Assessment of energy fluxes and surface-atmosphere energy balance is considered an important study for an urban environment. The arrangement of manmade impervious surfaces (building and roads), their geometry and orientation, material composition, albedo/emissivity, topography, natural and delineated spaces of vegetation, and the concurrent atmospheric profiles together play a pivotal role in defining the urban morphological environment at micro-scale. Hyperspectral remote sensing images can prove to be instrumental in identifying the inherent material characteristics of the urban surfaces. The study focuses on identifying six man-made (asphalt, concrete, tin, iron, china mosaic, HDPE) and five natural features (lake water, river water, trees, soil, grass) in the city of Ahmedabad, India using ISRO-NASA airborne campaign hyperspectral data captured on February 11, 2016 under the Airborne Visible and InfraRed Imaging Spectrometer – Next Generation (AVIRIS-NG), of JPL (Jet Propulsion Laboratory), NASA bearing a spatial resolution of 8.1 m. The dimensionality reduction of the reflectance data was performed using a standard shift difference method in minimum noise fraction (MNF) technique by retaining the bands possessing coherent signals and dismissing the noise component within the data. The MNF data was further exposed to a partial linear spectral unmixing approach of mixture tuned matched filtering (MTMF) possessing the dual character of maximizing the target endmember response and suppressing the background redundant noisy information by a filtering and tuning process. It was observed that the overall accuracy of identification of various materials using random checkpoints (ranging from 50 to 200) varied from 82.3% to 87.7%. High accuracy was observed in the natural features than the man-made features/materials. The knowledge of materials in an urban purlieu shall aid in understanding the urban environment in terms of energy demand and energy-balance and further help in deciphering the cause of urban heating.

The rapid urbanization of Jaipur has profoundly altered its urban climate, driven by anthropogenic heat flux (A_F) and shifts in surface energy dynamics. This study leverages remote sensing techniques, utilizing Landsat data, to quantify A_F and assess its influence on the city’s climate. The findings reveal a striking paradox; despite a significant rise in A_F from 127.31 W/m² in 1993 to 201.82 W/m² in 2020, Jaipur exhibits an anomalous urban cool island (UCI) effect during the daytime. In this phenomenon, surrounding fallow lands experience higher land surface temperatures (LSTs) than the urban core, defying the typical urban heat island (UHI) effect observed in most cities worldwide. This paradox is especially pronounced in semi-arid urban environments, where factors such as limited vegetation, arid conditions, and water scarcity intricately shape peculiar thermal behaviour. This study further highlights the role of urban expansion, with built-up areas growing from 11.95% in 1993 to 19% in 2020, intensifying A_F. Notably, the latent heat flux was highest in vegetated areas, significantly reducing LSTs by facilitating evapotranspiration. Daytime surface temperatures have surged significantly, with temperatures ranging from 26–46.9 °C in 1993 to 31–56.5 °C in 2020, indicating an overall increase in surface heat intensity. Despite these increases, the UCI effect remains observable, further illustrating the cooling potential of urban vegetation. This study offers novel insights into the intricate dynamics of urban heat in semi-arid cities, providing refined perspectives on urban heat mitigation strategies and climate adaptation, with implications for future sustainable urban planning and environmental management.