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

被引：1
|
作者：
Sameh, Sara [1 ,2 ]
Zarzoura, Fawzi H. [2 ]
El-Mewafi, Mahmoud [2 ]
机构：
[1] Badr Univ Cairo BUC, Fac Engn & Technol, Cairo, Egypt
[2] Mansoura Univ, Fac Engn, Publ Works Engn Dept, Mansoura, Egypt
来源：
JOURNAL OF SPATIAL SCIENCE | 2024年 / 69卷 / 02期
关键词：
Land Surface Temperature; Urban Heat Island; land use land cover; LULC indices; CA-ANN algorithm; SURFACE TEMPERATURE; NDVI;
D O I：
10.1080/14498596.2023.2257619
中图分类号：
P9 [自然地理学];
学科分类号：
0705 ; 070501 ;
摘要：
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.
引用
收藏
页码：551 / 572
页数：22
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