Evaluation of Wildfire Occurrences in Pakistan with Global Gridded Soil Properties Derived from Remotely Sensed Data

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 21; p. 5503
• Main Authors: Rafaqat, Warda, Iqbal, Mansoor, Kanwal, Rida, Weiguo, Song
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2022
• Subjects: Air pollution; Annual cycles; Annual variations; Atmospheric models; Bulk density; Climate change; Correlation; Elevation; fire count; Fire hazards; Forest & brush fires; fuel; Global warming; Learning algorithms; Machine learning; Monitoring; Monitoring methods; Multivariate analysis; Precipitation; Rain; Regression analysis; Regression models; Remote sensing; Satellite observation; satellite remote sensing; Soil density; Soil properties; Soils; Taxonomy; Temporal variations; Terrestrial ecosystems; Topography; Vegetation; Wildfires; Pakistan

Wildfires are predicted to occur more frequently and intensely as a result of global warming, posing a greater threat to human society, terrestrial ecosystems, and the atmosphere. Most existing methods for monitoring wildfire occurrences are based either on static topographical information or weathe...