Accurate land use and land cover (LULC) is crucial for sustainable urban planning and for
many scientific researches. However, the demand for accurate LULC maps is increasing; it …

Biodiversity is declining at an unprecedented rate, impacting ecosystem services necessary
to ensure food, water, and human health and well-being. Understanding the distribution of …

This is a systematic literature review of the application of machine learning (ML) algorithms
in geosciences, with a focus on environmental monitoring applications. ML algorithms, with …

Land use land cover change (LULC) significantly impacts urban sustainability, urban
planning, climate change, natural resource management, and biodiversity. The Chattogram …

Land Use and Land Cover (LULC) classification using remote sensing data is a challenging
problem that has evolved with the update and launch of new satellites in orbit. As new …

Analyzing alterations in land use/land cover is crucial for water Scientists, planners, and
decision-makers in watershed management. This examination enables the development of …

This review explores the comparative utility of machine learning (ML) and deep learning
(DL) in land system science (LSS) classification tasks. Through a comprehensive …

Mangrove forests, being high-yielding ecosystems, often dominate the intertidal sites along
equatorial and subtropical coasts. Despite the known significance of mangroves to the …

Savanna ecosystems across the globe have experienced substantial changes in their
vegetation composition. These changes can be attributed to three main processes:(1) …

Floods cause substantial losses to life and property, especially in flood-prone regions like
northwestern Bangladesh. Timely and precise evaluation of flood impacts is critical for …