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Spatiotemporal analysis of Urban Heat Island and land use land cover changes using Landsat images and CA-ANN machine learning techniques: a case study of Dakahlia government, Egypt.
- Source :
-
Journal of Spatial Science . May2024, Vol. 69 Issue 2, p551-572. 22p. - Publication Year :
- 2024
-
Abstract
- This study explores the relationship between Land Use Land Cover (LULC), Land Surface Temperature (LST), and Urban Heat Island (UHI) in Dakahlia Government using Landsat 8 images from 2014 to 2020. Support Vector Machine (SVM) and Mono-Window Algorithm were used to generate LULC and estimate LST. Results reveal an increase in built-up areas, rising LST, and variable UHI thresholds. The study highlights the impact of COVID-19 on LST in 2020. Positive correlations between LST and Normalized difference build-up index (NDBI) and negative correlations with Normalized difference vegetation index (NDVI) were observed. Projections for 2030 suggest an increase in high-temperature areas. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14498596
- Volume :
- 69
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Journal of Spatial Science
- Publication Type :
- Academic Journal
- Accession number :
- 178133910
- Full Text :
- https://doi.org/10.1080/14498596.2023.2257619