Experimental programs for geologic classification by geomorphological profiles were developed. A geomorphological profile indicates undulations and registance of a rock's characteristics, so this is one of the most important factors for the photogeological interpretation. This study processed by following method. 1) Segmentation of objective area into level ground and mountainous district, further segmentation of mountainous district into several mountains 2) Make geomorphological profile for each mountain, profiles maked for four directions (N-S, E-W, NE-SW, NW-SE) at the length of 1.4 km across the DTM 3) Considered statistical features of profile are following: relief energy, number of valleys and mountains, fourier transformation, second differential value, and others 4) Classification of geologic units by discriminant analysis In the result, the method by a geomorphological profile is partially applicable to the geologic classification.
A classification method which takes into account not only spectral but also spatial features for LANDSAT-4 and 5 Thematic Mapper (TM) data is proposed. Due to the increased spatial resolution of TM (30m compared with 80m for MSS), the number of ground cover spectral classes which are included in the Instantaneous Field of View (IFOV), decreases comparatively. This implies that spatial-spectral varibility for TM data increases in comparison to MSS. Therefore, treatment of the spatial-spectral variability existing within a region is more important. Standard deviations in small cells, such as 2x 2, 3x 3 and 4 x 4 pixels, were used as measures to represent the spatial-spectral variabilities. This information can be used together with conventional spectral features in an unified way, for the traditional classifier such as the pixel-wise Maximum Likelihood Decision Rule (MLDR). I focused my attention on the classification of new .clear cuts and alpine meadows which were very close in spectral space characteristics and difficult to distinguish them by conventional methods. There was a substantial improvement in overall classification accuracy for TM forestry data. The probability of correct classification;PCC for the new clearcuts and the alpine meadows classes rose by 7% to 97% correct. The confusion between alpine meadows and new clearcuts was reduced from 9% to 3%.
The SAR (Synthetic Aperture Radar), one of the microwave imaging radars, can offer a very high resolution image. It works effectively all day long in any weather condition without blocking by clouds. However, the conventional knowledge with visible light sensors can not be applied to the interpretation of SAR image, because of the property difference between two images. Our final purpose is to find an interpretation technique of undefined objects on the SAR images. We have examined one method to extract texture features from SAR images so far. Improving GLCM (Gray Level Co-occurrence Matrix) method, we propose Two Step GLCM method. In this new method, the GLCM method is applied double to one image with different conditions upon the partial images. This analysis yields an improved image features in comparison with the conventional simple GLCM method. Both micro-and macro-scopic image features are possible to be obtained separately. Further, the higher order features can be found on the image also. The authors had a confirmation that Two Step GLCM method is effective for complex texture pattern analysis using model patterns and SAR images.
Sophisticated spaceborne images with high spatial resolution and stereoscopic viewing capability have been available for photogeological applications since the SPOT Satellite-1 was launched in 1986. In these applications, the preliminary stage of onshore exploration for non-renewable resources requires users to select the most appropriate spaceborne image to minimize the exploration cost and to find the most promising field. From this viewpoint, it is necessary to quantitatively evaluate the practical quality of the available images. This paper describes the results obtained through the comparative study on the assessment of the spatial resolution and effectiveness of the stereoscopic viewing capability of Landsat and SPOT images of the same scale, covering identical areas in the Yerington area, Nevada. The study mainly involves photo-interpretation of the relative drainage density which seems to be directly related to the limits of the terrain feature extraction. The visual interpretation revealed that the extracted drainage density from SPOT images was much higher than that from Landsat TM images because of higher spatial resolution and stereoscopic viewing capability. So far as SPOT images on a basic scale of 1 : 200, 000 are concerned, the interpretation led to the conclusion that multispectral images did not differ much from panchromatic images within the practical limits of interpretation. Considering geological and geomorphological information obtained in this study area, it is concluded that the SPOT multispectral image is, at present, the most appropriate for visual photogeological interpretation.
This paper proposes a simplified geometric optics model for estimation of surface reflection of the sky radiation, assuming that the sea surface consists of small facets. This model enables the correction process of surface reflection to be much easier and less time-consuming, incorporating roughness sensitivity in reflective process. This paper also introduces a typical noncoherent scattering model by Wu and Fung in appendix. Finally, comparison of estimated reflection of the sky brightness temperature is made among above two models and Fresnel reflection model which does not take into account the roughness effect of the sea surface. Noncoherent scattering model resulted in the largest estimation and Fresnel reflection model the lowest one. The defference of estimated reflection among these three models ranges from 3-6 K and larger differences are seen at higher incidence angles. However, no reasonable explanation are available for these differences at present, since the surface reflection is highly dependent not only on the specific reflective process in each model but also on sea surface state, sky brightness temperature pattern, dielectric properties of sea water, etc. Less one tenth of calculation time of noncoherent scattering model was attained in geometric optics model, and this model is of higher practical potential application to the correction of surface reflection, however, detailed comparison is still prerequisite among models.