Volume XLI-B8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1003-1007, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-1003-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1003-1007, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-1003-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  24 Jun 2016

24 Jun 2016

OBJECT-BASED CLASSIFICATION AND CHANGE DETECTION OF HOKKAIDO, JAPAN

J. G. Park1, I. Harada1, and Y. Kwak2 J. G. Park et al.
  • 1Dept. of Informatics, Tokyo University of Information Sciences, 4-1 Onaridai, Wakabaku, Chiba-city, Japan
  • 2International Centre for Water Hazard and Risk Management (ICHARM), PWRI, 1-6 Minamihara, Tsukuba, Ibaraki, Japan

Keywords: Object-based, Relative DEM, Paddy, MODIS, SVM

Abstract. Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.