TITLE:
Influence of Vegetation Cover on the Oh Soil Moisture Retrieval Model: A Case Study of the Malinda Wetland, Tanzania
AUTHORS:
Fridah Kirimi, David N. Kuria, Frank Thonfeld, Esther Amler, Kenneth Mubea, Salome Misana, Gunter Menz
KEYWORDS:
Surface Soil Moisture, Oh Model, Water Cloud Model, Wetland, TerraSAR-X
JOURNAL NAME:
Advances in Remote Sensing,
Vol.5 No.1,
March
7,
2016
ABSTRACT: Soil moisture is an important parameter that drives agriculture, climate and hydrological systems.
In addition, retrieval of soil moisture is important in the analysis as well as its influence on these
systems. Radar imagery is best suited for this retrieval due to its all-weather capability and independence
from solar irradiation. Soil moisture retrieval was done for the Malinda Wetland, Tanzania,
during two time periods, March and September 2013. The aim of this paper was to analyze soil
moisture retrieval performance when vegetation contribution is taken into account. Backscatter
values were obtained from TerraSAR-X Spotlight mode imagery taken in March and September
2013. The backscatter values recorded by SAR imagery are influenced by vegetation, soil roughness
and soil moisture. Thus, in order to obtain the backscatter due to soil moisture, the roughness and
vegetation contribution are determined and decoupled from total backscatter. The roughness parameters
were obtained from a Digital Surface Model (DSM) from Unmanned Aerial Vehicle (UAV)
photographs whereas the vegetation parameter was obtained by inverting the Water Cloud Model
(WCM). Lastly, soil moisture was retrieved using the Oh Model. The coefficient of correlation between
the observed and retrieved was 0.39 for the month of March and 0.65 in the month of August.
When the vegetation contribution was considered, the r2 for March was 0.64 and that in August was
0.74. The results revealed that accounting for vegetation improved soil moisture retrieval.