scholarly journals Monitoring of Spatiotemporal Change of Green Spaces in Relation to the Land Surface Temperature: A Case Study of Belgrade, Serbia

2021 ◽  
Vol 13 (19) ◽  
pp. 3846
Author(s):  
Milena Marković ◽  
Jasmin Cheema ◽  
Anica Teofilović ◽  
Slavica Čepić ◽  
Zorica Popović ◽  
...  
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Indices ◽  
Green Spaces ◽  
Spatiotemporal Changes ◽  
Bare Land ◽  
Spectral Vegetation Indices

Understanding the relationship between land use and land cover and thermal environment has recently become an emerging issue for urban planners and policy makers. We chose Belgrade, as a case study, to present a cost- and time-effective framework for monitoring spatiotemporal changes of green spaces in relation to the land surface temperature (LST). Time series analysis was performed using Landsat 5 TM and Landsat 8 OLI/TIRS imagery from 1991 to 2019 with an approximate 5-year interval (18 images in total). Spectral vegetation indices and supervised land cover classifications were used to examine changes of green spaces. The results showed a fluctuating trend of the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI). The highest values were recorded in 2019, indicating vegetation recovery in the last decade. A significant positive correlation was determined between the spectral vegetation indices and the amount of precipitation during growing season. The land cover classification showed that the share of vegetated and bare land decreased by 11.74% during the study period. The most intensive conversion of green and bare land into built-up land cover occurred in the first decade (1991–2000). To assess spatiotemporal changes in the LST, Landsat Collection 2 Surface Temperature products were used. We found a negative correlation between change in the spectral vegetation indices and change in the LST. This indicates that the reduction in vegetation was associated with an increase in the LST. The municipalities that were the most affected in each decade were also identified with our framework. The findings of this study are of great relevance for actions targeting an improvement in urban thermal comfort and climate resilience.

scholarly journals THE LAND SURFACE TEMPERATURE IMPACT TO LAND COVER TYPES

2016 ◽  
Vol XLI-B3 ◽  
pp. 871-876 ◽  
Author(s):  
I. Ibrahim ◽  
A. Abu Samah ◽  
R. Fauzi ◽  
N. M. Noor
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Temperature Variation ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Bodies ◽  
Land Cover Types ◽  
Tukey Test ◽  
Bare Land ◽  
Post Hoc

Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R<sup>2</sup> = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

scholarly journals Effect of land cover composition and building configuration on land surface temperature in an urban-sprawl city, case study in Bangkok Metropolitan Area, Thailand

Heliyon ◽  
2020 ◽  
Vol 6 (8) ◽  
pp. e04485
Author(s):  
Tratrin Adulkongkaew ◽  
Tunlawit Satapanajaru ◽  
Sujittra Charoenhirunyingyos ◽  
Wichitra Singhirunnusorn
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Metropolitan Area ◽  
Urban Sprawl ◽  
Land Surface

scholarly journals Impact of land cover change on land surface temperature over Greater Beirut Area – Lebanon

2021 ◽  
Vol 2 (1) ◽  
pp. 14-27
Author(s):  
Ali Khyami
Keyword(s):  
Remote Sensing ◽  
Twentieth Century ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Cover Change ◽  
Land Surface Temperature ◽  
Urban Growth ◽  
Land Surface ◽  
Bare Land ◽  
The City

Remote sensing (RS) technology has been used together with geographic information systems (GIS) to determine the LC types, retrieve LST, and analyze their relationships. The term Greater Beirut Area (GBA) is used to refer to the city of Beirut and its suburbs which witnessed rapid urban growth, after the end of the civil war, in the last decade of the twentieth century, due to the increase in the number of its inhabitants, and the prosperity and development of sectors such as; industrial, trade, tourism, and construction. These factors led to a wide change in the land cover (LC) types and increased land surface temperature LST. The results showed an increase in built-up areas by 29.1%, and agricultural lands by 6%, while bare land, forests, and seawater decreased by 28.5%, 4.9%, and 1.9%, respectively. These changes caused large differences in the LST between built-up areas and other LC types. The highest LST recorded was in built-up areas (33.03°C in 1985, and 34.01°C in 2020), followed by bare lands (32.61 °C in 1985 and 33.49°C in 2020), cropland (31.23°C in 1985 and 32.17°C in 2020), forest (30.08°C in 1985 and 30.47°C in 2020), and water (24.97°C in 1985 and 28.15°C in 2020). Consequently, converting different LC types into built-up areas led to increases in LST and changed microclimate.

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