Response of soil moisture and vegetation conditions in seasonal variation of land surface temperature and surface urban heat island intensity in sub-tropical semi-arid cities
The cities of arid and semi-arid regions have distinctive landscape patterns and large-scale variations in soil moisture and vegetation cover which causes significant variations in land surface temperature (LST) and surface urban heat island intensity (SUHII) pattern. Therefore, the study aims to an...
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| Veröffentlicht in: | Theoretical and applied climatology 2023-07, Vol.153 (1-2), p.367-395 |
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| creator | Shahfahad Bindajam, Ahmed Ali Naikoo, Mohd Waseem Horo, Juhi Priyanka Mallick, Javed Rihan, Mohd Malcoti, Manisha Dabral Talukdar, Swapan Rahman, Rejaur Rahman, Atiqur |
| description | The cities of arid and semi-arid regions have distinctive landscape patterns and large-scale variations in soil moisture and vegetation cover which causes significant variations in land surface temperature (LST) and surface urban heat island intensity (SUHII) pattern. Therefore, the study aims to analyse the seasonal and spatial variation in LST and SUHII in the eight semi-arid cities of India in response to soil moisture and vegetation conditions. LST was retrieved from the thermal bands of Landsat data and then SUHII was calculated. The global Moran’s I was used to analysis the spatial pattern of SUHII. The result shows that the mean SUHII was higher during spring and summer seasons to a tune of 0.2 to 1.0 °C in comparison to the winter and autumn season. SUHII zones exhibit seasonal variation in coverage, with high and very high zones increasing during spring and summer, while low and very low zones increase during autumn and winter. Furthermore, the highest LST was noticed in outskirt areas of the selected cities. The regression coefficient shows that soil moisture is closely associated with SUHII, while there is a weak association between vegetation condition and SUHII. This indicates that soil moisture has a higher impact on SUHII than vegetation condition in semi-arid environment. Global Moran’s I showed that the SUHII had a clustered distribution pattern across all cities. The outcome of this study may provide useful insight for the urban planners in SUHII mitigation in the selected cities as well as in other semi-arid cities of the world with similar geographical conditions. |
| doi_str_mv | 10.1007/s00704-023-04477-2 |
| format | Article |
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Therefore, the study aims to analyse the seasonal and spatial variation in LST and SUHII in the eight semi-arid cities of India in response to soil moisture and vegetation conditions. LST was retrieved from the thermal bands of Landsat data and then SUHII was calculated. The global Moran’s I was used to analysis the spatial pattern of SUHII. The result shows that the mean SUHII was higher during spring and summer seasons to a tune of 0.2 to 1.0 °C in comparison to the winter and autumn season. SUHII zones exhibit seasonal variation in coverage, with high and very high zones increasing during spring and summer, while low and very low zones increase during autumn and winter. Furthermore, the highest LST was noticed in outskirt areas of the selected cities. The regression coefficient shows that soil moisture is closely associated with SUHII, while there is a weak association between vegetation condition and SUHII. This indicates that soil moisture has a higher impact on SUHII than vegetation condition in semi-arid environment. Global Moran’s I showed that the SUHII had a clustered distribution pattern across all cities. The outcome of this study may provide useful insight for the urban planners in SUHII mitigation in the selected cities as well as in other semi-arid cities of the world with similar geographical conditions.