Authors propose a parameter estimation method for a mixel problem in satellite images with coarse resolution. The method is based on an assumption that mixel class has its own probability distribution, and it can be calculated through convolution between pure class probability distributions near boundaries. In this paper, firstly the mechanism of mixel occurrence is explained through simulated images. Then, the proposed method for mixel decomposition is described. The result of the experiment using simulated images demonstrates that our method can decompose image's histogram and estimate each parameter of class probability distribution, especially mixel class ones, more accurately than a conventional method in terms of Kullback-Leibler entropy.
Drainage Direction Matrix (DDM) which can be generated from Digital Elevation Model (DEM) is useful information in order to analyze environment of watersheds. There are many studies about algorithm to make DDM from DEM, however, verification and modification, those are required to fit the river systems in the real world, are not easy. In this paper, algorithm for generating DDM using both DEM and existing river system map is proposed. By using the algorithm, the shapes of computed derived river system are similar with those of existing map information, if the streams information as input data are clearly delineated and prepared. As an application of the algorithm, continental scale DDM covering East Asia was generated using GOTPO30 and DCW with 30 seconds mesh size. There still require many corrections to have a perfect DDM because of difficulties to prepare perfect input data, however, the procedure to correct the errors is clear and easy to undertake.
In this study, we made thermal image observation and empirically discussed the relation between the environmental change and construction surface temperature. Also, we studied the heat balance model to predict the time serial temperature change of structure under the outdoor environment. As a result of this study, we were able to clarify that the environmental changes such as in the atmospheric temperature and solar insolation would exert great influence on the surface temperature of construction which had a internal transformation. We were also able to construct a heat balance model which can predict with relatively high accuracy the temperature change of construction reflecting these environmental conditions.