August 28,2024
The GNSS-Reflectometry (GNSS-R) instrument on the EOS-08 satellite commenced operations on August 18, 2024. The raw data is being processed at the National Remote Sensing Centre (NRSC-ISRO) in Shadnagar, Hyderabad, using algorithms and data processing software developed by the Space Applications Centre (SAC-ISRO), Ahmedabad. Multiple levels of data products have been successfully generated.
GNSS-Reflectometry represents a new mode of remote sensing. Signals from Global and Regional Navigation Satellite Systems (GNSS/RNSS), such as GPS and NavIC, are reflected off various Earth surfaces, including oceans, agricultural lands, and river bodies. These reflected signals are collected by a precision receiver onboard the satellite (Fig. 1) as it orbits the Earth at an altitude of 475 km. This measurement system operates without dedicated transmitters and is shallow in resource consumption—requiring minimal size, weight, and power. Additionally, it can scale up as a constellation of receivers for faster coverage, making this innovative remote-sensing mode highly useful.
Fig.1: General principle of GNSS-Reflectometry
Fig.2 Delay Doppler Maps of Reflections
The GNSS-R instrument, developed by the Space Applications Centre (SAC-ISRO), is India’s first space-borne precision receiver. It collects ground-reflected GNSS signals and measures their power and other signal characteristics. These measurements are used to derive scientific information about the regions covered by the receiver, including soil moisture, surface inundation, and ocean surface wind and wave measurements. The instrument provides a resolution of 15 km x 15 km over oceans and better than 1 km x 1 km over land. Delay-Doppler Maps (DDMs) are the primary outputs from GNSS-R raw data processing (Fig 2). These DDMs are used to derive parameters such as reflectivity and Normalized Bistatic Radar Cross-Section (NBRCS), which are then used for the retrieval of various scientific parameters.
All the science products are generated at SAC-ISRO using in-house developed algorithms. The first land data was collected over the Sahara Desert (North Africa) using a high-resolution mode of 1 km, which is significantly better than that of contemporary CYGNSS sensors. This data was processed to retrieve soil moisture (Fig. 3) at high resolution, and the results were found to be within the expected range. Another high-resolution land dataset was acquired over the Amazon Rainforest on August 21. This data has been used to generate surface inundation masks along the specular reflection track, showing sensitivity even towards sub-kilometer river widths (Fig. 3). The first ocean data was collected on August 19, over a region of the Pacific Ocean. This data was processed for the retrieval of wind speed and significant wave height (Fig. 4), with all obtained values falling within the expected ranges.
Fig.3 (left) Retrieved Land Surface Soil Moisture over North Africa (right) Surface inundation, over a stretch of Amazon Rain Forests, which was overlaid on the JRC Surface Water Mapping ‘Occurrence’ Layer dataset
Fig.4 (left) Retrieved wind speed (right) significant wave height, over a region of the Pacific Ocean
While calibration and validation are ongoing, these results demonstrate the immense potential of this instrument for various scientific studies and applications.