Advanced search
1 file | 6.12 MB Add to list

Land cover mapping in urban environments using hyperspectral APEX data : a study case in Baden, Switzerland

Author
Organization
Abstract
High spatial resolution hyperspectral imagery has shown considerable potential for deriving accurate land cover maps in urban areas. In this paper, a new classification framework for mapping land cover in urban environments using high spatial resolution hyperspectral data was proposed. The proposed classification scheme was applied to map urban land cover using APEX data in the city of Baden, Switzerland. We first used the NDWI and NDVI indices to separate the land cover in the scene into three main classes: water, vegetation and non-vegetated surface. Then we partitioned the scene into many superpixels and applied classification using a SVM separately on the vegetation and non-vegetated surfaces. Soil was classified both in vegetation and non-vegetated surface, and these two soil results were merged in the final classification map. Shadows were initially classified in shaded vegetation surfaces and shaded non-vegetated surfaces, and then they were further classified into meaningful land cover categories. Our experimental results demonstrate that the proposed classification framework is well suited for mapping land cover in urban environments using high resolution hyperspectral data. Although the proposed method performs better than traditional methods in terms of soil classification accuracy, our findings emphasize that the soil class should be interpreted with caution in urban land cover maps derived from remote sensing data, even when high spatial resolution hyperspectral data are used. Results from this study also demonstrate that although shaded surfaces are generally classified as a single category in urban environments, in high resolution hyperspectral data, the shadows can be further classified into meaningful land cover classes with an acceptable accuracy.
Keywords
OBJECT-BASED CLASSIFICATION, RESOLUTION SATELLITE IMAGERY, SPECTRAL, MIXTURE ANALYSIS, AREAS, VEGETATION, SURFACES, INFORMATION, EXTRACTION, LANDSCAPE, HEIGHT, Urban land cover, Hyperspectral, Classification, Vegetation, Impervious, surface, Shadow, Soil, Image segmentation, Superpixel

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 6.12 MB

Citation

Please use this url to cite or link to this publication:

MLA
Chen, Fen et al. “Land Cover Mapping in Urban Environments Using Hyperspectral APEX Data : a Study Case in Baden, Switzerland.” INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 71 (2018): 70–82. Print.
APA
Chen, F., Jiang, H., Van de Voorde, T., Lu, S., Xu, W., & Zhou, Y. (2018). Land cover mapping in urban environments using hyperspectral APEX data : a study case in Baden, Switzerland. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 71, 70–82.
Chicago author-date
Chen, Fen, Huajun Jiang, Tim Van de Voorde, Sijia Lu, Wenbo Xu, and Yan Zhou. 2018. “Land Cover Mapping in Urban Environments Using Hyperspectral APEX Data : a Study Case in Baden, Switzerland.” International Journal of Applied Earth Observation and Geoinformation 71: 70–82.
Chicago author-date (all authors)
Chen, Fen, Huajun Jiang, Tim Van de Voorde, Sijia Lu, Wenbo Xu, and Yan Zhou. 2018. “Land Cover Mapping in Urban Environments Using Hyperspectral APEX Data : a Study Case in Baden, Switzerland.” International Journal of Applied Earth Observation and Geoinformation 71: 70–82.
Vancouver
1.
Chen F, Jiang H, Van de Voorde T, Lu S, Xu W, Zhou Y. Land cover mapping in urban environments using hyperspectral APEX data : a study case in Baden, Switzerland. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION. 2018;71:70–82.
IEEE
[1]
F. Chen, H. Jiang, T. Van de Voorde, S. Lu, W. Xu, and Y. Zhou, “Land cover mapping in urban environments using hyperspectral APEX data : a study case in Baden, Switzerland,” INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, vol. 71, pp. 70–82, 2018.
@article{8599261,
  abstract     = {High spatial resolution hyperspectral imagery has shown considerable potential for deriving accurate land cover maps in urban areas. In this paper, a new classification framework for mapping land cover in urban environments using high spatial resolution hyperspectral data was proposed. The proposed classification scheme was applied to map urban land cover using APEX data in the city of Baden, Switzerland. We first used the NDWI and NDVI indices to separate the land cover in the scene into three main classes: water, vegetation and non-vegetated surface. Then we partitioned the scene into many superpixels and applied classification using a SVM separately on the vegetation and non-vegetated surfaces. Soil was classified both in vegetation and non-vegetated surface, and these two soil results were merged in the final classification map. Shadows were initially classified in shaded vegetation surfaces and shaded non-vegetated surfaces, and then they were further classified into meaningful land cover categories. Our experimental results demonstrate that the proposed classification framework is well suited for mapping land cover in urban environments using high resolution hyperspectral data. Although the proposed method performs better than traditional methods in terms of soil classification accuracy, our findings emphasize that the soil class should be interpreted with caution in urban land cover maps derived from remote sensing data, even when high spatial resolution hyperspectral data are used. Results from this study also demonstrate that although shaded surfaces are generally classified as a single category in urban environments, in high resolution hyperspectral data, the shadows can be further classified into meaningful land cover classes with an acceptable accuracy.},
  author       = {Chen, Fen and Jiang, Huajun and Van de Voorde, Tim and Lu, Sijia and Xu, Wenbo and Zhou, Yan},
  issn         = {0303-2434},
  journal      = {INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION},
  keywords     = {OBJECT-BASED CLASSIFICATION,RESOLUTION SATELLITE IMAGERY,SPECTRAL,MIXTURE ANALYSIS,AREAS,VEGETATION,SURFACES,INFORMATION,EXTRACTION,LANDSCAPE,HEIGHT,Urban land cover,Hyperspectral,Classification,Vegetation,Impervious,surface,Shadow,Soil,Image segmentation,Superpixel},
  language     = {eng},
  pages        = {70--82},
  title        = {Land cover mapping in urban environments using hyperspectral APEX data : a study case in Baden, Switzerland},
  url          = {http://dx.doi.org/10.1016/j.jag.2018.04.011},
  volume       = {71},
  year         = {2018},
}

Altmetric
View in Altmetric
Web of Science
Times cited: