Accuracy of pixel-based classification: application of different algorithms to landscapes of Western Iran.

Scenarios for monitoring land cover on a large scale, involving large volumes of data, are becoming more prevalent in remote sensing applications. The accuracy of algorithms is important for environmental monitoring and assessments. Because they performed equally well throughout the various research regions and required little human involvement during the categorization process, they appear to be resilient and accurate for automated, big area change monitoring.

The monetary facilities payment for ecosystem services as an approach to restore the Degraded Urmia Lake in Iran.

This study analyzed the potential use of Payment for Ecosystem Services (PES) as a strategy for improving water supply management. This study focused on the Siminehroud Sub-basin due to its high importance to the Basin of Urmia Lake (UL). Siminehroud is the second provider of water (by volume) to Urmia Lake.

Urban morphology detection and it's linking with land surface temperature: A case study for Tehran Metropolis, Iran.

Expansion of urban areas and alteration of natural land cover exacerbate the local climate change. To find out the effect of land cover changes on the local climate, in this study, the Local Climate Zone (LCZ) concept was utilized to detect urban morphology in Tehran Metropolis. LCZ and Land Surface Temperature (LST) can be identified and classified based on available remote sensing products.

Transboundary Basins Need More Attention: Anthropogenic Impacts on Land Cover Changes in Aras River Basin, Monitoring and Prediction.

Changes in land cover (LC) can alter the basin hydrology by affecting the evaporation, infiltration, and surface and subsurface flow processes, and ultimately affect river water quantity and quality. This study aimed to monitor and predict the LC composition of a major, transboundary basin contributing to the Caspian Sea, the Aras River Basin (ARB). To this end, four LC maps of ARB corresponding to the years 1984, 2000, 2010, and 2017 were generated using Landsat satellite imagery from Armenia and the Nakhchivan Autonomous Republic.