IEEE GRSS IADF Photo Contest 2023​

Indian Resourcesat satellites provide vital multispectral information in Visible and SWIR wavelength range of electromagnetic spectrum for resource monitoring. LISS-4 is one of the payload onboard Resourcesat that capture remote sensing images at a spatial resolution of 5.0 meters and have three spectral bands in visible wavelength region. The LISS-4 processed image shown captured eastern part of Sambhar Salt Lake. Sambhar Lake is India’s largest inland salt lake that is located 80 km south-west of Jaipur, India and also designated as Ramsar site (wetland of international importance). LISS-4 spectral bands are separated in the focal plane at different angles that results into Band-to-Band mis-registration. The bands are co-registered over each using multi-stage feature detection techniques to achieve sub-pixel level accuracy. LISS-4 sensor does not have SWIR band that have lot of potential for earth observation applications spans from wetland delineation, forest fire monitoring to snow & cloud discrimination. We have synthesized SWIR band on ground at a spatial resolution of 5.0 meters using novel deep learning model. Adversarial learning framework guided by Spatio-Spectral Laplacian attention mechanism regulate the process of SWIR band Synthesis that uses Low Resolution (LR) and existing High Resolution (HR) concurrent spectral bands. In addition, we have enhanced LISS-4 color composite image using Contrast Limited Adaptive Histogram Equalization (CLAHE) for better feature demarking and generate best representative LISS-4 image for visualization and analysis. The spectacular LISS-4 color image shown is the composite generated using synthesized SWIR, NIR and Red wavelength channels. Sambhar Lake City is clearly visible in the LISS-4 enhanced color image. Rail road is also recognized in the LISS-4 multispectral image that was constructed by the British before India’s independence to provide access from Sambhar Lake city to salt works. LISS-4 processed imagery is a treasure hub for remote sensing applications that showcases the capability of Indian earth observation sensors to map our planet earth for global scientific community.

Acquisition. This image is a mosaic of high-resolution radar images taken with DLR’s airborne Synthetic Aperture Radar (SAR) system “F-SAR” over the mouth of the river Elbe near Hamburg, Germany. The extent of the entire scene is about 10 km x 10 km at a resolution of 50 cm x 50 cm per pixel and the total acquisition time was about 2 hours.

What is special in this image? Synthetic Aperture Radar (SAR) imaging techniques are combined for the first time with High Dynamic Range (HDR) techniques known from optics. Normally, the tidal flats are imaged with dark colors so that they remain largely hidden. A global increase in contrast and brightness would drive the pixels on land into saturation (white color). We therefore decouple land and tidal flats so that both parts of the image can be optimized independently.

Colors. The image was taken at a wavelength of about 9 cm (S-band), a wavelength at which humans cannot see. We therefore get glossy effects on structures (sandbanks and meadows) that would not be glossy with human vision. The colors of the image correspond to polarimetric properties of electromagnetic waves and they are chosen so that roofs of houses appear red, vegetation green and sand in golden colors.

This image is an analysis of the Amphan cyclone that occurred on December 10, 2020, using satellite observations from the SCATSAT-01 scatterometer. The image shows the visual representation and wind circulation of the cyclone. This image is particularly interesting because it showcases the power and destruction of nature. The Amphan cyclone was one of the most intense tropical cyclones to hit the Bay of Bengal in recent years. It caused widespread damage to homes, crops, and infrastructure, leaving thousands of people homeless and in need of assistance. It highlights the need for early warning systems, evacuation plans, and infrastructure that can withstand the force of powerful storms. In this way, this image can serve as a valuable educational tool for communities and decision-makers around the world. Furthermore, the image’s scientific significance cannot be understated. By analysing the wind circulation patterns captured in the image, one can gain a better understanding of the dynamics of tropical cyclones and use this information to develop more accurate forecasting models.This image conveys a powerful message about the importance of disaster preparedness and response and its scientific significance in advancing our understanding of tropical cyclones.