Journal cover Journal topic
Proceedings of the International Association of Hydrological Sciences An open-access publication for refereed proceedings in hydrology
Journal topic

Journal metrics

CiteScore value: 0.9
CiteScore
0.9
SNIP value: 0.504
SNIP0.504
IPP value: 0.81
IPP0.81
SJR value: 0.296
SJR0.296
Scimago H <br class='widget-line-break'>index value: 11
Scimago H
index
11
h5-index value: 19
h5-index19
Volume 368
Proc. IAHS, 368, 51–56, 2015
https://doi.org/10.5194/piahs-368-51-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Proc. IAHS, 368, 51–56, 2015
https://doi.org/10.5194/piahs-368-51-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  06 May 2015

06 May 2015

Application of ZY-3 remote sensing image in the research of Huashan experimental watershed

K. Guo, J. Wang, and Y. Wang K. Guo et al.
  • College of Hydrology and Water resources, Hohai University, Nanjing, Jiangsu Province, 210098, China

Keywords: ZY-3, remote sensing, hydrological experimental watershed, land use

Abstract. Spatial information of Huashan experimental watershed, such as a DEM and land-use types, is extracted from ZY-3 images and studied for digital watershed construction and hydrological simulation. A high-accuracy DEM is extracted from the ZY-3 stereoscopic image. Water body information is extracted from high-accuracy fused images by the method of supervised classification with object-oriented techniques. Land-use types are extracted by the decision tree classification method based on mono-temporal fused image and multiple-temporal multispectral images. The construction of the classification decision tree of the mono-temporal images is based on a multivariate statistical analysis method and the construction of classification decision tree of the multiple-temporal images is based on the CART algorithm. The land-use information which meets the accuracy needs is synthesized into a final land-use map. The accuracy of the final land-use map was evaluated; the overall classification accuracy was 92.04% and the Kappa coefficient was 0.9030.

Publications Copernicus
Download
Citation