Geologic Interpretation
Japanese ERDS-1 Simulation data merged with geographic information
H. Watanabe, M.
Tsukada Japex Geo science institute, Inc. Introduction The J-ERS-1 (Japanese Eearte Resources Satellite - 1) is at the final stage of launching sin early 1991. As is well known, JERS-1 has two sensors on its platform: SAR (Synthetic Aperture Radar) and OPS (Optical Sensor). Especially, the letter has two characteristics.
Brief discrimination of the site (2) Target area is comb Ridge, which is located in western part of Paradox Basin extending over Uath, Colorado, Arizona and New Mexico; USA This basin is a large sedimentary basin of Paleozoic to Mesozoic era. Comb Ridge is a N-S trending monocline Characterized by the flat iron composed of Navajo white sand stone Eastern, side of Comb Ridge is an almost horizontal Jurassic horizon, while at the Western side appear older and older horizon and near the top of the anticline called Raplee is Rico Formation composed of limestone of Pennsylvanina era. Between Rico and Navajo Formation, Cutler formation of Permian and Chinle Formations of Triassic come p in the belt form parallel to Comb ridge. Cutler formation can be subdivided into Haligato, Cedar Mesa, Organ Roct and De Cherry Members, successively from the left to the right. Within these members, Cedar Mesa member is known to contain gypsum, particularly in the neighborhood of Comb Ridge. The geologic map is digitized by our interactive system as shown in fig. 1 Figure.1 Digitzed geologif map(after O'Sullivan) GER AIS data GER AIS is, data this moment, one of the most advanced airborne remote sensing sensors. Major parameters of GER-AIS are listed in tab.2 As shown in this Table, AIS has 63-spectra channels, 32 of which are located in SWIR region (1.5 - 1.7 mm, 2.0-2.5mm). In particular, the high spectral resolution for 2.0-2.5 mm is a powerful tool for rock and mineral as well known. In addition to this spectral characteristics, imaging capacity of this sensors allows us to locate easily specific pixel. We can see two typical examples of spectral features with its position, which are interactively searched on screen: one example is limestone of RCI formation and the other, gypsum of Cedar Mesa member. The spectral curves on the right hand side are calculated from 2.0-2.5 mm data of GER AIS by using normalizing method, and the associated spectral curves are the pointed of spectral measurement in the laboratory. It can be pointed out that both features express clearly spectral characteristics of limestone and gypsum, respectively. Here only the example of limestone is shown in Figs. 2 and 3. Figure.2 Extracted Spectral curve of GER-AIS data(limestone of Rico formation) Figure.3 Labouatory measurement of the sample from Rico formation Generation of ERS-1 OPS Multispectral data GER-AIS data with narrow bands are summed up to produce simulation data of ERS-1 OPS, taking into account band characteristics, spatial resolution and signal to noise ration. A sample image of ERS-1 OPS as shown in Fig. 4 where band combination is 1,4 and 5 and its quality is excellent. However, if we choose 3 bands in SWIR, color become much more monotonous, caused by the high correlation between bands. In such images, we can emphasis the difference of the colors keeping the original color as much as possible, by using decorrelated stretch. By this technique, we can find out many different colors caused by the lithology., and these color combination can be explained by the spectral characteristics as seen in the previous section. By stacking up such experience of color interpretation, we may be able to make a color table for spectral interpretation of rock and soil for J-ERS-1 OPS. Figure.4 J-ERS-1 simulation image of bands1,4,and5 Merge of geographic information on the image As mentioned in the first section of this paper, totographic and geologic maps are digitized in our GIS system. In such GIs system, it is possible to record geographic position together with its attributes such as topography, rock type……, Then difference of the location can be corrected on the screen interactively, by selecting control points. An example of merged image is shown in Fig. 5. subtle mismatch of the position seems to be caused by the complicated movement of the aircraft. However, we cannot only compare the results of spectral interpretation with the existing geologic map, but also can add detailed information about the lithology from the image. And furthermore, this merging capability may be helpful for the compilation of other kind of data and for statistics. Conclusion (1) J-ERS-1 OPS data will be useful especially for rock and soil discrimination (2) Merging capability of image data and geographic information will be a powerful tool of image interpretation. Most of the above processing were done by our Terra-Ma / JGI System. Acknowledgement The authors would like to tank to RRSS' for providing them with GER-AIS data. : Technology Research Association of Resource Remote Sensing System References
Table 1 Major Parameters of J-ERS-1OPS
Table 2. Major Parameters of GER-AIS
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