Remote sensing in a broad sense has been utilized in geology and natural resources exploration since early 20th century. Conventional photogeologic interpretation, which can be applied to airphotos and satellite imagery, is a practical method to know geologic structures and rock types. Multispectral data in the visible, near-infrared and thermal infrared regions such as LANDSAT TM, JERS-1 OPS, and ASTER are useful for lithologic mapping. Various data analysis algorithms have been developed to characterize multispectral response patterns. Recently, hyperspectral data become available, and allow us not only lithologic discrimination but also rock and mineral identification. SAR images are also useful for photogeologic interpretation particularly for the areas with low cloud-free probabilities. SAR interferometry and polarimetry are new tools for geologic mapping and surface monitoring. Lunar and planetary exploration projects are another important trend in Japan.
The Kalpin Uplift, located along the NW edge of the Tarim Basin in China, is a typical place to study the stratigraphy and structural features of the oil-bearing Paleozoic sequences buried underneath the Basin. Vegetation over the Uplift is extremely sparse and the contrast between lithological features of the sedimentary sequences is excellent in satellite images. The fundamental structure of the Uplift is characterized by a series of ENE-WSW to E-W trending folds and thrust faults, which consist of the thin-skinned thrust system, and Paleozoic sedimentary sequences are repeatedly exposed on the terrain surface. Brief interpretation of false color composite imagery gives an impression that lateral change in the lithology is uncommon over the Uplift, but the detailed stratigraphic analysis of geological units using the ratio images of Landsat TM reveals that some sequences show limited distribution and the lithology of a sequence laterally changes. Specific band combination of the ratio image is selected to discriminate individual rock types based on known spectral features of minerals. The ratio images are combined with Landsat TM band 4 to create a new composite image that enhances lithological features without the loss of geomorphologic detail. Geological phenomena revealed by the correlation of the units are found to be concordant with the evolutional history of the whole Kalpin Uplift, showing the usefulness of the approach focusing on the spectral features of rocks and minerals.
This study focuses on the limitations and benefits of satellite images when scouting topographically complicated desert area for seismic planning purposes. The study area is located in the Eastern Junggar Basin of the People's Republic of China. Due to restrictions in operations and environmental considerations, the above area is still unmanageable in terms of petroleum exploration. In order to understand the general features of the desert, the sand dunes were classified into 17 units using JERS-1 OPS images, on the basis of their Type, Wavelength and Relief Energy. Furthermore, Ratio between Wavelength and Relief Energy was newly defined and mapped as an index for planning purposes. Finally the entire study area was classified into four zones according to appropriate seismic source and operational difficulties. Detailed knowledge of complex dune types obtained from image interpretation allowed generation of a base map upon which a network of seismic lines can be planned to provide a reasonable reconnaissance grid in the study area. The results showed that satellite images can provide a variety of information which is vital when planning seismic surveys in desert areas.
Alteration mineral discrimination is important for natural resources exploration. Spectral patternanalysis is useful for altered mineral discrimination. This analysis is composed of Gray Scale Log Residual (GSLR) method and Spectral Pattern Index (SPI). These technique have the advantage that the processed results can be easily interpreted by a geologist for the purpose of altered mineral discrimination. The simulation for mineral separation was proccessed with spectral library (NASA/JPL) and ASTER simulation data from AVIRIS data of Cuprite, Nevada, using spectral pattern analysis. Mineral discrimination of ASTER data was discussed using degree of separation as standard. SPI image using SWIR Bands of ASTER simulation data successfully showed each mineral alteration zone in hydrothermally altered area. Adequate band combinations and threshold of separation standard can be showed.
We have developed the new effective data processing manner for ASTER VNIR-SWIR-TIR data. The disturbing factor in classifying rock type and mineral species using satellite data.is the product reflecting a mixture of various materials, which contains abundant noises. The manner estimates substances in each pixel by spectral pattern recognition with fuzzy inference, independently of channel number and end-member number. In addition, the results can be compared with other areas. Then, applying the manner in the Cuprite Hill area, Nevada, U.S.A., mineral distribution maps of the specific minerals were prepared and the applicability of method was assessed correlating with the existing geological data. The image data used in this study were the adjusted ASTER simulation image prepared by air-borne AVIRIS, TMS and TIMS. The band to band registration was also adjusted. In the case of Cuprite Hill area, five end-members were selected as follows according to the geological information. E/M1 (Hematite), E/M2 (Alunite), E/M3 (Kaolinite), E/M4 (Quartz), E/M5 (Buddingtonite). Results were compared with themineral assemblage of the alteration zone. Distributions of end-members showed a good correspondence with alteration zoning. A quantitative estimation was conducted using analysis results of ground survey that had been carried out by JGI (1990), MMAJ (1989, 1990), Abrams and Hook (1995) and Shipman and Adams (1987). Average coincidence between analysis results of ground survey and processed results was 73%.
