scholarly journals Remote Sensing Image-Based Analysis of the Impact of Land Use/Land Cover Changes on Land Surface Temperature

2019 ◽  
Vol 8 (4) ◽  
pp. 1834-1839

This study evaluated the land use/land cover (LULC) changes in Tuguegarao City and analyzed its impact on Land Surface Temperature (LST). It was carried out using Remote Sensing and Geographic Information System (GIS) techniques. Three Landsat TM and ETM+ images data were acquired for the years 1990, 2005 and 2016 from USGS Earth Explorer portal. ArcGIS software was used to determine the area statistics of the different land cover and to make the final LULC map. LST for the study area was taken from the thermal infrared band of the satellite images by converting the image digital number into degrees Kelvin using the LMin and LMax spectral radiance scaling factors. The largest areal change appeared in the built-up area with an increase of 1120.32 ha. However, this study detected higher LST in the crop land, grassland and barren land areas of the city rather than the built-up parts of the city which does not follow many of previous studies. The results of the study can be presented to the Local Government Unit so that they can draft appropriate laws for the betterment of the city specially that rapid urbanization and uncontrolled population growth may have extreme impact on the environment.

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1106
Author(s):  
Auwalu Faisal Koko ◽  
Yue Wu ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed ◽  
...  

Rapid urban expansion and the alteration of global land use/land cover (LULC) patterns have contributed substantially to the modification of urban climate, due to variations in Land Surface Temperature (LST). In this study, the LULC change dynamics of Kano metropolis, Nigeria, were analysed over the last three decades, i.e., 1990–2020, using multispectral satellite data to understand the impact of urbanization on LST in the study area. The Maximum Likelihood classification method and the Mono-window algorithm were utilised in classifying land uses and retrieving LST data. Spectral indices comprising the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) were also computed. A linear regression analysis was employed in order to examine the correlation between land surface temperature and the various spectral indices. The results indicate significant LULC changes and urban expansion of 152.55 sq. km from 1991 to 2020. During the study period, the city’s barren land and water bodies declined by approximately 172.58 sq. km and 26.55 sq. km, respectively, while vegetation increased slightly by 46.58 sq. km. Further analysis showed a negative correlation between NDVI and LST with a Pearson determination coefficient (R2) of 0.6145, 0.5644, 0.5402, and 0.5184 in 1991, 2000, 2010, and 2020 respectively. NDBI correlated positively with LST, having an R2 of 0.4132 in 1991, 0.3965 in 2000, 0.3907 in 2010, and 0.3300 in 2020. The findings of this study provide critical climatic data useful to policy- and decision-makers in optimizing land use and mitigating the impact of urban heat through sustainable urban development.


2019 ◽  
Vol 12 (3) ◽  
pp. 117-140
Author(s):  
Sunil Kumar ◽  
Swagata Ghosh ◽  
Ramesh Singh Hooda ◽  
Sultan Singh

Abstract Land use Land cover have significance in relation to Land, the most vital and fundamental resource pertaining to the urban development. Unprecedented urban growth has a noteworthy impact on natural landscape by converting natural land-cover in Haryana. Hisar, an area recognized for rapid urban growth is less explored in terms of research. The present research has shown a significant change in land use in terms of expansion of built-up area from 3.7 % (1991) to 5.0 % (2001) and 6.2 % (2011) by encroaching into agricultural land. Despite the clear difference between average land surface temperature for built up and non-built up area, grazing land and sandy waste, bare land in the rural surrounding possess higher temperature compared to the city core which contradicts the reported impact of urbanization earlier. Such contrary pertains to sparse vegetation cover leading to reduced evaporative cooling during dry pre-monsoon summer in the rural surrounding. On the other side, green parks and plantation in the city contribute to lower mean temperature because of high rates of evapotranspiration and produce ‘oasis effect’ in the present study area located in semi-arid climatic zone. Regression analysis between temperature and Normalized Difference Vegetation Index, Normalized Difference Built-up Index exhibited a strong negative and positive correlation respectively (Pearson’s r: between -0.79 to -0.87 and between 0.79 to 0.84 respectively). Future land use prediction project an increase (1.3 %) in built-up area from 2011 to 2021. This study recommends urban plantation and prohibition to overgrazing to check the heat effect.


Author(s):  
Simil Amir Siddiqui

Urban heat islands (UHI) are areas with elevated temperatures occurring in cities compared to surrounding rural areas. This study realizes the lack of research regarding the trends of UHIs in desert countries and focuses on Doha. The research includes twelve months of two-time periods; 2000-2019. ArcGIS software was used to compute the land surface temperature (LST) of the city using Landsat images. Land use/land cover (LULC) maps were computed to show how the city has evolved in 19 years. 30 field samples were used to verify the accuracy of the LULC. Results showed UHI in Doha did not display similar pattern to that of cities in subtropical and temperate regions. Higher temperatures were prevalent in out-skirts comprising of barren and built-up areas with high population and no vegetation. Comparatively, the main downtown with artificially planted vegetation and shade from skyscrapers created cooler microclimates. The overall LST of greater Doha has increased by 0.7°C from 2000 to 2019. Furthermore %LULC of built up, vegetation, barren land, marsh land and water body were 29%, 4.5%, 58.6%, 2.8% and 5% in 2000 and 56.5 %, 8.2%, 33.2 %, 0% and 2.1% in 2019 respectively. Overall, there was an increase in built-up and vegetation decrease in water and barren areas and complete loss of marshland. Highest temperatures were recorded for marshland area in year 2000 and barren and built in year 2019. Transect profiles showed positive correlation between NDBI and LST and a negative correlation between NDVI and LST.


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