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

Okada, Shiena, Khanal, Rajendra, Yoshimura, Chihiro, Saavedra, Oliver, Ryo, Masahiro
Landscape and ecological engineering 2019 v.15 no.1 pp. 63-74
alluvium, cloud cover, habitats, land cover, monitoring, remote sensing, river water, rivers, vegetation, Italy
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.