Dataset for Landslide Susceptibility Prediction

Published: 26 September 2023| Version 1 | DOI: 10.17632/jsn8cwb9nz.1
Geetanjali Mahamunkar,


This dataset considers 7 landslide conditioning factors such as Curvature, Slope, Aspect, Elevation, NDVI, Precipitation, and LULC for 100 random locations in Raigad district of Maharashtra, India. These factors were categorized based on their range of values and influence on landslide occurrence, ranging from very high(5), high(4), moderate(3), low(2) to very low(1). Further based on the values of these factors the landslide susceptibility of that location is categorized into low (1), moderate(2) and high(3). Thus this dataset can be used for multiclass classification of landslides using machine learning algorithm.



Machine Learning Algorithm, Landslide, Deep Learning