Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …

Floods are one of the most destructive natural disasters, causing financial and human losses
every year. As a result, reliable Flood Susceptibility Map** (FSM) is required for effective …

The success rate in landslide susceptibility map** efforts increased with the
advancements in machine learning algorithms and the availability of geospatial data with …

In the hilly region of the Western Himalayas, forest fires play a crucial role in forest
destruction and biodiversity loss. Therefore, addressing the problem of forest fires is an …

Gully erosion is a widespread environmental danger, threatening global socio-economic
stability and sustainable development. This study comprehensively applied seven machine …

As a frequent natural disaster, landslides incur significant economic and human losses
worldwide. The main idea of this paper is to propose novel integrative models for landslide …

Geological settings of the Karakoram Highway (KKH) increase the risk of natural disasters,
threatening its regular operations. Predicting landslides along the KKH is challenging due to …

This study examines the use of snow avalanche susceptibility maps (SASMs) to identify
areas prone to avalanches and develop measures to mitigate the risk in the Province of …

Flooding is one of the catastrophic natural hazards worldwide that can easily cause
devastating effects on human life and property. Remote sensing devices are becoming …

Wetland risk assessment is a global concern especially in develo** countries like
Bangladesh. The present study explored the spatiotemporal dynamics of wetlands …