GISdevelopment.net ---> AARS ---> ACRS 1990 ---> Geology/Disaster 2 Deposit Image Model and optimization of Prospect Targets Cui Zhenkui, Huang xianfang, Zhu Dai Luo Fusheng, Gao jun, Wang Guojuan (Beijing Research Institute of Uranium Geology, Bejing, China) Jin Zhenguo, Yang Xiaoli, Fu Song (Computer Application Institute of Nuclear Industry, Bejing, China) Abstract Based on the practice in the application of remote sensing techniques, a new concept-deposit image model has been put forward. It is a very important tool for regional prospective prognosis. Application of deposit image model has opened up a possibility for quick and effective selecting of promising areas. This paper takes Beishen region for example to illustrate that remotesening information plays an important role in gold reconnaissance. The procedure are as follows : first, selecting resonal multispectral band combinations and image processing methods in the light of theory analyses and image processing tests with the purpose to get ideal enhancement, feature extraction results and recognition effectiveness ; then determining major ore-controlling factors (including structures, formations, dikes, alternations and son on ) and extracting their comprehensive image features, on the basis of geological interpreation in combination with regional investigation and detailed geological research on deposit- deposit dessection”; Finally summarzing recognition criteria, establishing deposit image model, and optimizing target areas. The practice has shown that using deposit image model to optimize target areas is a scientific and successful method. Of the eleven predicted areas, three have been proven to be favourable where geochemical anomalies and gold mineralization have been found at the surface and good results have been obtained. Introduction How to apply remote sensing to mineral deposit prospecting is a subject which has been pursued for years. In the past, the work was done by comprehensive analysis (basically, geological analysis ) of some remote sensing interpretation information . Sure it is one of the methods to select promising areas. But how to uitilize the superiority of remote sensing (remote sensing signature are chracterized by objectiveness, directness, and vastness) to determine comprehensive image features of various ore-controlling factors including structures, formations, dikes , and alternations, and establish deposit image model, then apply analogue method to select favourable areas is still a problem to be scrutinized recently and in the future. Methods and Procedures Research on deposit image model is a sythetical project which is based on understanding all ore –controlling factors and typical image signature interpretation. On one hand, one must pay attention to study on regional metallogenic conditions, “deposit dissection master gold ore-controlling factors to enhance and extract useful image information as much as possible. the procedures are described below (Fig. 1) : Figure 1 Procedure Diagram of optimization of targets 1. Image Processing Image processing is the basis for establishing deposit image model. Inorder to get typical image signatures, various image enhancement and quantiative image processing methods are employed in accordance with difference objects. A. Image enhancement of rocks and alternations (1) Colour composite Colour composite plays an important role in discrimination various rock types, particularly gold source formation. Since image results depend on the selection of wave band, great attention has been paid to wave band selection. three factors affecting the image results are considered. (A) Spectral characteristics of surface objects Two factors have been taken into consideration : the first is division of rocktypes. TM band 7 and band 5 are selected. Since in the range of band 7 and band 5, diferent rock types have distinct reflectance charcteristics. The second is spectral charcteristics of altered rock. TM band 7 and band 4 are selected, because altered rocks in study area have an absorption band in band 7 and a valley in band 4 (B) Correlation coefficient In order to make the selected bands represent all the original digital data, three bands which have the smallest correlation coefficient are selected according to the statistic results, the corelation coefficient between band 1 and band 7,4 issmaller, so band 1 must be added. (C) Practical results of processed image The goal of image processing is to get an ideal processed image in which different objects have conspicuous difference in colour hue, saturation and lamination. (2) Principal components transformation Principal components transformation is realized by calculating a new coordinate in order to get principal components which have smaller correlation coefficient. Usually the first principal component contains 85 percent of the original six bands of TM data, so the colour composite image made from the first three principal components does not simply represent the information of three bands, but contain almost all information of the initial six bands of TM data. subtal difference of surface objects, hydrothermal alternation and degrees migmatization can highlighted in the PC image. Some signatures which are not displayed in colour composit image can reflected in the PC image as well. So the method is called as “hidden information-highlighting method”. (3) Ratio colour composite image Ratio colour