The influence of land use and land cover change on landslide susceptibility: a case study in Zhushan Town, Xuan'en County (Hubei, China)

• Published in: Natural hazards and earth system sciences Vol. 19; no. 10; pp. 2207 - 2228
• Main Authors: Chen, Lixia, Guo, Zizheng, Yin, Kunlong, Shrestha, Dhruba Pikha, Jin, Shikuan
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 10.10.2019; Copernicus Publications
• Subjects: Aerial photographs; Aerial photography; Aerial surveys; Agricultural land; Arable land; Case studies; China; Classification; Economic activities; Environmental aspects; Grasslands; Human engineering; Hydrologic analysis; Hydrological analysis; Hydrology; Image acquisition; Image classification; Infrastructure (Economics); Land cover; Land use; Land use controls; Land use management; Land use planning; Landslides; Mountain regions; Mountainous areas; Mountains; Regression analysis; Regression models; Remote sensing; Slope; Slopes; Spatial distribution; Surveys; Temperature; China; Hubei China
• ISSN: 1684-9981; 1561-8633; 1684-9981
• DOI: 10.5194/nhess-19-2207-2019

Land use and land cover change can increase or decrease landslide susceptibility (LS) in the mountainous areas. In the hilly and mountainous part of southwestern China, land use and land cover change (LUCC) has taken place in the last decades due to infrastructure development and rapid economic activities. This development and activities can worsen the slope susceptible to sliding due to mostly the cutting of slopes. This study, taking Zhushan Town, Xuan'en County, as the study area, aims to evaluate the influence of land use and land cover change on landslide susceptibility at a regional scale. Spatial distribution of landslides was determined in terms of visual interpretation of aerial photographs and remote sensing images, supported by field surveys. Two types of land use and land cover (LUC) maps, with a time interval covering 21 years (1992–2013), were prepared: the first was obtained by the neural net classification of images acquired in 1992 and the second by the object-oriented classification of images in 2002 and 2013. Landslide-susceptible areas were analyzed using the logistic regression model (LRM) in which six influencing factors were chosen as the landslide susceptibility indices. In addition, the hydrologic analysis method was applied to optimize the partitioning of the terrain. The results indicated that the LUCC in the region was mainly the transformation from the grassland and arable land to the forest land, which is increased by 34.3 %. An increase of 1.9 % is shown in the area where human engineering activities concentrate. The comparison of landslide susceptibility maps among different periods revealed that human engineering activities were the most important factor in increasing LS in this region. Such results emphasize the requirement of a reasonable land use planning activity process.