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-023-04477-2</identifier><language>eng</language><publisher>Vienna: Springer Vienna</publisher><subject>Analysis ; Aquatic Pollution ; Arid environments ; Arid regions ; Arid zones ; Atmospheric Protection/Air Quality Control/Air Pollution ; Atmospheric Sciences ; Autumn ; Cities ; Climate science ; Climatology ; Distribution patterns ; Earth and Environmental Science ; Earth Sciences ; Land surface temperature ; Landsat ; Mathematical analysis ; Mitigation ; Moisture effects ; Pattern analysis ; Plant cover ; Regression coefficients ; Remote sensing ; Seasonal variation ; Seasonal variations ; Seasons ; Semi arid areas ; Semi arid environments ; Semiarid environments ; Semiarid zones ; Soil ; Soil conditions ; Soil moisture ; Soil moisture variations ; Soil temperature ; Spatial analysis ; Spatial variations ; Spring ; Spring (season) ; Summer ; Surface temperature ; Urban climatology ; Urban heat islands ; Urban planning ; Vegetation ; Vegetation cover ; Waste Water Technology ; Water Management ; Water Pollution Control ; Winter</subject><ispartof>Theoretical and applied climatology, 2023-07, Vol.153 (1-2), p.367-395</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>COPYRIGHT 2023 Springer</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-f8646d56f53b4070bf1b43d971eb9e8b036428c5c2beb20e7185b851b486915f3</citedby><cites>FETCH-LOGICAL-c392t-f8646d56f53b4070bf1b43d971eb9e8b036428c5c2beb20e7185b851b486915f3</cites><orcidid>0000-0002-2533-8433 ; 0000-0001-5779-9325 ; 0000-0001-6680-9791 ; 0000-0003-3560-7200 ; 0000-0002-6155-3720 ; 0000-0001-5868-1062 ; 0000-0002-9001-5059</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00704-023-04477-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00704-023-04477-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Shahfahad</creatorcontrib><creatorcontrib>Bindajam, Ahmed Ali</creatorcontrib><creatorcontrib>Naikoo, Mohd Waseem</creatorcontrib><creatorcontrib>Horo, Juhi Priyanka</creatorcontrib><creatorcontrib>Mallick, Javed</creatorcontrib><creatorcontrib>Rihan, Mohd</creatorcontrib><creatorcontrib>Malcoti, Manisha Dabral</creatorcontrib><creatorcontrib>Talukdar, Swapan</creatorcontrib><creatorcontrib>Rahman, Rejaur</creatorcontrib><creatorcontrib>Rahman, Atiqur</creatorcontrib><title>Response of soil moisture and vegetation conditions in seasonal variation of land surface temperature and surface urban heat island intensity in sub-tropical semi-arid cities</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>The cities of arid and semi-arid regions have distinctive landscape patterns and large-scale variations in soil moisture and vegetation cover which causes significant variations in land surface temperature (LST) and surface urban heat island intensity (SUHII) pattern. Therefore, the study aims to analyse the seasonal and spatial variation in LST and SUHII in the eight semi-arid cities of India in response to soil moisture and vegetation conditions. LST was retrieved from the thermal bands of Landsat data and then SUHII was calculated. The global Moran’s I was used to analysis the spatial pattern of SUHII. The result shows that the mean SUHII was higher during spring and summer seasons to a tune of 0.2 to 1.0 °C in comparison to the winter and autumn season. SUHII zones exhibit seasonal variation in coverage, with high and very high zones increasing during spring and summer, while low and very low zones increase during autumn and winter. Furthermore, the highest LST was noticed in outskirt areas of the selected cities. The regression coefficient shows that soil moisture is closely associated with SUHII, while there is a weak association between vegetation condition and SUHII. 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The outcome of this study may provide useful insight for the urban planners in SUHII mitigation in the selected cities as well as in other semi-arid cities of the world with similar geographical conditions.</description><subject>Analysis</subject><subject>Aquatic Pollution</subject><subject>Arid environments</subject><subject>Arid regions</subject><subject>Arid zones</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Autumn</subject><subject>Cities</subject><subject>Climate science</subject><subject>Climatology</subject><subject>Distribution patterns</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Land surface temperature</subject><subject>Landsat</subject><subject>Mathematical analysis</subject><subject>Mitigation</subject><subject>Moisture effects</subject><subject>Pattern analysis</subject><subject>Plant cover</subject><subject>Regression 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of soil moisture and vegetation conditions in seasonal variation of land surface temperature and surface urban heat island intensity in sub-tropical semi-arid cities</title><author>Shahfahad ; Bindajam, Ahmed Ali ; Naikoo, Mohd