Urban Vegetation Cover Mapping with Vegetation Cover
Subclassification of vegetation areas
In this chapter , we propose the Subclassification of vegetation using VCRP image and multispectral image. Since it can be thought that the pixels with high VCRP have predominant information of subcategories , the pixel with high VCRP has been object for Subclassification. In tins case, it is necessary to clarify the threshold of VCRP form the spectral information, which can be sub classified into tree, grass and lawn. It should be elucidate the threshold as follow.
(a) In case of three categories(Tree, Grass, Lawn)
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(b) In case of four categories (Tree, Grass, Lawn, Unclassified) |
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Fig3. The rate of classification accuracy in Kawasaki area.
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Most likelihood methods are adopted n Subclassification. Supervisor had been set as tree, grass an lawn in vegetation map constructed by field survey. Figure 3(a) shows the classification accuracy of classification results on three categories. Accuracy was defined as concordance between Subclassification results and supervisor. It cab be found that the pixel with 60 percent or higher VCRP can be adequatable of Subclassification, on the point of 70 percent or higher classification accuracy. Figure 3(b) shows that of the case added category unclassified . the figure indicates that all pixel with 60 percent or les VCRP was unclassified . it can be also found that the pixel with 60 percent or less VCRP can be adequatable. From above two results , we can conclude that it should be proper to classify the pixels with VCRP 60 percent or higher into tree, grass and lawn.
Application to Kanazawa area
In order to investigate the practicability of the method, the method has been adapted to airborne MSS data ( spatial resolution :2 , observed on September 25, 1997) in Kanazawa. Figure 4 shows the classification results of Kanazawa area. E confirmed the propriety of this vegetation cover map comparing the field survey results carried out simultaneously. In this vegetation cover map, the roadside trees and garden trees located in the radius of a few meters as well as the lawn is identified as a result of classification . the small scale vegetations. Which cannot be classified pixels wise are expressed as the VCRP.
Fig.4 An example of vegetation cover map in kanazawa
Summary
Author have been developing the vegetation mapping with VCRP. Following items for putting to practical use of vegetation with VCRP were discussed. Practical use of the vegetation cover mapping using the multispectral data, it was clarified the method to quantity VCRP from arbitrary multispectral data the threshold of VCRPL suitable of the Subclassification into tree, grass and lawn. It was also showed that an example adapted the method to airborne MSS data in Kanazawa, Japan.
Acknowledgment
The airborne MSS data of Kanazawas is provided by "Pilot Project of Land Environment" a project in National Land Agency, Japan.
Reference:
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Donkyu YUN and Akira HOYANO : Index to extract VCRP in urban areas, jour . of the Remote. Sensing Society of Japan, Vol 18 No.3, 1998.
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Donkyu YUN, Akira Hoyano, Naoki, Shirai and Masahiro Setojima: A study on putting to practical use of urban vegetation mapping with VCRP, Part 1 and Part 2, Proc. Of the 25 the Japanese Conference on Remote Sensing, Nov. 1998, Koyoto, Japan.(Japanese).
