A circular target on a plane is projected as an ellipse onto an oblique image. This paper reports an experiment conducted to evaluate measuring methods of elliptical target location by using simulated images of various sizes, eccentricities, and rotation angles of elliptical targets. Three popular measuring methods in digital photogrammetry : unweighted centroid method using a binary image created by thresholding (BCM), weighted centroid method (WCM), and least squares matching (LSM) were investigated. The experiment results show that BCM is robust against flatness and rotation of a target, and image noise. However, BCM cannot produce more accurate measuring results than WCM and LSM. Meanwhile, the results demonstrate that WCM is robust against flatness and rotation of a target, and WCM can achieve the most accurate measurement when a target image has no image noise. However, the measuring error of WCM would be proportional to the magnitude of image noises, and WCM would be unable to provide the best measuring results when a target image has larger image noises. The results indicate that LSM is rather robust against image noise, but very sensitive to flatness and rotation of a target. Moreover, the results show that BCM using an enlarged target image by bi-linear interpolation should be a good measuring method on accuracy and robustness against flatness and rotation of a target, and image noise.
A method for determination of an appropriate support length of Duabechies base function based Multi-Resolution Analysis (MRA) for moving target detection from remote sensing satellite images is proposed. The method based on root mean square difference between original and reconstructed image from just a low frequency component from MRA. Also one of applications of the method for detection and tracking of moving targets, typhoon and boundary between warm and cold current observed from satellite remote sensing images is shown. It is found that the proposed method allows to detect and to track for moving targets of a typhoon and a boundary in the time series of GOES images.
The authors have been concentrating on developing convenient 3D measurement system using consumer grade digital cameras, and it was concluded that the system is expected to become a useful 3D measurement system for the various close range application fields. There were some issues, however, to realize a convenient photogrammetry using consumer grade digital cameras. One of issues is acquisition of accurate scale factor since pixel coordinates should be transformed into image coordinates using scale factor. Scale factor was generally computed using pixel numbers in a line on the display and sensor size which was given from manufacturer's specifications. Nevertheless, it became impossible to obtain sensor size for consumer grade digital cameras even from manufacturer's specification, and scale factor is unavoidably estimated from the sensor type such as 1/2 inch CCD sensor. On the contrary, focal length of digital cameras can be obtained from Exif file which is recorded on the image. In these circumstances, Exif dependent (E-D) calibration was proposed in this paper. The most remarkable point of the E-D calibration is its ability to calculate both of exterior and interior orientation parameters without scale factor or manufacturer's specifications.
PALSAR (Phased Array L-band Synthetic Aperture Radar) was installed on the Japanese ALOS (Advanced Land Observing Satellite) that was launched on 24 January 2006. This is the first satellite regularly operated with fully polarimetric SAR in the world, and is considered useful for monitoring forest and biomass, as well as topography and land use. Forest cover types and stand volume classifications were produced for Mt. Asama using unsupervised and supervised classifications from the backscatter matrix using polarimetric PALSAR data. The Mt. Asama region was selected for study because of its gentle geographic features and large number of representative Japanese larch (Larix kaempferi), red pine (Pinus densifolia), and sub-alpine conifer (Abies mariesii and Tsuga diversifolia) forests. The unsupervised classification data allowed the forest region to be distinguished from fields, rice fields, pastures, residential areas, roads, and bare ground. We also produced forest cover type and volume classification images using a supervised classifier with GIS and field data, with a classification accuracy of 11.0-56.5%. The accuracy of highest volume classes was 301-450 m3/ha (56.5%) and 451-800 m3/ha (49.6%). This may have been because the influence of geographic features such as slope azimuth and ridges were larger than that of forest cover types. Therefore, polarimetric PALSAR data are suitable for monitoring deforestation and detecting changes in forest cover types in a homogenous, large forested region without complex mountainous geographic features.
This paper presents a validation of Land surface temperature (LST) product retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data. For this purpose we used a scheme which validates LST product indirectly based on the emissivity validation derived from Atmospheric Infrared Sounder (AIRS). In addition we also made LST and emissivity spatial averaging model for compensating the difference of the spacial resolution between sensors. The validation result shows that MODIS LST product involves the emissivity bias of 0.023 and LST bias of -1.3K in Railroad Valley Playa and the emissivity bias of 0.019 and LST bias of -1.8K in Harvard Forest.
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