to southeast.

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Last Update: 2022-06-20