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Mauna Loa volcano (Hawaii) is the world’s largest subaerial volcano. Interferometric analysis of ISRO’s EOS-04 and ESA’s Sentinel-1 SAR images provided a detailed view on the surface deformation associated with the 2022 Mauna Loa volcano eruption. Co-eruptive InSAR analysis of Sentinel-1 data revealed Line-ofSight deformation of ±50 cm along the NE and SW rift zones. The complex bipolar deformation pattern in ascending and descending tracks suggests vertical and horizontal deformation associated with the sub-surface magma ascent and spreading respectively. InSAR analysis of EOS-04 data revealed concentric interferometric fringes east of the caldera. This near-circular deformation lobe (~ –13 cm) could be interpreted either as post-eruptive volcanic deflation or topographically correlated atmospheric artefact. Polarimetric and coherence based analysis revealed extensive lava flow along the SW and NE rifts (~15 km) and further towards the north along a topographic channel for about 16 km. Polarimetric radar analysis of a fresh lava flow channel associated with the NE rift zone revealed a transition between smooth pāhoehoe and rough a’a flow textures along its current extent. The present study demonstrates the interferometric and polarimetric capabilities of EOS-04 satellite for geophysical applications. [ABSTRACT FROM AUTHOR]

The retrieval of the biophysical parameters and subsequent estimation of the above-ground biomass (AGB) of vegetation stands are made possible by the simulation of the extinction and scattering components from the canopy layer using vector radiative transfer (VRT) theory-based scattering models. With the use of such a model, this study aims to evaluate and compare the potential of dual-pol, multi-frequency SAR data for estimating above-ground biomass. The data selected for this work are L-band dual polarized (HH/HV) ALOS-2 data, S-band dual polarized (HH/HV) NovaSAR data, and C-band dual polarized (VV/VH) Sentinel-1 data. The two key biophysical parameters, tree height, and trunk radius are retrieved using the proposed methodology, applying the frequencies independently. A general allometric equation with vegetation-specific coefficients is used to estimate the AGB from the retrieved biophysical parameters. The retrieval results are validated using ground truth measurements collected from the study area. The L-band, with the coefficient of determination ([Formula: see text]) of 0.73 and the root mean square error (RMSE) of 35.90 t/ha, has the best correlation between the modeled and field AGBs, followed by the S-band with an [Formula: see text] of 0.37 and an RMSE of 63.37 t/ha, and the C-band with an [Formula: see text] of 0.25 and an RMSE of 72.32 t/ha. The L-band has yielded improved estimates of AGB in regression analysis as well, with an [Formula: see text] of 0.48 and an RMSE of 50.02 t/ha, compared to the S- and C-bands, which have the [Formula: see text] of 0.12 and 0.03 and the RMSE of 70.98 t/ha and 80.84 t/ha, respectively., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)