Journal
ENVIRONMENTAL MONITORING AND ASSESSMENT
Volume 194, Issue 6, Pages -Publisher
SPRINGER
DOI: 10.1007/s10661-022-10072-1
Keywords
GIS; Image classification; Land cover changes; Land surface temperature; Remote sensing; Vegetation
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The study found dramatic land use/land cover changes in the Mardan and Charsadda districts of KP, Pakistan from 1990 to 2019, resulting in a decrease in vegetation cover, an increase in barren land and built-up areas, and significant impact on land surface temperature. Specifically, the temperature increase in vegetation and barren land was much higher than in built-up areas.
Land use/land cover (LULC) changes due to urban growth on the regional scale affect land surface temperature (LST). The present study aims to assess the LULC changes and their impact on LST over Mardan and Charsadda districts of Khyber Pakhtunkhwa (KP), Pakistan, in the period from 1990 to 2019. Landsat satellite (TM& ETM +) datasets in the period from 1990 to 2010 and Sentinel-2 images from 2016 to 2019 were used in this study. All the datasets were pre-processed and the LULC types were classified by maximum likelihood classification algorithm. The vegetation degradation was computed from normalized difference vegetation index (NDVI), and the LST was derived based on the LULC changes. The results showed that the overall accuracy of LULC classification was 87.84%. Dramatic LULC changes were observed during the last three decades, where the vegetation degradation area was decreased from 1307.8 (59.27%) to 1147.6 km(2) (52.1%) and the barren land area increased from 816.6 (37.07%) to 961.4 km(2) (42.64%). Similarly, the built-up area has also increased from 57.2 (2.5%) to 104.3 km(2) (4.73%) in the years 1990 and 2019, respectively. These variations in LULC types have significantly influenced the LST from 1990 to 2019; specifically, the LST of built-up area, barren land, and vegetation cover increased from 20.1 to 32.1 degrees C, 21.5 to 35.5 degrees C, and 17.1 to 28.2 degrees C, respectively. The regression line plotted defines that the LST has a negative correlation with NDVI and a positive correlation with normalized difference of built-up index (NDBI). In particular, the vegetation and land covers dramatically transformed to barren land and/or to urban development over the study area in the period from 1990 to2019, which has severely affected the LST and the natural resources of the study area. Therefore, our study will be very helpful for managing the rapid environmental changes and urban planning.
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