AbstractsEngineering

Using Satellite Based Microwave Observations to Characterize Land Surface Hydrology

by Yi Liu




Institution: University of New South Wales
Department: Civil & Environmental Engineering
Year: 2012
Keywords: soil moisture; satellite; microwave; vegetation optical depth
Record ID: 1072307
Full text PDF: http://handle.unsw.edu.au/1959.4/51538


Abstract

In previous studies, satellite based microwave instruments have been shown to provide useful retrievals of soil and vegetation moisture response at the global scale. Using a series of satellite based microwave sensors, passive microwave soil and vegetation moisture products from the VU Amsterdam-NASA (VUA-NASA) and the Vienna University of Technology (TU-Wien) active microwave soil moisture product have been derived. From this three decades record of land surface response, the opportunity to generate an enhanced long term soil and vegetation moisture products by combining retrievals from different satellites has been explored in this study. Several issues needed to be resolved in accomplishing this objective. 1. No single satellite covers the entire period. As such, differences in sensor and algorithm specifications result in different absolute values of soil and vegetation moisture, preventing direct merging of them from these different sensors. 2. The currently available VUA-NASA passive and TU-Wien active microwave soil moisture products are conceptually different, in that they produce volumetric soil moisture and degree of saturation, respectively. 3. Their accuracy differs, making the selection of the optimum retrieval a nontrivial task. A methodology is proposed to address these issues and generate long term blended soil moisture and vegetation products, through the use of 1) a cumulative distribution function (CDF) matching approach, 2) a land surface model simulated soil moisture product, and 3) globally distributed in situ soil moisture measurements. The two blended products resulting from this analysis were evaluated using independent data sources, including regional to global precipitation and temperature products, the Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (AVHRR NDVI), correlations with various ocean circulation indices, agricultural production of major crops, and satellite-based wild fire and deforestation products. These blended products are expected to provide additional valuable data with which to characterize long term dynamics of soil moisture and vegetation at global scales, providing an increased capacity for ongoing assessment and trend detection in land surface hydrology.