Vegetation moisture estimation in the Western United States using radiometer-radar-lidar synergy

• DOI: 10.1016/j.rse.2024.113993
• Publication Date: 2024-01-16T22:26:24Z
• Authors: David Chaparro; Thomas Jagdhuber; María Piles; François Jonard; Anke Fluhrer; Mercè Vall-llossera; Adriano Camps; Carlos López-Mart...; Roberto Fernández...; Martin Baur; Andrew F. Feldman; Anita Fink; Dara Entekhabi
• Keywords: Backscatter (email)

Monitoring vegetation moisture conditions is paramount to better understand and assess drought impacts on vegetation, enhance crop yield predictions, improve ecosystem models. Passive microwave remote sensing allows retrievals of the optical depth (VOD; [unitless]), which directly proportional water content (VWC; in units mass per unit area [kg/m2]). However, VWC largely dependent dry biomass structure imprints VOD signal. Previously, statistical models have been used isolate component from components. Physically-based approaches not yet proposed for this goal. In study, we present a multi-sensor semi-physical approach retrieve express it as Live Fuel Moisture Content (LFMC [%]; percentage unit). The study performed western United States period April 2015 – December 2018. There, situ LFMC samples are available assessment. We rely model based height data GEDI/Sentinel-2 radar backscatter Sentinel-1, account Vegetation retrieved at L-, X- Ku-bands by minimizing difference between modeled estimates SMAP (L-band) AMSR-2 (X- Ku-band) satellites. Results show that independent canopy height, land cover, backscatter, demonstrating capability algorithm separate dynamics biomass/structure VOD. reproduce well expected spatio-temporal LFMC. good agreement with regional scale, Pearson's correlations (r) 0.64 (Ku-band), 0.60 (X-band) 0.47 (L-band). Similar results obtained independently shrub forest sites Ku-bands. most comparisons estimated LFMC, biases below 10% dynamic range Performance L-band limited fact frequency senses full vertical extent canopy, while taken only top leaves much more sensitive. More insight will be needed grasslands (r = 0.44 X-band) using time-dynamic data. Furthermore, pixel-scale assessment conducted, showing > 0.6). method can tailored exploit synergies past (e.g., AMSR-E), current AMSR-2) future satellite sensors such CIMR ROSE-L global mapping different layers.