Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach
The land use and land cover (LULC) characteristics of Ghaziabad have experienced dynamic changes because of the city’s ongoing industrialization and urbanisation processes. These shifts can be directly attributed to human actions. These shifts can be directly attributed to human actions. Thermal var...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Sciendo
2023-05-01
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| Series: | Journal of Landscape Ecology |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/jlecol-2023-0001 |
| _version_ | 1797806261804204032 |
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| author | Diksha Kumari Maya Kumari Rina |
| author_facet | Diksha Kumari Maya Kumari Rina |
| author_sort | Diksha |
| collection | DOAJ |
| description | The land use and land cover (LULC) characteristics of Ghaziabad have experienced dynamic changes because of the city’s ongoing industrialization and urbanisation processes. These shifts can be directly attributed to human actions. These shifts can be directly attributed to human actions. Thermal variation in the study area necessitates LULC analysis. Landsat and Sentinel satellite data for 2011 and 2021 were used to map LULC, estimate land surface temperature (LST) and analysis spatial autocorrelation among the variables using ArcGIS software and the Google Earth Engine (GEE) cloud platform. A sharp descent is observed in the cropland while built-up area has increased during the study period. With the increase in the built-up surface in the area, the ambient temperatures have also increased from 18.70 °C in 2011 to 21.81 °C in 2021 leading to urban heat island effect. At all spatial scales, spatial autocorrelation is a characteristic property of most ecological parameters. The spatial clustering of LST in an ecosystem can play a crucial role in determining the dynamics of LULC.The Moran’s, I show that there is a considerable level of spatial autocorrelation in the values of LST and highly clustered pattern for both the years. Monitoring and understanding the surface thermal environment is crucial to discerning the causes of climate change. |
| first_indexed | 2024-03-13T06:04:40Z |
| format | Article |
| id | doaj.art-cc1c2e918f154e769dfa192d6170043e |
| institution | Directory Open Access Journal |
| issn | 1805-4196 |
| language | English |
| last_indexed | 2024-03-13T06:04:40Z |
| publishDate | 2023-05-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Journal of Landscape Ecology |
| spelling | doaj.art-cc1c2e918f154e769dfa192d6170043e2023-06-12T06:32:58ZengSciendoJournal of Landscape Ecology1805-41962023-05-0116111810.2478/jlecol-2023-0001Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation ApproachDiksha0Kumari Maya1Kumari Rina21Amity School of Natural Resources & Sustainable Development, Amity University Uttar Pradesh, Noida, Sector 125. India1Amity School of Natural Resources & Sustainable Development, Amity University Uttar Pradesh, Noida, Sector 125. India2School of Environment and Sustainable Development, Central University of Gujarat, Sector 30, Gandhinagar, IndiaThe land use and land cover (LULC) characteristics of Ghaziabad have experienced dynamic changes because of the city’s ongoing industrialization and urbanisation processes. These shifts can be directly attributed to human actions. These shifts can be directly attributed to human actions. Thermal variation in the study area necessitates LULC analysis. Landsat and Sentinel satellite data for 2011 and 2021 were used to map LULC, estimate land surface temperature (LST) and analysis spatial autocorrelation among the variables using ArcGIS software and the Google Earth Engine (GEE) cloud platform. A sharp descent is observed in the cropland while built-up area has increased during the study period. With the increase in the built-up surface in the area, the ambient temperatures have also increased from 18.70 °C in 2011 to 21.81 °C in 2021 leading to urban heat island effect. At all spatial scales, spatial autocorrelation is a characteristic property of most ecological parameters. The spatial clustering of LST in an ecosystem can play a crucial role in determining the dynamics of LULC.The Moran’s, I show that there is a considerable level of spatial autocorrelation in the values of LST and highly clustered pattern for both the years. Monitoring and understanding the surface thermal environment is crucial to discerning the causes of climate change.https://doi.org/10.2478/jlecol-2023-0001land use land coverland surface temperaturespatial autocorrelationghaziabad |
| spellingShingle | Diksha Kumari Maya Kumari Rina Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach Journal of Landscape Ecology land use land cover land surface temperature spatial autocorrelation ghaziabad |
| title | Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach |
| title_full | Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach |
| title_fullStr | Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach |
| title_full_unstemmed | Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach |
| title_short | Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach |
| title_sort | spatiotemporal characterization of land surface temperature in relation landuse cover a spatial autocorrelation approach |
| topic | land use land cover land surface temperature spatial autocorrelation ghaziabad |
| url | https://doi.org/10.2478/jlecol-2023-0001 |
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