composite method plays a special role in identifying altered rock and accentuating “colour anomalies”. It is manipulated by exaggerating subtal difference of reflectance of different surface objects in individual band. On one band, ratio image can minimize difference in illumination condition, on the other hand, it can stretch the average value of different type surface objects with smaller intensity. In this way we can not only avoid taking the same type, but also improve the ability to distinguish different type objects with appoximate intensity. B. Enhancement of linear strutures Linear features can be enhanced by digital filters. Usually Laplacian transform is suitable for enhancing almost any orientation linear features. Spatial convolution is employed in emphasizing circular structures. directional filter is used to enchance specfic linear trends in the image, During the period od doing Laplacian transform, some experiences have been accumulated. According to the necessity, by changing kernel value, we can obtain a result image in which linear features have greatly been enchanced, while background image is obscured; and also prepare a result image in which original background image is maintained and linear features are enhanced. 2. Research on Distribution Regularities of Gold Mineralization Study on mineralization distribution regularities is the key link for establishing deposit image model and the basis for determining prognosis guides. Having done geological investigation in the field, we summarized the distribution regularities of gold mineralization in study area as follows: Gold mineralization distribution is obviously controlled by structures according to the image (scale 1:200000) interpretation, the strutural framework in study area consists of Palaeozoic central uplift zone and subsidence zones on the both sides of the uplift. Mineralized zones are controlled by deepseated faults which have undergone long-term activites, displaying distribution pattern of EM trending. The deposits are located at the intersections of NE and EW stricking faults and occur in high order and small scale fault strutures. Ore-body localizing strutures dominantly depend on mineralization type. Generally speaking, quartz vein type occurs in tensile structures, while altered rock type is located in compressive or compressive-shear structures. Gold deposits of Different type displays zonal distribution zonal distribution is obvious in Beishen region. On the whole , it can be partitioned in to three mineralized zone: i.e. north zone-volcanic-type gold deposit zone; middle zone-granite-type zone; and south zone-mixing type zoen. The south zone can be further divided into three subzones , i.e. north subzone granite-type zone, middle subzone-valcanic-type zone, and south subzone –metamosphic rock-type zone. Gold mineralization is restricted within gold-source formation Intermediate- basic volcanic formation are important gold-source formation in the study area. For example , gold mineralization are strictly controlled by bimodal colcanic formation of lower proterzoic (the upper group) and intermediate-basic volacnic formation of Ordovician-Silurian system and carboniferous system, demonstrating that gold mineralization tends to be developed in pre-existing gold-source formation Gold mineralization is related to Middle-Late Variscian magmatism and hydro-thermalism The grantie relevant to gold mineralization mostly are intermediate, intermediate acidic granite, belonging to a group of granodiorite and taking the shape of small irrefular instrusions, sush as offshoot, stock. gold mineralization has close time and space relation to hyrdrothermal activities derived from Variscian intermediate acidic magmatism whic provided favourableconditions for gold migration and concentration. 3. Establishment of Deposit Image Model Deposit image model means comprehensive expression of typical image features of Major orecontrolling factors including strutures, formations, dikes, and so on. Since the genesis of gold deposits is quite complicated and recognition of deposit image signatures involves a wide range of methods and technologies. The deposit image model in question is established on spectral charcteristics of surface objects. Based on image processing, geological interpretation, study on gold mineralization distribution regularities and field ckeck, image features of various orecontrolling factors and recognition criteria have been extracted. Different-type deposit image models in study area have been summarized as follows: A. Granite-type gold deposit image model Gold- productive intrusive bodies are Variscian granite , granodiorite in the shape of stock and offshoot. Granite in the region has higher reflectance,showing grey,light-grey colour by which it is easily discerned in the image. Granite bodies are controlled by east-west orientation faults, and distributed in zonal and branch-like forms and inthe shape of bead string. Dikes and alternations are well developed in gold-productive granite bodies, demonnstrating uneven grey and mottled colour in the image, such as Jinbguozi and shijinpo granite bodies. deposit is controlled by regional east-west striking, occuring in its subsidary faults. for example, Jinguozi deposit is controlled by a group of subsidary NNW striking quartz veins, exhibiting distinct light orange linear feature in the image. there is “colour anomaly” in the range of every