Identification of climate change impact and thermal comfort zones in semi-arid regions of AP, India using LST and NDBI techniques

Andhra Pradesh, in southern India, frequently experiences warm summers and winters. However, the year-round greater relative humidity and the positioning of the summer hot spots are linked to actual weather heat exhaustion during the warmest months. Climate change is a significant-and frequently disregarded-factor in the relationship between climate and mortality. With the use of the Land Surface Temperature (LST) and Normalized Difference Built-up Index (NDBI), we sought to identify the climatic change in this research. Additionally, we attempted to identify the Thermal Comfort Zones (TCZs) in Andhra Pradesh, South India's semi-arid regions. Arc GIS and ERDAS Imagine were used to process the satellite data of Landsat 4-5 (TM & MSS), Landsat 7 ETM+, and Landsat 8 OLI for the development of LST and NDBI. The research was conducted for the past thirty years from 1990 to 2020. The resultant thermal comfort zones map was classified into four zones, Zone -I (Safe zone), Zone - II (Moderately safe zone), Zone - III (Risk Zone), and Zone-IV (Highly Risk Zone). The relation between the LST and NDBI is also revealed using correlation regression analysis in the study region. It has been noted that urban centre and high-density regions had greater LST than rural locations. The study finds that although this differs from one ecological zone to another and the distribution of LST intensity in the urban area depends on its changing LULC, various types of land cover within an urban region might impact the spatial pattern of urban LST. The main conclusions of this study might help policymakers understand the need of enabling more sustainable urban development in cities.

Automated summary

By using the Land Surface Temperature (LST) and Normalized Difference Built-up Index (NDBI), this study aimed to identify climate change and thermal comfort zones in the semi-arid regions of Andhra Pradesh, South India. The findings showed that urban areas and high-density regions had higher LST than rural areas, with different ecological zones exhibiting varying patterns. This study's main conclusions can assist policymakers in promoting more sustainable urban development.