Evaluation of different orientation angle distributions within the X-Bragg scattering model for bare soil moisture estimation

Autor: Y. S. Rao, G. G. Ponnurangam
Rok vydání: 2017
Předmět:
Zdroj: International Journal of Remote Sensing. 38:4379-4395
ISSN: 1366-5901
0143-1161
DOI: 10.1080/01431161.2017.1320447
Popis: In this paper, the applicability of three different orientation angle distributions of surface facets within the extended Bragg (X-Bragg) scattering model is investigated for estimation of soil moisture over bare surfaces using both Eigen-based and model-based polarimetric synthetic aperture radar (PolSAR) decomposition techniques. The three distributions considered for investigation in the X-Bragg model are uniform, half cosine, and the Lee distributions. In order to understand the sensitivity of the model using the three orientation angle distributions, key polarimetric parameters, such as scattering entropy (H), scattering anisotropy (A), scattering mechanism (a), cross-pol power (T-33), linear T-12 coherence (|gamma(HH+VV)(HH-VV)|), are simulated and analysed for various widths of distributions. The analysis of the simulated polarimetric parameters show that the Lee distribution has a reduced roughness validity range compared with the uniform and half cosine distributions. DLR E-SAR L-band data from the AgriSAR' 2006 campaign over the Demmin test site in Northern Germany are inverted for soil moisture over bare surfaces. The inverted soil moisture from the physics-based X-Bragg model is compared with in situ measured TDR (time domain reflectometry) soil moisture values. The inversion results using the Eigen-based decomposition reveal similar root mean square error (RMSE = 14 vol.%) and inversion rates for three distributions. The model-based decomposition inversion results obtained at various fixed widths of distributions reveal that the Lee distribution shows less RMSE of 8 vol. % and high inversion rates for moderate surface roughness (ks = 0.5) as compared with half cosine and uniform distributions.
Databáze: OpenAIRE