Published November 22, 2024 | Version v2

LandslideSusceptibilityMappingData

Description

This project aims to predict geological hazard susceptibility using the LightGBM machine learning model with DEM-related data and other indicators.

The GIS database, source code, and CSV data correspond to the paper titled "Low-Time-Cost but Accurate Landslide Susceptibility Mapping: Identifying Triggering Factors with Solely DEM-Derived Indicators, LightGBM Algorithm, and Explainable Machine Learning Techniques."

The study area is located in Zhushan County, Shiyan City, Hubei Province, China.

Files

Code&Dataset.zip

Files (724.6 MB)

Name Size
md5:b17926144cc013ab69402645e47e6296
94.2 MB Preview Download
md5:39fdfa75ce83708820338a954cde7057
3.4 kB Preview Download
md5:cf393f5eea64585b7b3d29334fa3d021
630.4 MB Preview Download

Additional details

Dates

Other
2024-11-22

Software

Development Status
Active