Object Classification in Remote Sensing Imagery holds paramount importance for extracting
meaningful insights from complex aerial scenes. Conventional methods encounter …

The Earth's history is documented in human civilizations, soil layers, river movement, and
quiet sediments throughout millennia. This investigation explores the significant legacy of …

Drought is the most destructive phenomenon that distresses the terrestrial carbon cycle
balance and crop production. The variation in evapotranspiration (ET) and gross primary …

Accurate assessment of water resources at the watershed level is crucial for effective
integrated watershed management. While semi-distributed/distributed models require …

This investigation aimed to scrutinize the level of phthalate esters (PEs) in the landfill
leachate of a coastal city in the north of the Persian Gulf and the sensitive ecosystem (soil …

This research utilized remote sensing (RS) technology to analyze and monitor land use land
cover (LULC) and climate change. This work mainly involves three components:(i) …

Accurate prediction of resilient modulus (MR) in compacted subgrade soil is crucial for
planning secure and environmentally friendly flexible pavement systems. This research …

Cluster analysis can be used to organize samples and generate ideas regarding the
multivariate geochemistry of given dataset. Traditional clustering techniques have the …

The accurate detection and monitoring of supraglacial lakes in high mountainous regions
are crucial for understanding their dynamic nature and implications for environmental …

This article presents an innovative artificial intelligence based multi-expression
programming approach to predict the seismic capacity of reinforced concrete rectangular …