NDLI: Moving window-based topographic normalization of optical satellite imagery for forest mapping in mountainous terrain

Content Provider	IEEE Xplore Digital Library
Author	Dengkui Mo Fuchs, H. Fehrmann, L. Haijun Yang Kleinn, C. Yuanchang Lu
Copyright Year	2014
Description	Author affiliation: Burckhardt Inst., Georg-August-Univ. Gottingen, Gottingen, Germany (Dengkui Mo; Fuchs, H.; Fehrmann, L.; Haijun Yang; Kleinn, C.) \|\| Res. Inst. of Forest Resource Inf. Tech., Chinese Acad. of Forestry, Beijing, China (Yuanchang Lu)
Abstract	Relief has a significant impact on image classification in mountain areas because slope and aspect of the terrain together with the illumination geometry (solar zenith, solar azimuth angle and sensor position) make that one and the same land cover class has markedly different spectral signatures within one satellite image. Topographic normalization models help reduce intra-class spectral variability. This study proposes and evaluates a moving window-based rotation-correction topographic normalization model. We tested the algorithm with the latest Landsat 8 imagery in a region with very high forest cover in Shitai County, Anhui Province, China, which is characterized by a rough terrain with very steep slopes. Visual comparison and statistical analysis showed that the proposed method yielded better performance at a range of window sizes compared to uncorrected data or global correction methods. The heterogeneity of spectral signatures inside each land cover class could significantly be reduced, which may be partly due to the fact that a site-specific parameterization was used. Model performance was relatively stable over the tested range of window sizes. This new method for parameter estimation for topographic normalization is simple and straightforward, making this technique a suitable option for standard pre-processing of optical satellite imagery.
Starting Page	452
Ending Page	456
File Size	699582
Page Count	5
File Format	PDF
e-ISBN	9781479941841
DOI	10.1109/EORSA.2014.6927932
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Earth Satellites Parameter estimation Landsat 8 Lighting Rotation-correction model empirical parameter estimation moving window Integrated circuit modeling Remote sensing ASTER GDEM
Content Type	Text
Resource Type	Article

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