Recently, many airborne hyperspectral sensors have been developed for studying and managing the Earth's resources. Furthermore, in the next century several spaceborne sensors are expected to be available. The hyperspectral sensors, that is, imaging spectrometers acquire spectral data in many contiguous narrow spectral bands for each picture element (pixel). Such spectral data can be compared with laboratory and field spectra to identify terrestrial materials. Data processing of hyperspectral imaging data applying to geologic survey needs to be established for such future spaceborne sensors. The data processing consists of two steps-retrieval of surface reflectance and surface mapping based on spectral features. First, the retrieval process estimates column water vapor in pixel by pixel basis, and then surface reflectance is retrieved based on estimated water vapor condition under the assumption of a horizontally uniform Lambertian surface. The estimation of water vapor was examined for 0.94 and 1.14pm water vapor absorption bands. This retrieval of surface reflectance is based on a radiative transfer code, MODTRAN without any external information on surface materials. The retrieval process was applied to a set of hyper spectral imaging data acquired by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over Cuprite mining district, Nevada. The estimated water vapor from 1.14, um seems to be less affected by reflectance of surface materials in water absorptions bands than that from 0.94.um. Furthermore, two alteration minerals, alunite and kaolinite are mapped based on the retrieved reflectance data. The retrieved surface reflectance and mineral map were compared with a detailed alteration map by Ashley and Abrams (1980) and laboratory spectra of rock samples from Cuprite. Generated mineral map clearly shows alunite and kaolinite distribution on the alteration zoning by Ashley and Abrams (1980). The results have demonstrated hyperspectral imaging data has a capability to add information on surface geology.
ASTER, which is going to be launched in December 1999 on NASA's polar orbit platform called "Terra", will be the first spaceborne thermal infrared multispectral remote sensing system with spatial and spectral resolution adequate for geologic applications. In this paper, the relationship between thermal infrared spectra of igneous rocks convolved into ASTER spectra, and chemically determined SiO2 contents was analyzed with a backpropagating neural network approach to derive an equation for a spectral estimation of SiO2 content. The validity of the derived equation against the remotely sensed emissivity spectra by ASTER was discussed. The results suggested the high possibility of a successful estimation of SiO2 content in the surface igneous rocks using ASTER data.
MIRACO2LAS is an airborne CO2 laser profiling system that measures bidirectional reflectance for 100 separate wavelengths between 9.1 and 11.2, um. The MIRACO2LAS was deployed over the Mount Fitton area in South Australia to establish the types of minerals that can be mapped, and to understand better the role of high spectral resolution remote sensing at thermal infrared (TIR) wavelengths, independent of the complicating effects of temperature that beset passive, multispectral TIR systems. The airborne data were processed to ground reflectance and compared with laboratory spectra of samples collected during the associated field campaign. The reduced airborne data showed good correlation with the laboratory spectra. The minerals apparent in the reduced airborne data include: quartz, K-feldspar, plagioclase, amphibole and kaolinite. The diagnostic spectral signatures of these minerals are all narrow and thus theoretically not detectable using broader band passive systems such as TIMS. Surface temperature and pseudo-emissivity images, derived from TIMS radiance data using a Residual and a Emissivity, showed that the surface temperature was well separated from the emissivity information. Furthermore, the resultant six-point alpha emissivity spectra from different types of geology showed spectral shapes consistent with laboratory measurements of corresponding rock-chip samples.
The AIRSAR system simultaneously records microwave data in P-band (68cm), L-band (24cm) and C-band (5.6cm), and measures the complete scattering matrix for each ground cell, thereby allowing the calculation of all polarizations for each frequency. This study aims at exploiting the ability of AIRSAR data to provide information about the terrain for mineral exploration, which is otherwise unobtainable from optical remotely sensed and other geophysical datasets. Two study areas were selected from South Australia for this purpose;Tarcoola, poorly outcropping granite terrain with high potential for Au and base metal mineralisation;Hilga, covered by a thin layer of aeolian sand within the sandplains and dunefields of the Great Victoria Desert, for assessment of the penetration capability of the longer-wavelength microwave. The radar backscatter from the earth's surface at a given wavelength and polarization is primarily a function of surface roughness and dielectric constant. To provide an understanding of the relative contributions of these parameters, and to enable unmixing of their effects in the AIRSAR data, field measurements of soil moisture, dielectric constant and surface roughness were made at selected ground sites across the Tarcoola area. Rock chip samples collected during the field survey were tested for their dielectric properties in the frequency ranging from 100 MHz to 3GHz. The results agreed with digital analysis of polarimetric AIRSAR data. GPR (Ground Penetrating Radar) was employed to assess the penetration capability of the longerwavelength microwave for subsurface geological mapping. GPR profiles showed the penetration of several tens of centimeters.
A visible-near infrared spectrometer, Spectral Profiler (SP), was proposed and selected as one of mission instruments onboard Japanese Selenological and Engineering Explorer (SELENE) spacecraft. The eventual goal of SP observation is to collect mineralogical and compositional information on the lunar surface and contribute to studies on the origin and the evolution of the moon and its crust. In this paper, performance and calibration requirements for SP based on these scientific objectives are discussed. Most critical performance requirements are those for spectral capabilities such as spectral coverage, 0.5-2.6μm, and spectral resolution, better than 10nm. Also, the high signal-to-noise ratio, 2000 or better in the 0.7-1.5μm spectral range, is very important to detect subtle absorption features on spectra of lunar highland soils which is often obscured by space weathering. Due to contamination, radiation, and other phenomena on optical components and detectors, the radiometric sensitivities of space optical instruments often degrade with time. To remove such degradation effects and retrieve accurate reflectance spectra on the moon, radiometric calibration activities are necessary. For SP, two complementary calibration methodologies are currently proposed:Vicarious calibration using the reflectance reference sites such as Apollo 16 landing site and the onboard calibration system including halogen lamps and a spectral filter.By careful analyses of such calibration data, detailed optical characterization of the instrument will be possible and hence accurate spectral data for the whole moon surface will be obtained.