Assessment of Cloudburst and Landslide in East Siang District, Arunachal Pradesh: Combining GIS and Remote Sensing

Authors

Yumi Nyori

Department of Chemistry, Jawaharlal Nehru College, Pasighat 791 103 (Arunachal Pradesh)

Kani Burang

Department of Geography, Jawaharlal Nehru College, Pasighat 791 103 (Arunachal Pradesh)

Yab Rajiv Camder

Department of Commerce, Arunachal Pradesh University, Hill Top, Pasighat 791 103 (Arunachal Pradesh)

Article Information

DOI: 10.47772/IJRISS.2025.91200281

Subject Category: geography

Volume/Issue: 9/12 | Page No: 3636-3641

Publication Timeline

Submitted: 2025-12-25

Accepted: 2025-12-30

Published: 2026-01-15

Abstract

The development of civilisations is part of human evolution, but it comes at the cost of nature's destruction. Unsustainable human development results in long-term human destruction itself. This paradox underscores the need to implement a sustainable approach that balances human progress with environmental preservation. Due to climate change, many activities in nature become extreme, which directly and indirectly impacts human lives. Cloudbursts and landslides are two calamities that attract researchers' attention. Cloudburst and landslide are interrelated with precipitation. Most of these incidents remain undocumented. The downstream ecosystems of the affected area witness loss of life and property. The Eastern Himalayas are prone to heavy rains, especially cloudbursts, which can cause rapid slope failures and landslides in steep hilly terrain. Recently, that region has faced many calamities that cost human lives and property. This study uses remote sensing and GIS tools to analyse the incidence, spatial distribution, and risk assessment of landslides triggered by cloudbursts in East Siang District, Arunachal Pradesh. Our study area comes in the lower Siwalik range of the Himalayas. The study uses satellite images, Digital Elevation Model (DEM) data and rainfall data. It was found that some parts of the study area are at risk of landslides and cloudbursts. The findings promote improved planning for catastrophe risk reduction in remote areas of the country.

Keywords

remote sensing, East Siang, Himalaya, cloudburst, landslide

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