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Surface Urban Heat Islands Dynamics in Response to LULC and Vegetation across South Asia (2000–2019)
- Source :
- Remote Sensing, Volume 13, Issue 16, Pages: 3177, Remote Sensing, Vol 13, Iss 3177, p 3177 (2021)
- Publication Year :
- 2021
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2021.
-
Abstract
- Urbanization is an increasing phenomenon around the world, causing many adverse effects in urban areas. Urban heat island is are of the most well-known phenomena. In the present study, surface urban heat islands (SUHI) were studied for seven megacities of the South Asian countries from 2000–2019. The urban thermal environment and relationship between land surface temperature (LST), land use landcover (LULC) and vegetation were examined. The connection was explored with remote-sensing indices such as urban thermal field variance (UTFVI), surface urban heat island intensity (SUHII) and normal difference vegetation index (NDVI). LULC maps are classified using a CART machine learning classifier, and an accuracy table was generated. The LULC change matrix shows that the vegetated areas of all the cities decreased with an increase in the urban areas during the 20 years. The average LST in the rural areas is increasing compared to the urban core, and the difference is in the range of 1–2 (°C). The SUHII linear trend is increasing in Delhi, Karachi, Kathmandu, and Thimphu, while decreasing in Colombo, Dhaka, and Kabul from 2000–2019. UTFVI has shown the poor ecological conditions in all urban buffers due to high LST and urban infrastructures. In addition, a strong negative correlation between LST and NDVI can be seen in a range of −0.1 to −0.6.
- Subjects :
- Land use
Science
surface urban heat island
normalized difference vegetation index
land use land cover
land surface temperature
urbanization
Vegetation
Normalized Difference Vegetation Index
Geography
Megacity
Urbanization
General Earth and Planetary Sciences
Table (landform)
Physical geography
Urban heat island
Rural area
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....cb999900ae369c000e8621347c49db29
- Full Text :
- https://doi.org/10.3390/rs13163177