Correcting the influence of vegetation on surface soil moisture indices by using hyperspectral artificial 3D-canopy models
2013
Surface soil moisture content is one of the key variables used for many applications especially in hydrology,
meteorology and agriculture. Hyperspectral remote sensing provides effective methodologies for mapping soil moisture
content over a broad area by different indices such as NSMI [1,2] and SMGM [3]. Both indices can achieve a high
accuracy for non-vegetation influenced soil samples, but their accuracy is limited in case of the presence of vegetation.
Since, the increase of the vegetation cover leads to non-linear variations of the indices.
In this study a new methodology for moisture indices correcting the influence of vegetation is presented consisting of
several processing steps. First, hyperspectral reflectance data are classified in terms of crop type and growth stage.
Second, based on these parameters 3D plant models from a database used to simulate typical canopy reflectance
considering variations in the canopy structure (e.g. plant density and distribution) and the soil moisture content for actual
solar illumination and sensor viewing angles. Third, a vegetation correction function is developed, based on the
calculated soil moisture indices and vegetation indices of the simulated canopy reflectance data. Finally this function is
applied on hyperspectral image data.
The method is tested on two hyperspectral image data sets of the AISA DUAL at the test site Fichtwald in Germany. The
results show a significant improvements compared to solely use of NSMI index. Up to a vegetation cover of 75 % the
correction function minimise the influences of vegetation cover significantly. If the vegetation is denser the method leads
to inadequate quality to predict the soil moisture content. In summary it can be said that applying the method on weakly
to moderately overgrown with vegetation locations enables a significant improvement in the quantification of soil
moisture and thus greatly expands the scope of NSMI.
Keywords:
- Correction
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