Waseem ; Horo, Juhi Priyanka ; Mallick, Javed ; Rihan, Mohd ; Malcoti, Manisha Dabral ; Talukdar, Swapan ; Rahman, Rejaur ; Rahman, Atiqur</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-f8646d56f53b4070bf1b43d971eb9e8b036428c5c2beb20e7185b851b486915f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Analysis</topic><topic>Aquatic Pollution</topic><topic>Arid environments</topic><topic>Arid regions</topic><topic>Arid zones</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Atmospheric Sciences</topic><topic>Autumn</topic><topic>Cities</topic><topic>Climate 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temperature and surface urban heat island intensity in sub-tropical semi-arid cities</atitle><jtitle>Theoretical and applied climatology</jtitle><stitle>Theor Appl Climatol</stitle><date>2023-07-01</date><risdate>2023</risdate><volume>153</volume><issue>1-2</issue><spage>367</spage><epage>395</epage><pages>367-395</pages><issn>0177-798X</issn><eissn>1434-4483</eissn><abstract>The cities of arid and semi-arid regions have distinctive landscape patterns and large-scale variations in soil moisture and vegetation cover which causes significant variations in land surface temperature (LST) and surface urban heat island intensity (SUHII) pattern. Therefore, the study aims to analyse the seasonal and spatial variation in LST and SUHII in the eight semi-arid cities of India in response to soil moisture and vegetation conditions. LST was retrieved from the thermal bands of Landsat data and then SUHII was calculated. The global Moran’s I was used to analysis the spatial pattern of SUHII. The result shows that the mean SUHII was higher during spring and summer seasons to a tune of 0.2 to 1.0 °C in comparison to the winter and autumn season. SUHII zones exhibit seasonal variation in coverage, with high and very high zones increasing during spring and summer, while low and very low zones increase during autumn and winter. Furthermore, the highest LST was noticed in outskirt areas of the selected cities. The regression coefficient shows that soil moisture is closely associated with SUHII, while there is a weak association between vegetation condition and SUHII. This indicates that soil moisture has a higher impact on SUHII than vegetation condition in semi-arid environment. Global Moran’s I showed that the SUHII had a clustered distribution pattern across all cities. The outcome of this study may provide useful insight for the urban planners in SUHII mitigation in the selected cities as well as in other semi-arid cities of the world with similar geographical conditions.</abstract><cop>Vienna</cop><pub>Springer Vienna</pub><doi>10.1007/s00704-023-04477-2</doi><tpages>29</tpages><orcidid>https://orcid.org/0000-0002-2533-8433</orcidid><orcidid>https://orcid.org/0000-0001-5779-9325</orcidid><orcidid>https://orcid.org/0000-0001-6680-9791</orcidid><orcidid>https://orcid.org/0000-0003-3560-7200</orcidid><orcidid>https://orcid.org/0000-0002-6155-3720</orcidid><orcidid>https://orcid.org/0000-0001-5868-1062</orcidid><orcidid>https://orcid.org/0000-0002-9001-5059</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0177-798X |
| ispartof | Theoretical and applied climatology, 2023-07, Vol.153 (1-2), p.367-395 |
| issn | 0177-798X 1434-4483 |
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| source | SpringerLink Journals |
| subjects | Analysis Aquatic Pollution Arid environments Arid regions Arid zones Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Autumn Cities Climate science Climatology Distribution patterns Earth and Environmental Science Earth Sciences Land surface temperature Landsat Mathematical analysis Mitigation Moisture effects Pattern analysis Plant cover Regression coefficients Remote sensing Seasonal variation Seasonal variations Seasons Semi arid areas Semi arid environments Semiarid environments Semiarid zones Soil Soil conditions Soil moisture Soil moisture variations Soil temperature Spatial analysis Spatial variations Spring Spring (season) Summer Surface temperature Urban climatology Urban heat islands Urban planning Vegetation Vegetation cover Waste Water Technology Water Management Water Pollution Control Winter |
| title | Response of soil moisture and vegetation conditions in seasonal variation of land surface temperature and surface urban heat island intensity in sub-tropical semi-arid cities |
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