To detect non-thinned stands using very-high-resolution imagery, we assessed the relationship between the texture statistics derived from the gray level co-occurrence matrix (GLCM) and the density of Cryptomeria japonica stands. Because it was difficult to make the condition, like stand age and slope, consistent using real images and stands, simulated images were used. The results showed that each texture statistic had a unique pattern of variation, owing to stand density. Moreover, the amount of thinning affected the texture statistics. Because the values of the texture statistics varied according to the amount of it even if the stand density was the same, it was indicated that it was difficult to predict stand density using the texture derived from GLCM. Nevertheless, it should be possible to extract stands that have not been thinned using the texture statistics from very-high-resolution imagery, especially the homogeneity and the angular second moment.
This paper investigates adequate selection of hyperspectral components for estimating the degree of soybean bacterial pustule infection. According to a filed report, the higher the disease damage level is, the less the yield is expected.Based on highresolution hyperspectral images for different levels of damaged soybean fields, we have investigated the relationship between the soybean weight averaged for 100 seeds and the hyperspectral changes.In order to estimate the degree of damages from the hyperspctral data, we have tested 3 methods: (i) Estimation using reflectance of a single band based on a linear regression analysis.The RMSE was 2.0g. (ii) Estimation using normalized vegetation indices also based on a linear regression analysis.The RMSE was 2.1g. (iii) Estimation using neural network (NN) of a single-layer perceptron which has input nodes corresponding to the hyperspectral bands and a single output node.The RMSE was 1.5g, for estimating 100 seeds weight ranged over 16.7g to 22.7g.This paper indicates that NN is the most accurate among three methods to estimate the degree of soybean bacterial pustule infection.
Sub-pixel estimation of the corresponding positions in area-based matching is often conducted to obtain the precise locations of objects using stereo images. Such sub-pixel estimation methods as least squares matching and cross correlation method using sub-pixel shifted images require appropriate interpolation of the gray values of the window corresponding to the template. Since there are few reports on comparison of image interpolation methods in sub-pixel estimation accuracy, we decided to investigate performance of interpolation methods applied to sub-pixel estimation. This paper reports the preparatory experiment conducted in order to evaluate image interpolation methods quantitatively by using 54 diverse images. Three popular methods in remote sensing and digital photogrammetry: bi-linear interpolation (BL), bi-cubic interpolation (BC), and cubic convolution (CC) were investigated. The experiment results demonstrate that the interpolation accuracy of all three methods is correlated to texture measures of the image such as grey level difference vector measures and spatial frequency. Furthermore, the experiment results show that BC and CC can produce better interpolation results than BL, when an image has no noise or smaller noises. On the other hand, BL and BC can produce better interpolation results than CC, when an image has larger noises.
Remote sensing is technology which acquires the physical information of a measuring object indirectly based on the radiation acquired by a remote sensor. Therefore, to systematize the technology of converting the radiation to physical quantity is an important subject for remote sensing to spread in all the natural science fields. When acquiring vegetation and soil information by the satellite-borne and airborne remote sensor, accumulation of the knowledge in wide range temporal and spatial scale is required about the spectrum characteristic of a measuring object to the improvement in the measuring accuracy. For this reason, field measurements which measure the spectrum characteristic are indispensable to remote sensing research. The field spectrum radiometer needs to satisfy the measurement specification which is equivalent to the latest satellite-borne and an airborne sensor (hyper spectrum sensor etc.) . This paper reports the development of a portable line spectrum radiometer which can acquire line spectrum of the specific line of measurement target. Line spectrum radiometer can measure not only line spectrum but also three bands image of measurement target. Three bands image gives the detailed information about geometry and structure of measurement target, such as vegetation, background soil, shadow etc.
This research focuses on a network based data distribution and visualization system of Multi-functional Tranport SATellite (MTSAT) . Institute of Industrial Science (IIS) and Institute of Earthquake Research Institute (ERI) both at University of Tokyo have been receiving, processing, archiving and dis-tributing of MTSAT imagery with a direct receiving of High Rate Information Transmit (HRIT) since October 2006. A software package, mtsatgeo, is developed including radiometric calibration, geometric cor-rection and spatial subset, and they are available on a web-based data distribution and processing service accessed at http: //webgms.iis.u-tokyo.ac.jp/