deposit. Different manifestations of image signatures are obtained by using diferent image methods. For example, “colour anomaly” of Mojindong area displays light purple colour which differ from that of surrounding granite in the colour composite image (4,5,7 bands) . While in the ratio composite image (5/7, 5/4, 5/1), Jinguozi diposit is expressed as bright light orange colour. The same “Colour anomaly” can be seen at No. 210 blind deposit which is located in the south of Jinguozi deposit (fig.2) . These colour must be caused by widespread altered rocks closely associated with gold mineralization in the range of deposit. Figure 2 Ratio composite image B. Intermediate-basic volcanic rock type deposit image model Intermediate-basic volcanic formation are controlled by faults, displaying zonal distribution of east-west orentation and dark, dark-blue colour composite image (fig.3) . Accordingly three intermediate-basic volcanic zones interpreted and their distribution has been delineated. Figure 3 Colour composite image Deposits are emplaced at the intersections of NE and NW faults which can be easily regnized in the image. Light-coloured alteration related to mineralization displays grey, light grey, light green colour in the colour composite image (4,5,7) . in contrast with dark-blue background colour caused by intermediate-basic volcanic rocks the light-coloured alternations are distinguished and their spatial distribution is easily delineated. Late small intrusive bodies which are closely relevant with gold mineralization in space and time show light purple colour in the colour composite image (4,5,7 bands) . In addition circular structures which reflect center of volcanic activities are important image signatures for this the type deposits. C. Metamorphic rock-type deposit image model Metamorphic rock-type deposits in the study region are referred to those which occured in ordovician-Silurian systems and Lower Proterozoic slightly metamophic rocks. (A) Lower proterozoic comprises, in ascending order, magmatite, marble and inthe upper part metamorphic rock formation characterized by occurrence of bi-modal volcanic rocks. In KL transform image, migmatite and different degrees of magmatization are well displayed. Bimodal volcanic rocks display dark, dark brown colour on both 2,7,5 and 4,5,7 band colour composite image . So regional distribution of the third subgroup of Lower Proterozioc ( target horizon for occurrence of gold deposists) is distinctly demonstrated. In some areas, these target horizons are controlled by east-west folding, showing symmetrically zonal distribution along the north and south limbs of folding. (B) In some areas, combination charcteristics of image signatures which reflected different lithological assemblage are vary distinct. ore-bearing strata (basic and intermediate colcanic rocks) display dark brown colour, while granite and quartz diorate light grey colour, syeniteporphyry dark-red brown colour, showing alternating banded signatures in the colour composit image (2,7,5 bands). (C) Light-coloured alternation displays grey, light blue colour in the colour composite image (1,7,5 bands ), exhibiting narrow bands and linear distribution. These image features are remarkably distinct from the dark brown colour background caused by ore-bearing formations. 4. Target Optimization The final purpose of study or regional gelogy, metallogenic regularities and image features is to optimize targets. Based on the analyses of regional geological evolution, gold mineralization distribution regularities, prognosis criteria of gold deposits have been determined . Exploring the inherent links between prognosis criteria and image features and converting ore-controlling factors (Includeing structures, intrusive bodies, gold-source formations, alternations) into recognizable eleven favourable areas have been predicted. Taking J-1 for example . According to established image model, except favourable structures and gold source conditions which should be considered, image feature of ore-bearing granite bodies are also important cirterion in predicting potential area. first, colour composite method is used to sieve favorable granite bodies having image features similar to known mineralized granic bodies. Redults of Applicaton After selecting favourable areas, field check has been done. Preliminary investigation has indicated that geochemical anomalies and gold mineralization have been found in three of the predicted areas . The results are satisfactory. Implications Remote sensing practice in Beishan region has shown that applying deposite image model to mineral prognosis is an effective, fast tool for regional assessment. it has a lot of advantages over conventional geological methods. It is suitable for regional recconaissance, especially for remote areas with poor transformation condition and basic geological information . The methods is of certain universal significance in theory and practice. Reference Cui zhekui and others, 1988, Application results of TM Image in Beishan Region, Radiogeology Newsletter , 1988-7 J.J. bache , 1987 , world Gold Deposits: A Geological Classification Floyd F. Sabins , JR. 1987 , Remote Sensing Principles and interpreation Beijing Research Institute of Uranium Geology, Computer Application Institute of Nuclear Industry, 1988, Synopsis pof TM Data processing and Application in Gold Recconaissance Uranium and Gold newsletter, 1988-15 .