Multivariable Spatial Analysis of Landslide Susceptibility in the Alto Huallaga Basin Using Satellite Data and Modeling in GEE (#345)

Authors

Cernades Palomino, Diego Alonso

Meza Caysahuana, Oscar Antonio

Carmona Arteaga, Abel

Abstract

In the Peruvian context, landslides represent a persistent threat, especially in the Andean regions where the combination of steep slopes, intense rainfall, and unregulated human activity increases terrain vulnerability. Every year, these events cause severe impacts on infrastructure, communities, and transportation networks, resulting in significant human and economic losses. The Alto Huallaga basin is among the most affected areas due to its geographic conditions and the expansion of extractive activities, which exacerbate landslide risks along critical roads. However, there remains a notable lack of systematized technical information from the government regarding the factors triggering these events. In response, this study proposes a methodology based on multivariable spatial analysis, integrating key variables such as slope, precipitation (CHIRPS), and vegetation cover (NDVI). A JavaScript-based script was implemented on the Google Earth Engine platform to temporally monitor and analyze these variables, enabling a comprehensive assessment of landslide susceptibility. The results provide valuable inputs for civil engineering planning and territorial management in the basin, contributing to a safer and more sustainable approach to geohazard risk reduction.