Many camera calibration methods for a non-metric digital camera have been proposed. However there is no standard procedure to evaluate an estimated distribution of image distortion directly. Calibration results are usually evaluated indirectly by such indexes as root mean square of residuals on image, three dimensional measurement errors of control points, or error estimates of obtained camera parameters. Therefore, we conducted a numerical simulation in order to examine capabilities of these indexes. In the simulation nine images were supposed to be acquired vertically to shoot control points on four layers disposed at regular intervals of the depth. Seven sets of control points were prepared, and these sets varied in the depth of the distribution of control points from 2/3 to 1/96 of the average camera height. Numerical simulation results show the limits of capabilities of these indexes. Error estimates of obtained camera parameters may be the most effective, however it is very difficult to interpret values of the error estimates obtained in a camera calibration. The authors propose that a set of numerical simulations should be conducted in a camera calibration to evaluate calibration results in addition to conventional evaluation by using the abovementioned indexes.
In this paper, a geometric correction considering the elevation for GMS S-VISSR data is described. In order to get high accuracy of the geometric correction in high elevation areas, the conventional geometric correction is improved in this paper. As a result, through the experiment using 4 scenes, the average and the maximum of errors in the proposed method are improved in comparison with the conventional method. Especially the each average of errors in the proposed method is less than or equal to 0.006 degree in the both direction of latitude and longitude, and the each maximum is 0.02 degree. Namely, it is shown that the proposed method has accuracy higher than the conventional method.
While the bamboo stands near residential areas have become less useful due to the lack of demand, they have survived on hillsides and spread into mountains without human cares over the past several decades. The purpose of this study is to estimate through satellite remote sensing where bamboo stands have been distributed. As bamboo stands grow quickly in spring and summer, the Landsat 5-TM data which had been observed on April 19, 1991, May 31, 1989, June 5, 1985 and August 4, 1995, were employed for their analyses. By using the decision tree classifier method, bamboo was separated from other vegetations. In consequence, we found that TM data observed on May 31, 1989 was most useful to extract the distribution of bamboo stands. And we clarified the most distinctive threshold for the bamboo classification by applying four indices (NDVI, B54, B65 and Band4) . As a result, it was found that bamboo stands with more than 5 pixels could be extracted with high accuracy in the case of Nishigyo-ku, Kyoto city.