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<p><strong>Abstract.</strong> Urban environment is examined through time series Landsat TM (Thematic Mapper) and OLI/TIRS (Operational Land Imager &amp;amp; Thermal Infrared Sensor) sensor images. A continuous surface of Land Surface Temperature (LST) can be extracted from Landsat thermal bands. Similarly different band combinations and ratios will give spatial pattern of land cover categories. Among these, building and vegetation indices are used to characterize the spatiotemporal pattern of elevated temperature zones in cities. This excess heat concentration creates thermal hotspots which are known as Urban Heat Islands (UHI). Parameters of land cover are then related to LST to detect the influence of urbanization on intensity and extent of heat islands, by pixel based quantitative analysis. This paper focuses on two megacities of India and their surrounding districts for identifying the critical UHI areas. The purpose of this paper is to create a database for reconstruction in old cities and planning of new smart cities. Results suggest that urban sprawl and substitution of rural areas with impervious surface plays significant role in microclimate, causing formation of new thermal hotspots. The analysis of urban thermal environment and its dynamics is to provide a scientific basis for future strategy building.</p>

Abstract. Land management in the limited environment of city regions with immense population pressure is a challenging task. To achieve the goal of sustainable smart cities, reliable spatial information needs to be incorporated in land governance policies. In this study, Landsat 8 satellite bands were processed to derive the land use characteristics which are causing the development of urban heat islands at certain locations. To assess the prolonged effects of heat-trapping in cities, night time temperature data was obtained through in-situ data collection with error within 1 °C. Much higher intensity of urban heat island was observed during the night. The maximum increase of 1.67 °C was noted from day to night temperature for the same heat island. Seasonal analysis between winter and summer months was also carried out. The results suggested that for both day and night summer months produced more critical heat islands with maximum intensity up to 3.48 °C; while in winter the heat island intensity did not exceed 2.18 °C. Through comparative analysis between two cities with varying extent, urbanization and population pressure, it was observed that the maximum intensity of day time temperature was greater in a bigger city and heat islands were less fragmented. Heat islands covered an area of 10.39 km2 over Prayagraj and 28.29 km2 area of Kolkata. The temperature patterns obtained during day and night were statistically validated with the index of impervious surface area, at the significance level of α0.05.

Abstract. Satellite imageries were used to study temporal and seasonal patterns of Land Surface Temperature (LST) in Kabul, followed by establishing an interrelation with Land Use Land Cover (LULC) changes occurring in the city. LULC and LST changes were examined based on Landsat Thematic Mapper (TM) and Landsat Operational Land Imager (OLI), Thermal Infrared Sensors (TIRS). LST Maps were derived from the thermal band of Landsat images for decadal study (Winter/Summer; 2008–09 and 2018–19). Visible bands were utilized for supervised LULC classification in the same decade. Results showed that Kabul City expanded rapidly over the study period from 232.28 km2 to 371.08 km2 in one decade (2009–2019). Other land cover classes i.e. barren land, mountains and vegetation, were observed to be converted to urban class i.e. residential, commercial, and industrial. High LST zones of Kabul city consisted of mountains, barren land and urban areas. Notable difference of 3 °C was observed between urban and vegetated lands. This study successfully identified the areas (i.e. district 12, district 13 and district 17) currently affected by rapid urban sprawl. The results also highlighted the changes in LST pattern caused by urbanization. The study will help the government, private sector investors and land planners to develop sustainable land management policies.