Analysis of ALOS2 L-band repeat-pass InSAR for the retrieval of Snow Water Equivalent over boreal forest.

<p>The mass of seasonal snow is a challenging parameter to measure from space. This is a significant observational gap as information on snow mass would be required by diverse applications such as flood prevention, and water resource management. Snow Water Equivalent (SWE) describes the amount of liquid water that is stored in the snowpack. A promising technique to measure changes in SWE over time is repeat-pass Interferometric SAR (InSAR), since it provides high spatial resolution and reasonable temporal resolution. The retrieval technique relies on the phase difference induced by the increase in propagation path due to snow accumulation since snow has a higher permittivity than air [1]. The retrieval has been demonstrated using a wide range of sensors [1-3]. In a recent work [4], the usability of L-, S-, C-, and X- frequency bands (1-10 GHz) was analysed in the context of coherence conservation and SWE retrieval. L-band emerged as a solid candidate, as this band appeared more resilient against temporal decorrelation in snow while enabling retrieval of large amounts of SWE.</p> <p>The Copernicus Radar Observation System for Europe in L-band (ROSE-L), estimated to be launched in 2028, is one of the six Copernicus high-priority Sentinel Expansion missions selected for implementation. The mission will consist of two satellites with a 180 degrees orbit phasing, allowing a temporal baseline of 6 days. We present an analysis of L-band ALOS2 imagery over Sodankyl&#228;, in northern Finland, applied for SWE retrieval using the InSAR method. The landscape is dominated by coniferous forest, presenting a challenge for large-scale retrieval of SWE. Due to ALOS2 revisit time of 14 days, it is prone to suffer from temporal decorrelation. We analysed the coherence conservation considering environmental events, land cover, canopy cover and topography. We introduce SnowModel [5], a high-resolution, spatially distributed physical snow evolution model, for comparison to InSAR SWE retrievals. SnowModel simulations were used to calibrate the interferometric phase, allowing a comparison between the two and demonstrating in which areas and under which conditions the retrieval works.</p> <p>&#160;</p> <p>[1] T. Guneriussen, K. A. Hogda, H. Johnsen and I. Lauknes, "InSAR for estimation of changes in snow water equivalent of dry snow," in IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 10, pp. 2101-2108, Oct. 2001, doi: 10.1109/36.957273.</p> <p>[2] T. Nagler et al., "Airborne Experiment on Insar Snow Mass Retrieval in Alpine Environment," IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 4549-4552, doi: 10.1109/IGARSS46834.2022.9883809.</p> <p>[3] S. Leinss, A. Wiesmann, J. Lemmetyinen and I. Hajnsek, "Snow Water Equivalent of Dry Snow Measured by Differential Interferometry," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 8, pp. 3773-3790, Aug. 2015.</p> <p>[4] J. J. Ruiz et al., "Investigation of Environmental Effects on Coherence Loss in SAR Interferometry for Snow Water Equivalent Retrieval," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022, Art no. 4306715, doi: 10.1109/TGRS.2022.3223760.</p> <p>[5] Liston, Glen E.; Elder, Kelly. 2006. A distributed snow-evolution modeling system (SnowModel). Journal of Hydrometeorology. 7(6): 1259-1276</p> <p>&#160;</p>