parameterized surface reflectivity model and estimation of bare-surface soil moisture with L-band radiometer

• Published in: IEEE transactions on geoscience and remote sensing Vol. 40; no. 12; pp. 2674 - 2686
• Main Authors: Shi, Jiancheng, Chen, K. S, Li, Qin, Jackson, Thomas J, O'Neill, Peggy E, Tsang, Leung
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.12.2002; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: algorithms; Applied geophysics; Dielectric measurements; dielectric properties; Earth; Earth sciences; Earth, ocean, space; environmental models; environmental monitoring; equations; Exact sciences and technology; Geophysical measurements; geophysics; Internal geophysics; L-band; microwave radiation; microwave radiometers; Microwave radiometry; model validation; monitoring; Monte Carlo method; Reflectivity; Remote monitoring; remote sensing; Rough surfaces; roughness; satellites; simulation models; Soil moisture; soil surface layers; soil water; Surface roughness; Maryland; USA, Maryland; algorithms; models; inverse problem; soil moisture; Space remote sensing; dielectric properties; accuracy; Index Terms-L-band radiometer; roughness; radiometry; polarization; wave reflection; surface properties; errors; surface emission; correlation function
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2002.807003

Soil moisture is an important parameter for hydrological and climatic investigations. Future satellite missions with L-band passive microwave radiometers will significantly increase the capability of monitoring Earth's soil moisture globally. Understanding the effects of surface roughness on microwave emission and developing quantitative bare-surface soil moisture retrieval algorithms is one of the essential components in many applications of geophysical properties in the complex Earth terrain by microwave remote sensing. We explore the use of the integral equation model (IEM) for modeling microwave emission. This model was validated using a three-dimensional Monte Carlo model. The results indicate that the IEM model can be used to simulate the surface emission quite well for a wide range of surface roughness conditions with high confidence. Several important characteristics of the effects of surface roughness on radiometer emission signals at L-band 1.4 GHz that have not been adequately addressed in the current semiempirical surface effective reflectivity models are demonstrated by using IEM-simulated data. Using an IEM-simulated database for a wide range of surface soil moisture and roughness properties, we developed a parameterized surface effective reflectivity model with three typically used correlation functions and an inversion model that puts different weights on the polarization measurements to minimize surface roughness effects and to estimate the surface dielectric properties directly from dual-polarization measurements. The inversion technique was validated with four years (1979-1982) of ground microwave radiometer experiment data over several bare-surface test sites at Beltsville, Maryland. The accuracies in random-mean-square error are within or about 3% for incidence angles from 20° to 50°.