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The purpose of this study was to evaluate the decadal changes in the Land use/Land cover (LULC) pattern of the Jaipur district that affect the occurrence of Urban Heat Island (UHI) from 2009 to 2019, by using remote sensing and GIS data. The Landsat 7 and Landsat 8 datasets were classified using Supervised Maximum Likelihood classification method into classes: Urban, Vegetation, and Other. Further, using heatwave-based approach on land surface temperature (LST) maps, occurrence of UHI was determined. The results indicate a 26.55% increase in the urban area cover with a subsequent rise of 50C in the mean LST from year 2009 to 2019. With the increase in LULC and LST over the study period, intensification in the occurrence of Urban Heat Islands has been observed both in terms of their number and temperature. Interestingly, a 5.97% increase in vegetation cover has also been observed during the decade, but the effect of increase in vegetation was negligible and could not prevent the UHI effect in the area. Furthermore, Jaipur master development plan 2025 indicates expansion in terms of urbanisation and industrialization, so this study will be valuable for urban planners, policymakers, and relevant authorities in order to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Polarimetric synthetic‐aperture radar (SAR) remote sensing has been widely used for structural and biophysical parameters retrieval of forest vegetation. It has been found that the combination of polarimetric properties and interferometric characteristics of SAR remote sensing provides the capacity to retrieve forest height. The prime objective of this research was to investigate the potential of Polarimetric Synthetic Aperture Radar Tomography (PolTomSAR) for the forested and river region of Mondah National Park, Gabon. SAR tomography is an improved method for acquiring the height of geographical features. UAVSAR L‐band fully polarimetric multibaseline data have been used in this research (1.275 GHz). SAR data and ground data over the area have been collected in the year 2016. With the superresolution‐based Capon algorithm, multiple scatterers located at a different vertical position in the same azimuth range cell has been resolved and reconstructed. This work provides a framework for Capon‐based tomographic processing of multibaseline UAVSAR data for vertical profile retrieval of forest vegetation. The height profile of the forest patch having sparse, as well as dense vegetation, were retrieved. The vertical profile for a single azimuthal bin was obtained in range direction. The tomographic profile obtained was cross‐checked with the field‐measured forest height for the 16 locations in Mondah National Park, Gabon. To check the accuracy of the applied method, the statistical method of R2 and root‐mean‐square error (RMSE) is employed. The obtained RMSE of the result is 4.21 m and R2 is 0.92. The obtained results were concluded to find the potential of the Capon algorithm for the tomographic reconstruction of UAVSAR data. Key Points: PolSAR Tomography of UAVSAR data for forest height retrievalAn analysis of tomographic profiles for forest vegetation and water bodyAccuracy assessment of PolSAR tomography‐based forest height retrieval [ABSTRACT FROM AUTHOR]