Identifying spatial attributes of LULC classes affecting urban area LST in districts of India

Ravi Verma; P.K. Garg

doi:10.1117/12.2685083

19 October 2023 Identifying spatial attributes of LULC classes affecting urban area LST in districts of India

Ravi Verma, P.K. Garg

Proceedings Volume 12735, Remote Sensing Technologies and Applications in Urban Environments VIII; 1273505 (2023) https://doi.org/10.1117/12.2685083
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Abstract

Urban Heat Island (UHI) driven effectively by urbanisation can directly affect environment and weather of city. UHI mitigation remains a hot topic for researchers around the world for sustainable urban planning. This study attempts on finding the relationship between spatial attributes of Land Use \ Land Cover (LULC) classes in city and their effect on Land Surface Temperature (LST) over the Built-up patches present inside the 694 districts of different States and Union Territories (UTs) of India. Pan India Decadal LULC by ORNL DAAC for year 2005 and Copernicus Global Land service LULC for year 2015 at 100 m resolution has been taken as classified data for the study. MODIS LST maps at 1km resolution were used to find temperature patterns across the districts of India. Class Level Landscape metrics (LSM) were calculated for Built-up and Shrub LU present inside every district and correlated with average LST over Built-up patches present in district. Results show that Average LST of built-up patches is affected by spatial attributes of Built-up patches with highest Variable Importance (VI) to Mean Perimeter-Area Ratio (para_mn) LSM in both years. Other common Important LSMs for LST of built-up patches are Core- Area index (cai_mn), Euclidian Mean Neighborhood Distance (enn_mn) and Aggregation index (ai). Region wise LSM for built-up patches in East and West regions of India show much significant relationship to LST. Shrub LU also shows a significant relationship with LST patterns of Built-up patches in the same district in terms of LSMs as spatial attributes.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ravi Verma and P.K. Garg "Identifying spatial attributes of LULC classes affecting urban area LST in districts of India", Proc. SPIE 12735, Remote Sensing Technologies and Applications in Urban Environments VIII, 1273505 (19 October 2023); https://doi.org/10.1117/12.2685083

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