Land-use and land-cover change (LULCC) are of importance in natural resource
management, environmental modelling and assessment, and agricultural production …

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

Abstract Google Earth Engine (GEE) is presently the most innovative international open-
source platform for the advanced-level analysis of geospatial big data. In this study, we used …

Change detection of natural lake boundaries is one of the important tasks in remote sensing
image interpretation. In an ordinary fully connected network, or CNN, the signal of neurons …

Accurate land use land cover (LULC) classification is vital for the sustainable management
of natural resources and to learn how the landscape is changing due to climate. For …

Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …

This study aimed to provide a systematic overview of the progress made in utilizing remote
sensing for assessing the impacts of land use and land cover (LULC) changes on water …

The increasing urban heat island intensity (UHII) is a matter of concern for the sustainable
urban planning and maintaining urban thermal comfort in the metropolitan cities of …

Land use land cover (LULC) modeling is considered as the best tool to comprehend and
unravel the dynamics of future urban expansion. The present paper provides a …

This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …