GIS Predictive Model for Producing Hydrothermal Gold Potential Map Using Weights of Evidence Approach in Gengma Region, Sanjiang District, China

Gengma region, Sanjiang district is known to have some large-scale gold deposits. GIS predictive model for hydrothermal gold potential was carried out in this region using weights of evidence modeling technique. Datasets used include large-scale hydrothermal gold deposit records, geological, geophysical and remote sensing imagery. Based on the geological and mineral characteristics of areas with known gold occurrences in Sanjiang, several geological features were thought to be indicative of areas with potential for the occurrence of hydrothermal gold deposits. Indicative features were extracted from geoexploration datasets for use as input in the predictive model. The features include host rock lithology, geologic structures, wallrock alteration and associated (volcanic-plutonic) igneous rocks. To determine which of the indicative geological features are important spatial predictors of area with potential for gold deposits, spatial analysis was done through the modeling method. The input maps were buffered and the optimum distance of spatial association for each geological feature was determined by calculating the contrast and studentized contrast. Five feature maps were converted to binary predictor patterns and used as evidential layers for predictive modeling. The binary patterns were integrated in two combinations, each of which consists of four patterns in order to avoid over prediction due to the effect of duplicate features in the two structural evidences. The two produced potential maps define almost similar favorable zones. Areas of intersections between these zones in the two potential maps placed the highest predictive favorable zones in the region.

Using Remote Sensing Data to Delineate the Lineaments for Hydrothermal Mineral Prediction in Heqing Area, Northwest Yunnan Province, China

Lineament extraction and analysis is one of the routine work in mapping medium and large areas using remote sensing data, most of which are satellite images. Landsat Enhanced Thematic Mapper （ETM） of 945×1 232 pixels subscene acquired on 21 March 2000 covering the northwestern part of Yunnan Province has been digitally processed using ER Mapper software. This article aims to produce lineament density map that predicts favorable zones for hydrothermal mineral occurrences and quantify spatial associations between the known hydrothermal mineral deposits. In the process of lineament extraction a number of image processing techniques were applied. The extracted lineaments were imported into MapGIS software and a suitable grid of 100 m×100 m was chosen. The Kriging method was used to create the lineament density map of the area. The results show that remote sensing data could be useful to extract the lineaments in the area. These lineaments are closely correlated with the faults obtained through other geological investigation methods. On comparing with field data the lineament-density map identifies two important high prospective zones, where large-scale deposits are already existing. In addition the map highlights unrecognized target areas that require follow up investigation.

Improved Geological Interpretation Using Landsat TM Data in Lancang-Jinghong Area, Yunnan Province, China

Landsat TM digital spectral data of Lancang Jinghong area (Yunnan P ro vince) has been used for the purpose of geological interpretation. To meet this object, different image processing techniques including selected band color comp osites, principal component analysis and IHS decorrelation stretching are used t o improve the discrimination of different lithological and structural features i n the area.It was found that IHS decorrelation stretching images obtained from t he transformation of false color composite 741 (in red, green and blue) prov ided the best results based on the original data.By combining the characteristic s of images produced by different approaches and other canonically transformed i mages with available geological data and surface observations, the geological in terpretation could be done with satisfactory degree of accuracy.