<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</abstract>

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.

Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach

Journal of Landscape Ecology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The land use and land cover (LULC) characteristics of Ghaziabad have experienced dynamic changes because of the city’s ongoing industrialization and...

Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach

Publicado en línea: 09 jun 2023

Páginas: 1 - 18

Recibido: 28 ago 2022

Aceptado: 20 oct 2022

DOI: https://doi.org/10.2478/jlecol-2023-0001

Palabras clave
Land use land cover, Land Surface Temperature, spatial autocorrelation, Ghaziabad

© 2023 Diksha et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Spatiotemporal Characterization Of Land Surface Temperature In Relation Landuse/Cover: A Spatial Autocorrelation Approach

Publicado en línea: 09 jun 2023

Páginas: 1 - 18

Recibido: 28 ago 2022

Aceptado: 20 oct 2022

DOI: https://doi.org/10.2478/jlecol-2023-0001

Palabras claveLand use land cover, Land Surface Temperature, spatial autocorrelation, Ghaziabad

© 2023 Diksha et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Palabras clave
Land use land cover, Land Surface Temperature, spatial autocorrelation, Ghaziabad