We propose a method for classifying and monitoring the wetland vegetation in a wide area using satellite remote sensing and a geographical information system (GIS). The study area is in Sarobetsu Mire, northern Hokkaido, Japan. The method is expected to contribute to wetland conservation from its ability to provide spatial maps of basic information. It classifies wetland vegetation by using multivariate analysis of satellite images based on groundtruth data, spectroscopic data and flora data. We used stepwise discriminant analysis to classify satellite images from Landsat (7 bands) and ASTER (9 bands) into wetland vegetation of 7 classes : sphagnum, sedge, dwarf bamboo, reed and three mixed classes. The classification maps drafted from the satellite images were found to accurately reproduce the actual vegetation. An increase in dwarf bamboo vegetation and decline in sphagnum vegetation were quantitatively identified from comparison between the 1991 and 2000 Landsat data. A monitoring method that can analyze vegetation changes in greater detail was proposed. This method sets monitoring sites and monitoring lines by superimposing polygonal and linear data on a satellite image.

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This paper discusses about the technical issues on the production and utilization of digital vegetation maps using GIS. The vegetation map is one of the important spatial information in the field of natural environmental studies, and is frequently used for wildlife habitats conservation, monitoring works as well as environmental assessment. GIS plays an important role on the above analysis, and it becomes a common tool not only for the GIS specialists but also the common end-users who analyze the environmental phenomena with various maps.
As methodological discussions on the vegetation mapping with GIS, it is firstly emphasized that the digital ortho-rectified aerial photos and high resolution satellite images can contribute to classify and map the vegetation at a scale of 1 : 25, 000 effectively and efficiently. The ortho photos are very effective, and they can be easily used as background images for the visual interpretation on the PC-displays. The advantages of digital ortho include that ; the interpreters are free to select the scale of presentation according to the minimum mapping unit of vegetation. The alternative is to apply the high resolution satellite images such as QuickBird or IKONOS. They can provide the images having almost same spatial resolution with ortho photos. The superior of these images is that the multi-spectral analysis can be performed for both manual interpretation and automated classification. More recently, it becomes clear that the object oriented image classification method is more effective than the pixel based procedure for the high resolution satellite images.
The final discussion is regarding the contents of attribute in conjunction with vegetation map. The detail records of vegetation survey in the field have been stored in the database with their geographical locations, so that various levels of users can select the necessary information according to their requirements. The multi-layer structure database of GIS makes it possible with much flexibility. For the appropriate utilization and diffusion of vegetation maps, the metadata which describe the mapping process and methodology of each vegetation map are highly recommended.

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Vegetation maps and forest inventory maps contain spatial and attribute data that can be useful in analyzing forest landscapes and ecology. The value of these data would be enhanced if the two types of maps could be accurately combined into an integrated vegetation map. In this research, IKONOS high resolution satellite data was utilized to generate an integrated vegetation map. The research was conducted at Dodaira, in the eastern part of the Tanzawa-Oyama Mountains, Kanagawa Prefecture, west of Tokyo. The spatial boundaries of the integrated vegetation map were extracted by IKONOS image segmentation analysis. The segmentation scheme was based on standards employed in forest inventory maps and the Ministry of Environment' s vegetation maps, and the boundaries were adjusted and aligned as required. When segmentation was complete, the vegetation and attribute data from the two maps was then imposed on the integrated map. This system was able to resolve problems with slight differences in boundary lines, and also succeeded in unifying and integrating the various data contained in the two maps.

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Physiognomic and species compositional criteria that form a basis for correct use of the vegetation map are compared and discussed in this review. Systematizing classification systematizing of vegetation units was done by the criterion of species composition such as association would have not only a syntaxonomic attribute but also attributes of the synchorology, synmorphology and syndinamic. Moreover, description and understanding of an ecological characteristics of various attributes of each vegetation unit was necessary when the vegetation diagnosis and land evaluation were done from the vegetation map for which the phytosociological units were made as legends. However, it is not necessary for users to understand the ecological characteristics of vegetation units for effective use of the vegetation map. Ecological research related to classification of the patterns of vegetation landscape using the vegetation map are discussed further as the classification criterion of each vegetation complex in the symphytosociology or symphytocoenology developed from the phytosociology. Geosigmassociation is explained as a basic unit of vegetation landscape. Some results of the landscape ecological research related to the analyses of the spatial structure of vegetation landscape and of the interrelation are also shown.

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