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Landscape and Ecological Engineering

, Volume 15, Issue 1, pp 63–74 | Cite as

Monitoring land cover change of a river-floodplain system using high-resolution satellite images

  • Shiena Okada
  • Rajendra KhanalEmail author
  • Chihiro Yoshimura
  • Oliver Saavedra
  • Masahiro Ryo
Original Paper
  • 61 Downloads

Abstract

In this study, a method was developed to monitor habitat structure in river-floodplain systems using high-resolution satellite images from 2010 to 2012 across a 30-km longitudinal section of the Tagliamento River, Northeast Italy. Three ortho-corrected RapidEye satellite images at 5-m spatial resolution and cloud cover of < 1%, with four spectral bands, namely, blue, green, red, and near-infrared, were used for land cover classification by converting pixel values into digital number (DN) distributions. The DN distributions for each band were clustered into separate classes based on correlations among all bands. The rate of unchanged habitat was further calculated as the intersection of all habitats divided by the area of the habitat of interest. The land cover categories were bare alluvium, river water, and vegetation. Bare alluvium was the dominant type, covering 55–75% of land. Vegetation and river water covered a relatively smaller area of the upper part and a larger area of the middle part of the Tagliamento River. The accuracy of this method was greater (> 89%) than that of the conventional unsupervised ISODATA method (> 83%) as river water and vegetation could be differentiated more accurately using this new method. The unchanged area was greater for river water than for vegetation and bare alluvium. These results indicated that habitat distribution changed spatially and temporally, especially for fluvial habitats, while the composition of habitat types was preserved in the middle reaches of the Tagliamento River. This method can be used to continuously and accurately monitor the large-scale spatiotemporal dynamics of habitat structures.

Keywords

Habitat turnover Spatio-temporal dynamics Land cover classification Digital number distribution Pixel value Tagliamento River 

Notes

Acknowledgments

The authors would like to thank Drs Yasuhiro Takemon, Kozo Watanabe, Takeo Tadono and Sayaka Yoshikawa for their constructive comments, which helped us polish this manuscript. This research was supported by Japan Society for the Promotion of Science Kakenhi grants (numbers JP25241024, JP15K00592) and partly by JST/JICA, SATREPS.

Supplementary material

11355_2018_361_MOESM1_ESM.docx (681 kb)
Supplementary material 1 (DOCX 681 kb)

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Copyright information

© International Consortium of Landscape and Ecological Engineering and Springer Japan KK, part of Springer Nature 2018

Authors and Affiliations

  • Shiena Okada
    • 1
  • Rajendra Khanal
    • 1
    Email author
  • Chihiro Yoshimura
    • 1
  • Oliver Saavedra
    • 2
  • Masahiro Ryo
    • 1
  1. 1.Department of Civil and Environmental Engineering, School of Environment and SocietyTokyo Institute of TechnologyTokyoJapan
  2. 2.Civil and Environmental Research CenterUniversidad Privada BoliviaCochabambaBolivia

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