Review of topographic analysis methods for the western Himalaya using AWiFS and MODIS satellite imagery

Abstract The topographic effects of differential terrain illumination in optical satellite imagery of rugged mountainous regions have serious consequences for qualitative and quantitative analysis for various snow applications. Therefore, effective removal or minimization of topographic effects is necessary in satellite image data of mountainous regions. Different methods for topographic corrections, including C-correction, Minnaert corrections (including slope) and slope-matching method, are analysed in the context of snow reflectance. Combination of dark-object subtraction models DOS1 and DOS3 is used for image-based atmospheric corrections while considering the effect of Rayleigh scattering on the transmissivity in different spectral bands of AWiFS and MODIS image data. The performance of different models is evaluated using (1) visual analysis, (2) change in snow reflectance on sunny and shady slopes after the corrections, (3) validation with in situ observations and (4) graphical analysis. The results show that the slope-matching technique could eliminate most of the shadowing effects in Himalayan rugged terrain and correctly estimate snow reflectance from AWiFS and MODIS imagery. The validation of results with in situ observations for both types of imagery suggests that all other methods significantly underestimate reflectance values after the corrections.

[1]  Yousuke Noumi,et al.  Discrepancy Between ASTER- and MODIS- Derived Land Surface Temperatures: Terrain Effects , 2009, Sensors.

[2]  R. Richter,et al.  Correction of satellite imagery over mountainous terrain. , 1998, Applied optics.

[3]  J. Colby,et al.  Topographic Normalization in Rugged Terrain , 1991 .

[4]  Vinay K. Dadhwal,et al.  Bandpass solar exoatmospheric irradiance and Rayleigh optical thickness of sensors on board Indian Remote Sensing Satellites-1B, -1C, -1D, and P4 , 2002, IEEE Trans. Geosci. Remote. Sens..

[5]  H. P. Foote,et al.  Radiometric calibration of Landsat Thematic Mapper , 1988 .

[6]  M. Minnaert.  The reciprocity principle in lunar photometry , 1941 .

[7]  P. Chavez.  Radiometric calibration of Landsat Thematic Mapper multispectral images , 1989 .

[8]  Ramesh P. Singh,et al.  Retrieval of sub-pixel snow cover information in the Himalayan region using medium and coarse resolution remote sensing data , 2009 .

[9]  David Riaño,et al.  Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types (2003) , 2003, IEEE Trans. Geosci. Remote. Sens..

[10]  M. S. Moran,et al.  Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output , 1992 .

[11]  C. Woodcock,et al.  Classification and Change Detection Using Landsat TM Data: When and How to Correct Atmospheric Effects? , 2001 .

[12]  Jeff Dozier,et al.  Snow Mapping and Classification from Landsat Thematic Mapper Data , 1987, Annals of Glaciology.

[13]  D. Civco.  Topographic normalization of landsat thematic mapper digital imagery , 1989 .

[14]  C. Justice,et al.  The topographic effect on spectral response from nadir-pointing sensors , 1980 .

[15]  F. D. van der Meer,et al.  Spectral mixture modelling and spectral stratigraphy in carbonate lithofacies mapping , 1996 .

[16]  J. Dymond,et al.  Correcting satellite imagery for the variance of reflectance and illumination with topography , 2003 .

[17]  D. Hall,et al.  Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data , 1995 .

[18]  Janet Nichol,et al.  Empirical correction of low Sun angle images in steeply sloping terrain: a slope‐matching technique , 2006 .

[19]  P. Teillet,et al.  On the Slope-Aspect Correction of Multispectral Scanner Data , 1982 .