Detection of Soil Moisture and Soil Freeze Using Microwave Radars
Smolander, Tuomo; Pulliainen, Jouni; Rautiainen, Kimmo; Lemmetyinen, Juha
Finnish Meteorological Institute, FINLAND
Soil moisture is considered an essential climate variable because it affects both weather and climate. It is important for understanding land surface processes for example in hydrology or agriculture. It also affects water and energy cycles between land and atmosphere, as well as surface energy balance. Soil moisture is an important variable for both climate models and numerical weather prediction models. It can also be used for monitoring the effects of climate change. Because soil moisture is hard to measure at large scales by traditional means, satellite remote sensing might provide a way to monitor its variation globally.
A method for detection of soil moisture and soil freeze using microwave radar measurements is presented. The detection is based on an inversion method presented by Pulliainen et al. in . It employs a semiempirical backscattering model that describes the dependence of radar backscattering of forest as a function of stem volume, soil moisture, vegetation canopy moisture, surface roughness and incidence angle. The backscattering model was developed using C- and X-band airborne HUTSCAT scatterometer data. The backscattering of soil is determined using model presented in . The inversion is made using a least-squares minimizing algorithm.
This method gives an estimate of soil moisture. It can be used to detect soil freeze by determining a treshold value below which the soil is considered to be frozen. The method can be used with both low resolution scatterometer measurements and higher resolution SAR-radars. It has been applied to spaceborne ASCAT scatterometer measurements within ESA CCI (Climate Change Initiative) Soil Moisture project and also to ASAR radar measurements over Sodankylä test site.
The ESA CCI Soil Moisture project aims to produce global soil moisture data record based on both active and passive microwave observations and includes comparing and analyzing different soil moisture retrieval algorithms using same satellite observation data set. The results produced by these algorithms are being evaluated by comparing them to in situ measurements and Global Land Data Assimilation System (GLDAS) soil moisture estimates. The results show that at some locations the soil moisture estimate acquired by the method presented here provides satisfactory accuracy but the results vary between different locations and some locations also have big variance in estimated values.
 Jouni T. Pulliainen, Terhikki Manninen, and Martti T. Hallikainen, "Application of ERS-1 Wind Scatterometer Data to Soil Frost and Soil Moisture Monitoring in Boreal Forest Zone," IEEE Transactions on Geoscience and Remote Sensing, vol. 36, no. 3, pp. 849-863, May 1998.
 Yisok Oh, Kamal Sarabandi, and Fawwaz T. Ulaby, "An Empirical Model and an Inversion Technique for Radar Scattering from Bare Soil Surfaces," IEEE Transactions on Geoscience and Remote Sensing, vol. 30, no. 2, pp. 370-381, March 1992.