The abundance and distribution of plastic debris in natural waters is largely unknown due to
limited comprehensive monitoring. Here, optical properties of dry and wet marine-harvested …

This study aims to quantify the landscape spatio-temporal dynamics including Land
Use/Land Cover (LULC) changes occurred in a typical Mediterranean ecosystem of high …

This study proposes the application of a hybrid methodology combining the Best-Worst
Method (BWM) and Additive Ratio Assessment (ARAS) approaches to mineral prospectivity …

Intertidal macroalgal habitats are major components of temperate coastal ecosystems. Their
distribution was studied using field sampling and hyperspectral remote mapping on a rocky …

Recently, deep learning (DL) techniques including Convolutional neural network (CNN),
Recurrent neural network (RNN), and Recurrent-Convolutional neural network (R-CNN) …

Image fusion combines the images of different spectral, spatial, multi-date, as well as
radiometric data to achieve a better quality image for improved classification results …

Classification of tree species provides important data in forest monitoring, sustainable forest
management and planning. The recent developments in Multi Spectral (MS) and Hyper …

The combination of remote sensing techniques and Geographic Information Systems (GIS)
to measure water quality allows researchers to monitor changes in various water quality …

Plastic pollution in the marine environment is a pervasive, global problem that threatens
wildlife and human health. Routine monitoring is required to determine pollution hotspots …

In this study, we investigated the performance of different fusion and classification
techniques for land cover mapping in Hilir Perak, Peninsula Malaysia using RADAR and …