LI Y M, XIANG Q Y, DENG X L, et al. Evaluation of landslide susceptibility in Nujiang Prefecture based on optimized MaxEnt model[J]. Journal of Henan Polytechnic University(Natural Science) , 2025, 44(1): 57-67.

doi: 10.16186/j.cnki.1673-9787.2023070010

Received: 2023/07/06

Revised: 2023/09/14

Published: 2025/01/02

Evaluation of landslide susceptibility in Nujiang Prefecture based on optimized MaxEnt model

LI Yimin1,2,XIANG Qianying3, DENG Xuanlun1, FENG Xianjie3

1. School of Earth Sciences，Yunnan University， Kunming  650500， Yunnan， China; 2. Yunnan University Engineering Research Center of High-resolution Satellite Remote Sensing， Yunnan University， Kunming  650500， Yunnan， China; 3. Institute of International Rivers and Ecol-Security， Yunnan University， Kunming  650500， Yunnan， China

Abstract: Objectives Nujiang Prefecture is a typical alpine canyon area， frequent  landscape geological disasters seriously restricts local development. Methods To solve this problem， taking into account the actual situation in Nujiang Prefecture，14 influencing factors such as slope direction and elevation were selected from five aspects of meteorology and hydrology， topography and geo⁃morphology， stratigraphic lithology， vegetation ecology and human activities to judge the correlation between landslides and each influencing factor， and build an evaluation index system. The MaxEnt model feature combination （FC） and regularization multi⁃plier （RM） parameters were optimized， and the sample of the akaike information criterion（AICc）， Omission Rate （OR） and AUC （Area Under Curve） value before optimization were compared with that after opitimazation，and the occurrence of landslide hazards based on the optimized MaxEnt model was predictedto realize the landslide susceptibility evaluation in Nujiang Prefecture. Results The optimized MaxEnt model has excellent applicability in predicting landslide susceptibility in the study area （AUC=0.913））. Jackknife method was used to calculate the influence degree of each influencing factor on susceptibility. Elevation （S,23.2%）， slope （S9，22.4%）， settlement density （S5，14.2%）， distance from river（S1,13.7%）， distance from road （S4，9.6%） and lithology （S7，8.7%） tare the top six factors， with a cumulative contribution of 91.8%. The spatial proportions of extremely high， high， medium and low landslide susceptibility levels were 4.88%， 8.96%， 18.40% and 67.76%， respectively. The highest proportion of extremely high and high susceptibility areas was found in Lushui City. On the whole， extremely high and high susceptibility areas were mainly distributed in valleys along rivers and roads， while low susceptibility areas were mainly distributed in areas with little human activities and undeveloped river valleys. Conclusions The optimized MaxEnt model is more suitable for landslide sensitivity prediction in Nujiang Prefecture， and the research results can provide reference for disaster prevention， and land use planning in Nujiang Prefecture.

Key words: Nujiang Prefecture; maximum entropy model; landslide; susceptibility