| Geology |
Estimation of The Prospective ORE-Bearing sites using Multivariate Statistical and Image Analysis
To perform more detailed analysis, aerial photographs were converted to a digital format and the defined resolution was 300 dpi.
To improve the determination of natural objects, different types of spatial enhancement techniques such as average, Robert, Sobal and Laplacian type filters were applied to the aerial images . the result of the spatial convolution were assigned to red, green and blue colour images significantly improved the interpretation. In the colour images, specifically circle structures of regional and local levels were clearly seen. As a result of the interpretation, a structural map was created. Furthermore map was compared with geological and geomorphological maps.
To test the accuracy of the interpretation, the same image was given to two thematic interpreters with different experiences. The result of the interpretation was analysed using linear regression model. The correlation coefficient was 0.65. During the analysis it was seen that the 3D images created by integration of the DEM and the geological and geomorphological maps significantly improves the interpretation and investigation of some peculiar morphological structures [8]. A 3d view of geology of the study area is shown in figure 2.
Figure 2. A 3D view of geology of the Khumul area.
Multivariate Statistical Analysis
For the investigation of the actual new ore-bearing sites, a factor analysis has been applied [1,4] and a total of 34 variables such as the length and density of the lineaments, geological structural information, gold ore, the present distribution of the gold mine and other necessary information were used. The study areas was divided into grid cells each of which was 2kmx2km and a total of 156 cells were defined. In the factor analysis R-mode approach has been used.
As a result of the analysis the following were defined .
a) factor loading was calculated and the factors containing highest values were selected.
b) The variables which are highly correlated with the observed factors were selected.
c) Anomalies were calculated and 4 factors were selected after a varimax rotation.
Here, as an additional estimation, the sum of all projections has been used. The determined factors were mapped and isolines for each of the calculated factors were drawn. The isolines were overlapped and on the basis of the delineated isolines the new ore-bearing sites were determined
Figure 3. Defined locations of gold distributions estimated by a factor analysis
Conclusions
The aim of this study was to estimate the actual ore-bearing sites in the Khumul area, north-eastern Mongolia, integrating data from multiple sources. As seen from the analysis, RS and GIS techniques have an efficient usage for data analysis and extraction of structural information and when integrated with multivariate statistical analysis can be considered as a powerful technique for the estimation of the possible new locations of minerals. Moreover, the same approach can be applied for the estimation of other land resources.
Refernces
- A.R.H.Swan, M.Sandilands, P.McCabe, 1995, Introduction to Geolgical Data Analysis, Blackwell Science Ltd, pp435.
- D.Amarsaikhan, M.Ganzorig, J.Gan-Ochir, I.Ulemj, D.Narangerel, 1997, Estimation of Mineral Resources using GIS and Statistical Methods, Scientific Report of the Institute of Informatics and R.S, Academy of Sciences, Ulaanbaatar, Mongolia.
- ERDAS, 1991, User's Guide, ESRI, USA.
- J.Davis, 1986, 2nd ed. Statistics and Data Analysis in Geology, Publisher Wiley, New York, pp646.
- J.Gan-Ochir, 1997, Relationship between Geostructure and Minerals in Khumul- Balj Area, Geological Report, Ulannbaatar, Mongolia.
- J.Gan-Ochir, Z.Ariun, Ts.Bekhtur, 1989, Geostructure, Complex Methods of Estimation of Mineral Resources of Geological Structure in Mongolian Territory, Ulaanbaatar, Mongolia.
- ILWIS, 1992, User's Guide, ITC, The Netherlands.
- M.Ganzorig, D.Amarsikhan, B.Enkhtuvshin, Kh.Tulgaa, 1994, Design of A Multilevel Databases using RS and GIS Techniques, Proceedings of ACRS, Bangalore, India.
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