Cost benefit analysis, based on economic efficiency, has been frequently used in order to evaluate an economic feasibility of development projects, and environmental impacts assessment has been recently introduced for project evaluation with it. In addition, contribution to regional development, for which many methods are developed, is also an important aspect for project evaluation. However global environmental impacts are not considered in the above methodologies. In order to deal with them in the project evaluation procedure, a new model, using satellite remote sensing data, that represents the relationship between economic feasibility and global environmental impacts is proposed. And then its effectiveness is examined through its applications to some actual projects.
As the earth science activities for International Space Year (ISY) in Japan, a project for Sea Surface Temperature (SST) data sets has been carried out under the sponsorship by National Space Development Agency of Japan (NASDA) . Authors developed a algorithm for generation of SST data sets using MOS-1/VTIR data. 18 regional SST data sets around Japan Islands from 1989 to 1992 based on this algorithm were created by superimposing of multi-date VTIR data during about one week. The procedure of data processing consists of seven stages, radiometric correction, averaging of row data, cloud elimination, atmospheric correction using split-window equation, image registration, Masking of land area, color coding of SST value and data output. The SST distribution in data set was evaluated by comparing with actual observed sources. The results showed the validity for the investigation of SST distribution and the monitoring of ocean currents. Especially, the possibility for monitoring of the change of the Kuroshio Current was recognized.
This paper describes on a study for ganerating a vegetation map using an image interpretation of multi temporal Landsat TM imageries. The TM data obtained in spring and autumn seasons were used for this interpretation. The discrimination of vegetation types was achieved by the interpretation of the differences of color tone due to the differences of vegetation types which were introduced by the results of ground investigations. The vegetation map was generated through two kinds of interpretation steps. As the preliminary step, two major types of ever green vegetation and deciduous vegetation were identified using the TM imageries obtained in the autumn season. Next, more detailed vegetation types were discriminated using the color tone differences in the multi-seasonal TM imageries and the results of preliminary interpretation. Through this study, the image interpetation of satellite imageries was verified to be a practical and effective method for making a reasonal vegetation map, which may be expected to be used as one of the environmental information in some local regions.