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The continuous expansion of impervious surfaces replacing the vegetation cover and surface water areas increases urban heating. Such heating leads to downward heat transfer and latent heat flux from the surface to subsurface aquifers. This study used Landsat optical and thermal satellite data for land use/land cover (LULC), land surface temperature (LST), and anthropogenic heat flux (Has) change mapping in Bangalore City, India. The in situ sensor-based land surface temperature (LST) and groundwater temperature (GWT) measurements were used to validate the study outcome. A minor difference was observed between the satellite data and the in situ LST due to the differential data acquisition time. The built-up area increased from 7.61% to 28.78% from 1999 to 2017 at the cost of the green cover and the extent of waterbodies. Therefore, LST change was higher in green cover areas (~6 °C LST) than in urban areas (>3 °C). The anthropogenic heat fluxes increased significantly (above 65 W/m2) during the study period. The in situ GWT was strongly correlated with the Has (R2 = 0.83) and LST (R2 = 0.78). The study highlights the nature of urban expansion in Bangalore City, India, and its impact on LST, Has, and GWT. The observed changes in land use practices with urban heat indicators at 30 m scale can be used for sustainable land use planning to improve the thermal comfort of the city, preserving the urban ecosystems. The high collinearity between satellite-data-derived LST, Has, and GWT can be used for periodic monitoring at seasonal and annual scales using the Landsat data, which can be important inputs for land use planners and policymakers.

India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.

The Pulicat lagoon extending between 13 degree 20'-13 degree 40'N lat. and 80 degree 14'-80 degree 15'E long., and formed out of backwaters of the Bay of Bengal super(1)- super(2), is the second largest brackish water lagoon having an area of approximately 600 km super(2). The river waters of Kalangi, Uppativagu, Pamu-lakalva and other rainfed freshwater streams super(3)' super(4) drain into the lagoon, making it rich in biodiversity. Pulicat lagoon is the feeding ground for local and longdistance migrant bird species. Longdistance migrants like the pelican, flamingo, painted stork, spoon-billed stork, snake bird and sand piper, and a variety of bird species super(3) feed on aquatic flora and fauna of the Pulicat Lake waters. Besides, several species of crustaceans, brachiopods, edible and non-edible fishes, and mollusks are present in the Pulicat Lake, providing food for secondary and tertiary consumers of the food chain, namely migrant birds super(3,5,6),. About 50,000 fishermen are also dependent on the Pulicat Lake. The sea mouth is important as sea water flows into the lake during high tide and lake water flows into the sea during low tide. Satellite data and field work undertaken showed shrinking of one of the three sea mouths, namely that at Tupilipalem on the northern most side of the Pulicat lagoon located in Nellore District, Andhra Pradesh, which might pose a threat to the lake biodiversity. The sea-mouth width retrospective data were retrieved by satellite remote sensing, whereas direct observation data in the field were collected for 2007 and 2008. Future ecoremedial measures for conservation are discussed and presented here.

Traditional processing of Circular Polarimetric (Compact Polarimetric)—Synthetic Aperture Radar (CP-SAR) images from the Satellites has been done after receiving the raw data in the Ground Station. The availability of million gate FPGAs has given scope for doing many processing steps on-board itself which has given scope for Smart Small Satellites. The feasibility exists especially for small scenes of interest which have limited data in smaller volumes for ease of processing. National Remote Sensing Centre, Indian Space Research Organisation (NRSC, ISRO) have carried out ground processing with software tools hosted in high performance computers, using the m-delta (δ) decomposition method on the L1-SLC data of CP-SAR payload of RISAT-1 satellite for classification. In our research work, the same data set, and m-delta(ẟ) decomposition method have been chosen for implementation and processing in FPGA fabric, for comparison with earlier Ground based processed results. As part of prototyping, an Intel FPGA evaluation board kit was used. Preliminary results are encouraging and can lead to potential future Smart Small Satellite missions with CP-SAR and on-board processing for direct classification of the scene under imaging for its possible direct delivery to the end user. Major advantage of this approach is the reduction in bandwidth, as the volume of data to be downlinked is reduced, due to lower latency, computational and round-trip times, potential scope for delivery to user with near real-time processing.

Background/Objectives: Uveal melanoma is a rare but aggressive intraocular malignancy that metastasizes in up to half of patients, most commonly to the liver, despite effective local treatment. In the absence of robust evidence, there are no standardized guidelines for post-treatment surveillance, resulting in wide variation in imaging modalities, frequency, and duration across physicians and institutions. This study aimed to develop expert consensus recommendations for surveillance strategies in patients with uveal melanoma. Methods: A modified Delphi method was conducted across three iterative survey rounds between September 2024 and February 2025 using an online platform. Panelists included medical oncologists, ocular oncologists, radiologists, and surgical oncologists from North America. A multidisciplinary steering committee developed statements addressing risk-based surveillance using both molecular and clinical prognostic factors, including gene expression profiling (GEP) and PRAME status. Consensus was defined a priori as ≥70% of panelists rating a statement 7–9 on a 9-point Likert scale. Results: Forty-nine experts were invited, and 41 completed at least one survey round. The panel represented 17 U.S. states, Washington, D.C., and two Canadian provinces. Twelve statements reached stable consensus, including recommendations for imaging modality, frequency, and duration in intermediate- and high-risk patients. Although there was agreement that low-risk patients warrant surveillance, no consensus was reached on the optimal approach for this group. Conclusions: This is the first study to provide consensus-based guidance incorporating GEP and PRAME status into surveillance recommendations for uveal melanoma, offering a standardized framework to guide clinical practice and future research.