Development of a physically-based soil moisture retrieval algorithm for spaceborne passive microwave radiometers and its application to AMSR-E

• Published in: Journal of the Remote Sensing Society of Japan (Japan) Vol. 29; no. 1
• Main Authors: Lu, H.(Tokyo Univ. (Japan)), Koike, T, Fujii, H, Ohta, T, Tamagawa, K
• Format: Journal Article
• Language: English
• Published: 01.01.2009
• Subjects: CALCUL; CALCULATION; CALCULO; CAPTEUR; CONTENIDO DE AGUA EN EL SUELO; EARTH OBSERVATION SATELLITES; MICRO-ONDES; MICROONDAS; MICROWAVE RADIATION; MONGOLIA; MONGOLIE; REMOTE SENSING; SATELITES DE OBSERVACION TERRESTRE; SATELLITES D'OBSERVATION DE LA TERRE; SENSORES; SENSORS; SIMULACION; SIMULATION; SOIL TEMPERATURE; SOIL WATER CONTENT; TELEDETECCION; TELEDETECTION; TEMPERATURA DEL SUELO; TEMPERATURE DU SOL; TENEUR EN EAU DU SOL
• ISSN: 0289-7911
• DOI: 10.11440/rssj.29.253

Many microwave radiometer algorithms for the retrieval of soil moisture tend to overestimate moisture in very dry cases, partly due to volume scattering effects. This study reports the development of a physically-based soil moisture retrieval algorithm for passive microwave remote sensing. The algorithm is based on physically-based radiative transfer, which simulates the radiative transfer processes in soil by a 4-stream discrete ordinate method and the Henyey-Greenstein phase function. The multiple scattering effects of soil particles are calculated using the Dense Media Radiative Transfer Theory, and the surface roughness effects are simulated by the Advance Integral Equation method. The implementation of this algorithm consists of three steps: 1) forward model parameters optimization; 2) lookup table generation; and 3) lookup table reversion and soil moisture estimation. The algorithm was tested by retrieving soil moisture and temperature from AMSR-E Brightness Temperature data at a Coordinate Enhanced Observing Period reference site on the Mongolian Gobi. The retrieved soil moisture data was compared with in situ observations. The comparison shows that the performance of the new algorithm is satisfactory, with acceptable values of Standard Error of the Estimate and the square of the correlation coefficient. Moreover, the algorithm estimates soil physical temperature accurately.