A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index

Abstract

Is it possible to solve the radiative transfer equation to derive surface soil moisture without information on the vegetation cover or soil moisture ground observations for calibration. Approach:A methodology for retrieving surface soil moisture and vegetation optical from satellite microwave radiometer data has been developed.The approach uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth with a nonlinear iterative optimization procedure.Results compared well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors. Significance and Implications of Findings:This approach does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes, and is totally independent of wavelength. It permits the retrieval of global surface moisture fields from satellite microwave observations. This procedure can provide historical data sets of global surface moisture from archived satellite microwave data, near-real time estimates, and could be valuable for initialization and as an input parameter for General Circulation Models. Relation to Earth Science Enterprise:The interpretation of satellite microwave observations for soil moisture determination has strong relevance within the Earth Science Enterprise Program, especially in land cover and use change, seasonal to interannual climate variability and prediction, and climate change research.The significance of this methodology increases with the inclusion of a microwave instrument on the new AQUA platform. A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference IndexManfred Owe, Richard de Jeu and Jeffrey Walker Popular SummaryA new procedure for estimating global soil moisture from microwave sensors on Earthorbiting satellites has been developed. This method uses a physically based equation, known as a radiative transfer relationship, and is unique in that it does not require measurements of ground data that have traditionally been necessary for calibration purposes.In addition, the procedure also estimates the vegetation optical depth. The optical depth is a measure of the amount of vegetation which overlies the surface. Together, these two variables can provide researchers with valuable information about the moisture status of the Earth's surface. Such information may be important for a variety of applications, such as drought monitoring, determining flooding potential, various agricultural applications, and estimating fire danger.

Üçlü Eşleştirme Yöntemi ile Uydu ve Hidrolojik Model Kaynaklı Toprak Nemi Değerlerinin Hata Oranlarının Bulunması

“…2002 yılından 2011 yılına kadar AQUA uydusu üzerinde bulunan AMSR-E sensörü vasıtasıyla yapılan gözlemlere dayanan toprak nemi değerleri, kuşkusuz bu alanda en sık kullanılan gözlemlerden birisidir. Bu gözlemler VUA tarafından uygulanan tek tabakalı modele dayanan radyasyon transfer denklemleri ile 0,25° mekansal ve 1 günlük zamansal çözünürlükteki LPRM toprak nemi değerlerine dönüştürülmüştür [8][9]. Bu verilerin analizleri şu ana kadar birçok çalışmada yapılmıştır [20][21][22].…”

Intercomparison of Soil Moisture Retrievals From In Situ, ASAR, and ECV SM Data Sets Over Different European Sites

“…The Essential Climate Variable Soil Moisture (ECV SM) product (Liu et al, 2011;Liu et al, 2012;Wagner et al, 2012) (Wagner et al, 1999a;Wagner et al, 1999b;Naeimi et al, 2009) is used to convert backscatter measurements to soil moisture values and the Land Parameter Retrieval Model (LPRM) developed jointly by VU University Amsterdam and the NASA Goddard Space Flight Center (Owe et al, 2001;De Jeu and Owe, 2003;Owe et al, 2008) is used to convert brightness temperatures to soil moisture respectively. The ECV SM product has been validated across different regions using in-situ, model and SAR-derived soil moisture datasets in previous studies (e.g.…”

New Approach for Calculating the Effective Dielectric Constant of the Moist Soil for Microwaves

“…To retrieve the soil moisture content from the measured TB, the traditional retrieval method requires ancillary information to account for soil temperature and soil texture, as well as for the effects of vegetation. Studies have attempted to obtain this ancillary data for vegetation from the vegetation parameter b [10], multi-frequency microwave sensor measurements [11][12][13], the NDVI (normalized differenced vegetation index) [14] or the MPDI (microwave polarization difference index) [15][16][17]. However, the measurement of land-surface properties is already very uncertain for bare soil without vegetation.…”