|CHAPPELL, ANDREW - University Of Salford|
|LEYS, JOHN - Department Of Agriculture - Australia|
|MCTAINSH, GRANT - Griffiths University|
|STRONG, CRAIG - Griffiths University|
Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 4/1/2008
Publication Date: 4/22/2009
Citation: Chappell, A., Leys, J.F., Mctainsh, G.H., Strong, C., Zobeck, T.M. 2009. Simulating multi-angle imaging spectro-radiometer (MISR) sampling and retrieval of soil surface roughness and composition changes using a bi-directional soil spectral reflectance model. In: Roeder, A and Hill, J, editors. Recent Advances in Remote Sensing and Geoinformation Processing for Land Degradation Assessment. London, UK: Taylor and Francis Group. p. 243-259.
Technical Abstract: Soil surface changes due to soil erosion can be detected by ground-based, hyper-spectral measurements of angular reflectance and a bi-directional soil spectral reflectance model. The next generation of wind and water erosion models should incorporate directional remote sensing data to improve large area assessment more frequently in time. The utility of this approach was investigated by simulating the angular sampling of pre-defined soil surface spectral reflectance models using the configuration of the Multi-angle Imaging Spectro-Radiometer (MISR) sensor. At least two zenith angles, regardless of the number of solar azimuth angles, were required to simulate MISR overpasses and match the ‘true’ values. The simulated MIST parameter values were used to detect soil surface change after rainfall and aeolian abrasion. The coarse spectral resolution and range of the simulated MISR wavebands limited the inferences that were made about the soil surface changes compared to earlier work.