Journal of Remote Sensing & GIS

South Asia, a region characterized by hydro-climatic instability, faces an intensifying risk from devastating flooding, aggravated by human-induced climate change and intricate river basin interactions.

Present study analyses the performance of deep leaning algorithm-autoencoder to reduce data dimension as compared to conventional models. Classification accuracies of Sirpur wetland using Sentinel 2A dataset with different inputs have also been studied.

By integrating high-resolution satellite images into pre-existing mapping frameworks, this study tackles the problem of guaranteeing correctness and dependability in geospatial data updates.

Water scarcity is a critical concern in arid and semi-arid regions, with implications for ecological stability, public health, and sustainable resource management.

In recent years, the world has faced many disasters, but the effects of floods have received considerable focus due to their harmful consequences. More than half of the global destruction and damage from floods takes place in Asia, leading to loss of life, infrastructure damage, and community panic.

The urban ecological system is crucial for human survival in cities. Residents receive various services directly or indirectly from the functions of ecosystems, known as ecosystem services.