Urban Land Use Land Cover Changes and Their Effect on Land Surface Temperature: Case Study Using Dohuk City in the Kurdistan Region of Iraq
The growth of urban areas has a significant impact on land use by replacing areas of vegetation with residential and commercial areas and their related infrastructure; this escalates the land surface temperature (LST). Rapid urban growth has occurred in Duhok City due to enhanced political and econo...
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description | The growth of urban areas has a significant impact on land use by replacing areas of vegetation with residential and commercial areas and their related infrastructure; this escalates the land surface temperature (LST). Rapid urban growth has occurred in Duhok City due to enhanced political and economic growth during the period of this study. The objective is to investigate the effect of land use changes on LST; this study depends on data from three Landsat images (two Landsat 5-TM and Landsat OLI_TIRS-8) from 1990, 2000 and 2016. Supervised classification was used to compute land use/cover categories, and to generate the land surface temperature (LST) maps the Mono-window algorithm was used. Images were also used to create the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBAI) and normalized difference water index (NDWI) maps. Linear regression analysis was used to generate relationships between LST with NDVI, NDBI, NDBAI and NDWI. The study outcome proves that the changes in land use/cover have a significant role in the escalation of land surface temperatures. The highest temperatures are associated with barren land and built-up areas, ranging from 47°C, 50°C, 56°C while lower temperatures are related to water bodies and forests, ranging from 25°C, 26°C, 29°C respectively, in 1990, 2000 and 2016. This study also proves that NDVI and NDWI correlate negatively with low temperatures while NDBI and NDBAI correlate positively with high temperatures. |
doi_str_mv | 10.3390/cli5010013 |
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Rapid urban growth has occurred in Duhok City due to enhanced political and economic growth during the period of this study. The objective is to investigate the effect of land use changes on LST; this study depends on data from three Landsat images (two Landsat 5-TM and Landsat OLI_TIRS-8) from 1990, 2000 and 2016. Supervised classification was used to compute land use/cover categories, and to generate the land surface temperature (LST) maps the Mono-window algorithm was used. Images were also used to create the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBAI) and normalized difference water index (NDWI) maps. Linear regression analysis was used to generate relationships between LST with NDVI, NDBI, NDBAI and NDWI. The study outcome proves that the changes in land use/cover have a significant role in the escalation of land surface temperatures. The highest temperatures are associated with barren land and built-up areas, ranging from 47°C, 50°C, 56°C while lower temperatures are related to water bodies and forests, ranging from 25°C, 26°C, 29°C respectively, in 1990, 2000 and 2016. 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Rapid urban growth has occurred in Duhok City due to enhanced political and economic growth during the period of this study. The objective is to investigate the effect of land use changes on LST; this study depends on data from three Landsat images (two Landsat 5-TM and Landsat OLI_TIRS-8) from 1990, 2000 and 2016. Supervised classification was used to compute land use/cover categories, and to generate the land surface temperature (LST) maps the Mono-window algorithm was used. Images were also used to create the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBAI) and normalized difference water index (NDWI) maps. Linear regression analysis was used to generate relationships between LST with NDVI, NDBI, NDBAI and NDWI. The study outcome proves that the changes in land use/cover have a significant role in the escalation of land surface temperatures. The highest temperatures are associated with barren land and built-up areas, ranging from 47°C, 50°C, 56°C while lower temperatures are related to water bodies and forests, ranging from 25°C, 26°C, 29°C respectively, in 1990, 2000 and 2016. This study also proves that NDVI and NDWI correlate negatively with low temperatures while NDBI and NDBAI correlate positively with high temperatures.</description><subject>Barren lands</subject><subject>Case studies</subject><subject>Economic development</subject><subject>Economic growth</subject><subject>Environmental impact</subject><subject>Forests</subject><subject>Growth</subject><subject>High temperature</subject><subject>Land cover</subject><subject>Land surface temperature</subject><subject>Land use</subject><subject>Landsat</subject><subject>Landsat satellites</subject><subject>Low temperature</subject><subject>Mathematical models</subject><subject>Normalized difference vegetative index</subject><subject>Regression analysis</subject><subject>Remote sensing</subject><subject>Residential areas</subject><subject>Satellite imagery</subject><subject>Surface temperature</subject><subject>Temperature</subject><subject>Temperature effects</subject><subject>Urban 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surface temperature (LST). Rapid urban growth has occurred in Duhok City due to enhanced political and economic growth during the period of this study. The objective is to investigate the effect of land use changes on LST; this study depends on data from three Landsat images (two Landsat 5-TM and Landsat OLI_TIRS-8) from 1990, 2000 and 2016. Supervised classification was used to compute land use/cover categories, and to generate the land surface temperature (LST) maps the Mono-window algorithm was used. Images were also used to create the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBAI) and normalized difference water index (NDWI) maps. Linear regression analysis was used to generate relationships between LST with NDVI, NDBI, NDBAI and NDWI. The study outcome proves that the changes in land use/cover have a significant role in the escalation of land surface temperatures. The highest temperatures are associated with barren land and built-up areas, ranging from 47°C, 50°C, 56°C while lower temperatures are related to water bodies and forests, ranging from 25°C, 26°C, 29°C respectively, in 1990, 2000 and 2016. This study also proves that NDVI and NDWI correlate negatively with low temperatures while NDBI and NDBAI correlate positively with high temperatures.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/cli5010013</doi><orcidid>https://orcid.org/0000-0001-8772-4404</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Barren lands Case studies Economic development Economic growth Environmental impact Forests Growth High temperature Land cover Land surface temperature Land use Landsat Landsat satellites Low temperature Mathematical models Normalized difference vegetative index Regression analysis Remote sensing Residential areas Satellite imagery Surface temperature Temperature Temperature effects Urban areas Urban development Urban sprawl Vegetation Vegetation changes Vegetation index |
title | Urban Land Use Land Cover Changes and Their Effect on Land Surface Temperature: Case Study Using Dohuk City in the Kurdistan Region of Iraq |
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