Semantic Scholar Open Access 2017 170 sitasi

An Urban Heat Island Study of the Colombo Metropolitan Area, Sri Lanka, Based on Landsat Data (1997-2017)

M. Ranagalage R. Estoque Y. Murayama

Abstrak

One of the major impacts associated with unplanned rapid urban growth is the decrease of urban vegetation, which is often replaced with impervious surfaces such as buildings, parking lots, roads, and pavements. Consequently, as the percentage of impervious surfaces continues to increase at the expense of vegetation cover, surface urban heat island (SUHI) forms and becomes more intense. The Colombo Metropolitan Area (CMA), Sri Lanka, is one of the rapidly urbanizing metropolitan regions in South Asia. In this study, we examined the spatiotemporal variations of land surface temperature (LST) in the CMA in the context of the SUHI phenomenon using Landsat data. More specifically, we examined the relationship of LST with the normalized difference vegetation index (NDVI) and the normalized difference built-up index (NDBI) at three time points (1997, 2007 and 2017). In addition, we also identified environmentally critical areas based on LST and NDVI. We found significant correlations of LST with NDVI (negative) and NDBI (positive) (p < 0.001) across all three time points. Most of the environmentally critical areas are located in the central business district (CBD), near the harbor, across the coastal belt, and along the main transportation network. We recommend that those identified environmentally critical areas be considered in the future urban planning and landscape development of the city. Green spaces can help improve the environmental sustainability of the CMA.

Penulis (3)

M

M. Ranagalage

R

R. Estoque

Y

Y. Murayama

Format Sitasi

Ranagalage, M., Estoque, R., Murayama, Y. (2017). An Urban Heat Island Study of the Colombo Metropolitan Area, Sri Lanka, Based on Landsat Data (1997-2017). https://doi.org/10.3390/IJGI6070189

Akses Cepat

Lihat di Sumber doi.org/10.3390/IJGI6070189
Informasi Jurnal
Tahun Terbit
2017
Bahasa
en
Total Sitasi
170×
Sumber Database
Semantic Scholar
DOI
10.3390/IJGI6070189
Akses
Open Access ✓