The data for "Expanding the Global Martian Landslide Inventory with Multi-modal DINOv2 Feature Fusion and SVM Classification"

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Yunwan Tao, Lu Pan, Zongfang Liu
DOI: 10.5281/zenodo.19158843
Cited by: 1

Abstract

This archive includes: 2,263 Martian landslide features used for training and testing, based on the inventory of Crosta et al. (2018), provided as point features. 2,263 non-landslide features used for training and testing, generated by random clipping in ArcGIS Pro and provided as point features. 25 newly mapped landslides, identified by Mars-DiSVM and provided as point features. A trained SVM classifier for potential users. Example code for applying the Mars-DiSVM framework. requirements.txt README.md

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 January 2026
Language
EN
Document type
Dataset