scholarly journals Urbanization and Its Impacts on Land Surface Temperature in Colombo Metropolitan Area, Sri Lanka, from 1988 to 2016

2019 ◽  
Vol 11 (8) ◽  
pp. 957 ◽  
Author(s):  
H.P.U. Fonseka ◽  
Hongsheng Zhang ◽  
Ying Sun ◽  
Hua Su ◽  
Hui Lin ◽  
...  

Urbanization has become one of the most important human activities modifying the Earth’s land surfaces; and its impacts on tropical and subtropical cities (e.g., in South/Southeast Asia) are not fully understood. Colombo; the capital of Sri Lanka; has been urbanized for about 2000 years; due to its strategic position on the east–west sea trade routes. This study aims to investigate the characteristics of urban expansion and its impacts on land surface temperature in Colombo from 1988 to 2016; using a time-series of Landsat images. Urban land cover changes (ULCC) were derived from time-series satellite images with the assistance of machine learning methods. Urban density was selected as a measure of urbanization; derived from both the multi-buffer ring method and a gravity model; which were comparatively adopted to evaluate the impacts of ULCC on the changes in land surface temperature (LST) over the study period. The experimental results indicate that: (1) the urban land cover classification during the study period was conducted with satisfactory accuracy; with more than 80% for the overall accuracy and over 0.73 for the Kappa coefficient; (2) the Colombo Metropolitan Area exhibits a diffusion pattern of urban growth; especially along the west coastal line; from both the multi-buffer ring approach and the gravity model; (3) urban density was identified as having a positive relationship with LST through time; (4) there was a noticeable increase in the mean LST; of 5.24 °C for water surfaces; 5.92 °C for vegetation; 8.62 °C for bare land; and 8.94 °C for urban areas. The results provide a scientific reference for policy makers and urban planners working towards a healthy and sustainable Colombo Metropolitan Area.

Heliyon ◽  
2020 ◽  
Vol 6 (8) ◽  
pp. e04485
Author(s):  
Tratrin Adulkongkaew ◽  
Tunlawit Satapanajaru ◽  
Sujittra Charoenhirunyingyos ◽  
Wichitra Singhirunnusorn

2019 ◽  
Vol 51 (3) ◽  
pp. 357
Author(s):  
Hasti Widyasamratri ◽  
Kazuyoshi Souma ◽  
Tadashi Suetsugi

This research aim to investigate the urban thermal environment profile and land cover classification  in the Jakarta Metropolitan Area (JMA) in 1989 and 2013. Thermal environment conducted by installing fix point ground measurement of air temperature and land surface temperature. The land cover classification was carried out  by using Landsat TM 5 and Landsat 7 ETM+ data sets. The diurnal variation of air temperature shows that Urban Heat Island (UHI) was occurring in urban and suburban JMA, which can be seen the slower cooling period in the urban area than suburban areas. Positive correlation between air temperature (Ta) and land surface temperature (Ts) on the brush (r2 = 0.78) and the asphalt surface (r2= 0.88) is clearly shown during the study. The rapid urbanization was detected during 1989 to 2013 where the urban sprawl is spread over to the whole area of JMA. Urban built up is the dominant of high increase due to years, while vegetation is decreasing.    


2020 ◽  
Vol 6 (1) ◽  
pp. 1787738 ◽  
Author(s):  
Caleb Mensah ◽  
Julia Atayi ◽  
Amos T. Kabo-Bah ◽  
Marian Švik ◽  
Daniel Acheampong ◽  
...  

2021 ◽  
Vol 10 (2) ◽  
pp. 76
Author(s):  
Erika Betzabeth Palafox-Juárez ◽  
Jorge Omar López-Martínez ◽  
José Luis Hernández-Stefanoni ◽  
Héctor Hernández-Nuñez

Climate change has severe consequences on ecosystem processes, as well as on people’s quality of life. It has been suggested that the loss of vegetation cover increases the land surface temperature (LST) due to modifications in biogeochemical patterns, generating a phenomenon known as “urban heat island” (UHI). The aim of this work was to analyze the effects of urban land-cover changes on the spatiotemporal variation of surface temperature in the tropical city of Mérida, Mexico. To find these effects we used both detected land-cover changes as well as variations of the Normalized Difference Vegetation Index (NDVI). Mérida is ranked worldwide as one of the best cities to live due to its quality of life. Data from satellite images of Landsat were analyzed to calculate land use change (LUC), LST, and NDVI. LST increased ca. 4 °C in the dry season and 3 °C in the wet season because of the LUC. In addition, a positive relationship between the LST and the NDVI was observed mainly in the dry season. The results confirm an increase in the LST as a consequence of the loss of vegetation cover, which favors the urban heat island phenomenon.


2021 ◽  
Vol 13 (17) ◽  
pp. 3473
Author(s):  
Philipp Reiners ◽  
Sarah Asam ◽  
Corinne Frey ◽  
Stefanie Holzwarth ◽  
Martin Bachmann ◽  
...  

Land Surface Temperature (LST) is an important parameter for tracing the impact of changing climatic conditions on our environment. Describing the interface between long- and shortwave radiation fluxes, as well as between turbulent heat fluxes and the ground heat flux, LST plays a crucial role in the global heat balance. Satellite-derived LST is an indispensable tool for monitoring these changes consistently over large areas and for long time periods. Data from the AVHRR (Advanced Very High-Resolution Radiometer) sensors have been available since the early 1980s. In the TIMELINE project, LST is derived for the entire operating period of AVHRR sensors over Europe at a 1 km spatial resolution. In this study, we present the validation results for the TIMELINE AVHRR daytime LST. The validation approach consists of an assessment of the temporal consistency of the AVHRR LST time series, an inter-comparison between AVHRR LST and in situ LST, and a comparison of the AVHRR LST product with concurrent MODIS (Moderate Resolution Imaging Spectroradiometer) LST. The results indicate the successful derivation of stable LST time series from multi-decadal AVHRR data. The validation results were investigated regarding different LST, TCWV and VA, as well as land cover classes. The comparisons between the TIMELINE LST product and the reference datasets show seasonal and land cover-related patterns. The LST level was found to be the most determinative factor of the error. On average, an absolute deviation of the AVHRR LST by 1.83 K from in situ LST, as well as a difference of 2.34 K from the MODIS product, was observed.


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