The operational role of remote sensing in assessing and predicting land use/land cover and seasonal land surface temperature using machine learning algorithms in Rajshahi, Bangladesh

2021 ◽  
Author(s):  
Abdulla - Al Kafy ◽  
Abdullah-Al-Faisal ◽  
Abdullah Al Rakib ◽  
Kaniz Shaleha Akter ◽  
Zullyadini A. Rahaman ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Machine Learning Algorithms ◽  
Land Use Land Cover

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
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spectral Radiance ◽  
Land Use Land Cover ◽  
The Impact ◽  
The City

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.

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