Understanding the relationship between land use/land cover changes and air quality: A GIS-based fuzzy inference system approach

• Published in: Environmental monitoring and assessment Vol. 196; no. 12; p. 1160
• Main Authors: Zaid, Mohd, Basu, D.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2024; Springer Nature B.V
• Subjects: air; air pollutants; Air Pollutants - analysis; Air pollution; Air Pollution - statistics & numerical data; Air pollution control; Air pollution effects; Air quality; Air quality management; Atmospheric Protection/Air Quality Control/Air Pollution; Cities; Correlation analysis; Earth and Environmental Science; Ecology; Ecotoxicology; Environment; Environmental Management; Environmental Monitoring - methods; Fuzzy Logic; Geographic Information Systems; Geographical information systems; human health; India; Inference; Land cover; Land use; land use and land cover maps; Land use management; Monitoring/Environmental Analysis; Outdoor air quality; Particulate emissions; Particulate matter; Particulate Matter - analysis; particulates; Plant cover; Pollutants; Quality management; Suspended particulate matter; Temporal variations; Urban planning; Urbanization; Vegetation; Vegetation cover; Vegetation index; India; Air quality; Correlation; Fuzzy inference system (FIS); Hotspot; LULC change

Air pollution is a global issue that demands urgent attention due to its detrimental effects on human health and the environment. Land Use and Land Cover (LULC) change is an essential factor that significantly impacts ambient air quality through alterations in emission sources, vegetation cover, nat...