DOI: 10.1016/j.jag.2013.02.003
Scopus记录号: 2-s2.0-84880113869
论文题名: The effect of atmospheric and topographic correction methods on land cover classification accuracy
作者: Vanonckelen S ; , Lhermitte S ; , Van Rompaey A
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2013
卷: 24, 期: 1 起始页码: 9
结束页码: 21
语种: 英语
英文关键词: Atmospheric correction
; Bi-temporal
; Classification accuracy assessment
; Land cover mapping
; Landsat
; Mountain areas
; Topographic correction
Scopus关键词: accuracy assessment
; atmospheric correction
; error correction
; image classification
; land cover
; Landsat
; mapping
; model test
; model validation
; mountain region
; pixel
; remote sensing
; satellite imagery
; topographic effect
; Carpathians
; Romania
英文摘要: Mapping of vegetation in mountain areas based on remote sensing is obstructed by atmospheric and topographic distortions. A variety of atmospheric and topographic correction methods has been proposed to minimize atmospheric and topographic effects and should in principle lead to a better land cover classification. Only a limited number of atmospheric and topographic combinations has been tested and the effect on class accuracy and on different illumination conditions is not yet researched extensively. The purpose of this study was to evaluate the effect of coupled correction methods on land cover classification accuracy. Therefore, all combinations of three atmospheric (no atmospheric correction, dark object subtraction and correction based on transmittance functions) and five topographic corrections (no topographic correction, band ratioing, cosine correction, pixel-based Minnaert and pixel-based C-correction) were applied on two acquisitions (2009 and 2010) of a Landsat image in the Romanian Carpathian mountains. The accuracies of the fifteen resulting land cover maps were evaluated statistically based on two validation sets: a random validation set and a validation subset containing pixels present in the difference area between the uncorrected classification and one of the fourteen corrected classifications. New insights into the differences in classification accuracy were obtained. First, results showed that all corrected images resulted in higher overall classification accuracies than the uncorrected images. The highest accuracy for the full validation set was achieved after combination of an atmospheric correction based on transmittance functions and a pixel-based Minnaert topographic correction. Secondly, class accuracies of especially the coniferous and mixed forest classes were enhanced after correction. There was only a minor improvement for the other land cover classes (broadleaved forest, bare soil, grass and water). This was explained by the position of different land cover types in the landscape. Finally, coupled correction methods showed most efficient on weakly illuminated slopes. After correction, accuracies in the low illumination zone (cos β ≤ 0.65) were improved more than in the moderate and high illumination zones. Considering all results, best overall classification results were achieved after combination of the transmittance function correction with pixel-based Minnaert or pixel-based C-topographic correction. Furthermore, results of this bi-temporal study indicated that the topographic component had a higher influence on classification accuracy than the atmospheric component and that it is worthwhile to invest in both atmospheric and topographic corrections in a multi-temporal study. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79822
Appears in Collections: 气候变化事实与影响
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作者单位: Division of Geography, Katholieke Universiteit Leuven, Celestijnenlaan 200E, BE-3001 Heverlee, Belgium; Royal Netherlands Meteorological Institute, Wilhelminalaan 10, AE-3730 De Bilt, Netherlands
Recommended Citation:
Vanonckelen S,, Lhermitte S,, Van Rompaey A. The effect of atmospheric and topographic correction methods on land cover classification accuracy[J]. International Journal of Applied Earth Observation and Geoinformation,2013-01-01,24(1)