Assessment of different topographic correction methods in ALOS AVNIR-2 data over a forest area

Abstract Because the removal of topographic effects is one the most important pre-processing steps when extracting information from satellite images in digital Earth applications, the problem of differential terrain illumination on satellite imagery has been investigated for at least 20 years. As there is no superior topographic correction method applicable to all areas and all images, a comparison of topographic normalization methods in different regions and images is necessary. In this study, common topographic correction methods were applied on an ALOS AVNIR-2 image of a rugged forest area, and the results were evaluated through different criteria. The results show that the simple correction methods [Cosine, Sun-Canopy-sensor (SCS), and Minnaert correction] are inefficient in exceptionally rough forests. Among the improved correction methods (SCS+C, modified Minnaert, and pixel-based Minnaert), the best result was achieved using a pixel-based Minnaert approach in which a separate correction factor in various slope angles is used. Thus, this method should be considered for topographic correction, especially in forests with severe topography.

[1]  C. E. Leprieur,et al.  Influence of topography on forest reflectance using Landsat Thematic Mapper and Digital Terrain Data , 1988 .

[2]  J. Colby,et al.  Anisotropic reflectance correction of SPOT-3 HRV imagery , 2002 .

[3]  Li Zhang,et al.  Integrating modelling and remote sensing to identify ecosystem performance anomalies in the boreal forest, Yukon River Basin, Alaska , 2008, Int. J. Digit. Earth.

[4]  A. Gillespie,et al.  Comment on: Topographic normalization of Landsat TM images of forest based on subpixel sun-canopy-sensor geometry, by Gu and Gillespie (Remote Sens. Environ 64 :166-175, 1998). Authors' reply , 1999 .

[5]  P. Chavez.  Image-Based Atmospheric Corrections - Revisited and Improved , 1996 .

[6]  Klaus I. Itten,et al.  RADIOMETRIC CORRECTIONS OF TOPOGRAPHICALLY INDUCED EFFECTS ON LANDSAT TM DATA IN ALPINE TERRAIN , 1997 .

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

[8]  Ayad Mohammed Fadhil,et al.  Drought mapping using Geoinformation technology for some sites in the Iraqi Kurdistan region , 2011, Int. J. Digit. Earth.

[9]  A. Gillespie,et al.  Topographic Normalization of Landsat TM Images of Forest Based on Subpixel Sun–Canopy–Sensor Geometry , 1998 .

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

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

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

[13]  C. Conese.  Topographic normalization of TM scenes through the use of an atmospheric correction method and digital terrain model , 1993 .

[14]  Shaban Shataee Joibary,et al.  Forest type mapping using incorporation of spatial models and ETM+ data. , 2007, Pakistan journal of biological sciences : PJBS.

[15]  T. Tokola,et al.  Use of topographic correction in Landsat TM-based forest interpretation in Nepal , 2001 .

[16]  C. Justice,et al.  Application of digital terrain data to quantify and reduce the topographic effect on Landsat data , 1981 .

[17]  Klaus I. Itten,et al.  Geometric and radiometric correction of TM data of mountainous forested areas , 1993, IEEE Trans. Geosci. Remote. Sens..

[18]  H. Du,et al.  Pixel-based Minnaert correction method for reducing topographic effects on a landsat 7 ETM+ image , 2008 .

[19]  Leonhard Blesius,et al.  The use of the Minnaert correction for land‐cover classification in mountainous terrain , 2005 .

[20]  P. Chavez.  An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data , 1988 .

[21]  Hermann Kaufmann,et al.  Comparison of Topographic Correction Methods , 2009, Remote. Sens..

[22]  Klaus I. Itten,et al.  A physically-based model to correct atmospheric and illumination effects in optical satellite data of rugged terrain , 1997, IEEE Trans. Geosci. Remote. Sens..

[23]  Michael P. Bishop,et al.  Remote Sensing and Geomorphometry for Studying Relief Production in High Mountains , 2003 .

[24]  S. Sandmeier,et al.  Radiometric corrections of topographically induced effects on Landsat TM data in an alpine environment , 1993 .

[25]  Panos Panagos,et al.  Monthly soil erosion monitoring based on remotely sensed biophysical parameters: a case study in Strymonas river basin towards a functional pan-European service , 2012, Int. J. Digit. Earth.

[26]  Fred A. Kruse,et al.  The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data , 1993 .

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

[28]  Craig A. Coburn,et al.  SCS+C: a modified Sun-canopy-sensor topographic correction in forested terrain , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[29]  S. Ekstrand,et al.  Landsat TM-based forest damage assessment : correction for topographic effects , 1996 .

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

[31]  A. Thomson,et al.  Effects of topography on radiance from upland vegetation in North Wales , 1990 .

[32]  A. S. Mahiny,et al.  Modelling forest stand volume and tree density using Landsat ETM+ data , 2010 .

[33]  A. Darvishsefat,et al.  Forest Type Classification Improvement Using Spatial Predictive Distribution Models , 2005 .