Improvement of microwave emissivity of frozen Arctic soils using roughness measurements derived from automated computer vision photogrammetry.

Abstract:

Soil emissivity of Arctic regions is a key parameter for assessing surface properties from microwave brightness temperature (Tb) measurements. Particularly in winter, frozen soil permittivity and roughness are two poorly characterized unknowns that must be considered. Here, we show that after removing snow, the 3D soil roughness can be accurately inferred from in-situ photogrammetry using Structure from Motion (SfM). Using an automated method of computer vision, multiple field measurements were perform giving us more insight of geophysical properties of frozen ground. We focus on using a SfM technique to provide accurate roughness measurements and improve emissivity models of frozen arctic soil for microwave applications at large scale. Validation was performed from ground-based radiometric measurements at 19 and 37 GHz using three different soil emission models: the Wegmüller and Mätzler (1999) model (Weg99), the Wang and Choudhury (1981) model (QNH), and a geometrical optics model (Geo Optics). Measured and simulated brightness temperatures over different tundra and rock sites in the Canadian High Arctic show that Weg99, parametrized with SfM-based roughness and prescribed permittivity, best models soil emission, yielding a root mean square error below 4 K for all frequencies and polarizations, compared to 10.9 K with soil parametrization reported in the literature. Our SfM based approach allowed us to measure roughness with 0.1 mm accuracy at 55 locations of different land cover type using a digital camera.