Summary The Semi-Automatic Classification Plugin is a Python plugin for the software QGIS
(QGIS Development Team, 2021) developed with the overall objective to facilitate land cover …

This study proposed an integrated approach to generating a forest fire risk map. It used
geographic information system–based multiple criteria decision analysis (GIS-MCDA) with …

A methodology to estimate the extent of areas affected by forest fires, as well as the burn
severity levels using Sentinel 2 images (10 and 20 m) is proposed and applied to the fires …

Sentinel‐2 imagery can identify forest and land fires in underground parts, surface fires, and
crown fires. The dNBR and RBR spectral indices on Sentinel‐2 images proved accurate in …

This study investigated forest fires in the Mediterranean of Türkiye between July 28, 2021,
and August 11, 2021. Burn severity maps were produced with the difference normalised …

Recent large wildfires have caused serious environmental and social impacts in different
areas of the world, such as Portugal, Greece and Australia. Sociodemographic changes in …

Forest fires threaten the population's health, biomass, and biodiversity, intensifying the
desertification processes and causing temporary damage to conservation areas. Remote …

Land cover (LC) maps are crucial to environmental modeling and define sustainable
management and planning policies. The development of a land cover mapping continuous …

Wildfire is an environmental hazard that has both local and global effects, causing economic
losses and various severe environmental problems. Due to the adverse effects of climate …

Change detection from multi-temporal remote sensing images is an effective way to identify
the burned areas after forest fires. However, the complex image scenario and the similar …