The merged image of the high spatial and the high spectral resolution images could provide more information than each individual image. In this study, the feasibility of using the merged image to extract bambootree mixed forests was examined. To achieve this, the merged image was generated from SPOT PAN and Landsat ETM+ satellite images by applying IBS (Intensity- Hue-Saturation) transform, PCA (Principal Component Analysis), Multiplicative transform, and Brovey transform, respectively. The spectral and spatial information was thus evaluated. Among the four merged methods, IHS transform was proved the most effective to present useful information from original images. Besides, using the created merged images with all four merging methods, the land cover type was further classified by the maximum likelihood classifier method, overall extraction accuracy for the bamboo forest was shown to be 80.9%, 75.3%, 74.2% and 78.7%, respectively. Since the classified result displayed the presence of the bamboo forest in mixtures with different tree crown, the results were further interpreted with the aid of the aerial photographs. As a result, bamboo in the mixtures were determined and the occupation percentages of bamboo crown were grouped into four categories : above 90%, 70-90%, 50-70% and 30-50%. For all four categories, reclassification was performed and the extraction accuracy for bamboo forest were obtained as 80.0%, 71.1%, 62.2%, and 53.3%. The corresponding bamboo area ratio in each category against the whole bamboo area occupied by this type, mixed vegetation were 32.4%, 31.3%, 20.5% and 15.7%, respectively. Therefore, it is clear that using the merged image, a great part of the bamboo-tree mixed forest could be extracted in addition to pure bamboo forest; and it is also possible for better assessment of the current bamboo distribution situations and future expansion tendencies in local or larger basin areas.
The Mid Niigata prefecture Earthquake (M6.8 at 17: 56 JST on October 23, 2004) triggered many landslides especially in Yamakoshi Village (currently merged into Nagaoka City), and blocked Imo River stream at several places, which caused landslide dam lakes.Urgent construction of channel works showed immediate effects by avoiding collapse of the landslide dams.However, high amounts of recorded snowfall in the winter brought another fear that collapse of the dams might occur when snow melts and water level of the dam lakes rise in the spring.Therefore, it was important to know how much snow was in the whole Imo River basin in advance. The Geographical Survey Institute measured the snow depth in the study area from the upper basin to the confluence of Uono River by comparing two airborne LIDAR (light detecting and ranging) data sets, which were collected before and after the snowfall.Average snow depth of the study area, which is 37.8km2in area, was 2.84m, and total volume of snow was 108.6 million cubic meters. Then total snow water equivalent volume was calculated as 49.6±5.1 million cubic meters using sample snow weight data collected at five points over the basin. These results were sent to the earthquake disaster countermeasures headquarters and other organizations concerned such as local government offices.