Automatic Approach for Assessing forest Disasters Utilizing Simulated High Resolution Satellite Imagery
On specifying a position for the damaged areas, it gives the information about the distance from city
®country
® town
® village and from forest group
® subgroup and their listing on forest information.
Figure.6 An example of the report
The range of the damaged areas can be selected from the results of the references. The damaged areas and satellite image can be indicated on the top of the screen and analysis can be done. FDAS user can automatically obtain the corresponding geographic location in response to the mouse location. The result about the damaged areas is displayed as table(s) in Excel document for reporting (Figure 6).
Conclusions
FDAS is developed considering the utilization of the high-resolution commercial remote sensing satellite, recently or soon to be launched, for forest management planning. The system utilizes the digital information for automatic reporting about the areas affected by disasters which was previously a manual process. This system can be installed on the notebook computer and used on-site and for the network communication as well. The analyzed aerial photographs were monochrome of single band with limited spectral information and therefore the amount of disaster expect the hillside/mountain stream disaster. Further improvement with increased precision are required for high-resolution satellite images. Image handling and preparation of supporting tool with advance image processing technique and integration with GIS will be more effective with high-resolution satellite image for the forest management purposes.
Acknowledgements
The authors are thankful to the Fukuoka Prefecture for their continuous support to supply the necessary information during the study.
References
-
Inamura M., Toyota H., and Fujimura S., 1982. Exterior algebraic
processing for remote sensed multispectral and multitemporal images,
IEEEE Trans. Geosci. Remote sensing, 20 (1), 112-118.
-
Yasuoka et al., 1988. Detection of Land-cover change from remotely sensed
image using spectral signature similarity, Proc. Ninth Asian Conf. Remote
Sens., Nov. 1988, pp. G-3-1-G-3-6.
