The dominant species are Rhizophora stylosa and Bruguiera gymnorrhiza in the mangrove forest in Okinawa. Measurement of seven stand parameters, tree hight, diameter at breast hight, stem volume, crown area, stand volume, mixture ratio of R. stylosa and stand density for mangrove forest was carried out at fourteen plots in Ishigaki Island and Iriomote Island. Correlation coefficients between seven stand parameters and many ratios and indexes calculated from TM data of Landsat 5 at fourteen sample plots, were obtained and arranged in Table 2. Significantly high correlation was recognized between stand parameters and some ratios and indexes. Relationships between these ratios and indexes, sand parameters might be linear or curvilinear. So it was considered that some ratios and indexes were useful to estimate stand parameters for mangrove forest in Okinawa.
In this paper, we consider classification methods using neural networks for multi-frequency polarimetric SAR data. This data was obtained by SIR-C inside Space Shuttle (Space Radar Lab I) . We propose a learning algorithm for competitive neural networks and find the most effective feature vector. The proposed algorithm is as follows: First, weight vectors are trained by one of three basic algorithms (LVQ1, LVQ2.1, and OLVQ1) . Next, they are re-trained and tuned up by the LVQ2.1 for a narrower window area around the category boundaries. In these experiments, we demonstrate the re-training effects. Then nine types of feature vectors are adopted to the classification methods, which in turn are compared to the conventional methods such as the maximum likelihood method and the layered neural networks (BP) with respect to average accuracy, classification image quality, and computational time. As a result, the proposed method, especially, OLVQ1 + LVQ2.1 outperforms other methods and the feature vector which is composed of back-scattering power of cross polarization for L and C bands generates the best classification accuracies and noiseless images.
In recent years, disaster is practically an annual occurrence in Japan. There are reasons in following, that is limited in narrow country, that is located in zone of much rain and heavy snow and frequent earthquake, that is made the steep terrain and complex, that is kept in the remarkable development of natural. These disaster occurs that the movement of earth and the produce of human life which the natural phenomena are crossing. Accordingly, it is important that is examined to the item of soils and land uses for make clear the disasters. The survey to these wide land use was taken to the remote sensing by satellite in the recent year. The techniques of remote sensing makes the most of the data that is transmitted as the data to obtain the information of ground, and it is able to examination not only the data of points in the surface ground but also the data of face in the wide land use. For these reasons, this report is adopted the data that is explained to the object from the satellite image data used the multiplex information, and is made the detailed thematic map for the classification of surface ground.
Conventional GIS software provides information such as answers to queries by displaying two dimensional map images with a monitor. Users are usually required to make some efforts in interpreting or comparing the results with real landscape or world situations. This study proposes a more natural or user friendly interface can be devloped which can reduce the distance between the information provided by GIS and the real situations, by fusing real landscape images with three dimensional spatial data on the real-time basis. An experimental GIS user interface was developed based on this idea to demonstrate the possiblities.
Attention is being given to the development of photogrammetry to get information on the exterior orientation parameters, that is to say the position and attitude, of a camera without using any control points. The exterior orientation of a camera could be determined by using GPS and an optical gyro. Such equipment, however, is not widely diffused due to the price aspect. This paper is the fundamental study to get information on the position and attitude of a camera using a vibration gyroscope and accelerometer. This paper deals with various experimental results regarding the performance and experiments of this system using a vibration gyroscope and accelerometer. After the experiment, we could obtain a basis sample by the vibration gyroscope and accerelometer used. For the application to the close range photogrammetry, this system could give the camera's position and attitude. As a result, no control point photogammetry could be made, but efficiency was remarkable.
This study assessed the feasibility and accuracy of a laser scanner system on board a helicopter for three dimensional measurement of urban features. The spatial accuracies of the system for horizontal and vertical directions were approximately 100 cm and 10-25 cm (standard deviation), respectively. The large horizontal error was considered as the result of insufficient control over the system attitude during the flights. Due to the digital data acquisition by helicopter and the automated nature of data processing, the time required to acquire and process the data for an area of two square km was significantly shorter than conventional methods, and approximately 30 minutes and two hours, respectively, which may be considered adequate for disaster response operations.
3 dimensional representation of local spatial data, such as bird's eye view, has been attracted attention because of these 3D maps gives realistic impression. However, these 3D maps are influenced by direction, e.g.a back parts of high building are not represented. With this in motive, the authors have been concentrating on developing the radial oblique projection which is the new 3 dimensional representation of local spatial date. This paper presents 3 dimensional representation of buildings at road section using the radial oblique projection.