Porwal, Alok 
  
A PREDICTIVE MODEL FOR BASEMETAL EXPLORATION IN A GIS ENVIRONMENT 
Alok Porwal* and Edmund Sides 
International Institute for Aerospace Survey and Earth Sciences (ITC), Delft, The Netherlands 
*Department of Mines and Geology, Govt. of Rajasthan, Udaipur, India 
porwal @itc.nl 
sides @itc.nl 
KEY WORDS: Fuzzy, Geology, Geophysics, GIS, Integration, Mathematical models. 
ABSTRACT 
A predictive model for mineral potential mapping based on fuzzy set theory is described. It is tested in the south-central 
part of the Aravalli province (western India), which hosts a number of conformable sediment-hosted basemetal deposits. 
Recognition criteria for basemetal mineralisation were identified on the basis of published work on metallogenesis in 
Aravalli province. A regional GIS was then established in ArcView GIS software using several public-domain geodata 
sets. These were reviewed, processed, reclassified and gridded to generate multi-class lithological, stratigraphic, 
structural, magnetic and lineament-density maps. Weights were assigned to each evidential map, and also to each class 
of the maps, on the basis of their significance as guides to the occurrence of basemetal mineralisation. These were used 
to calculate fuzzy membership values for all classes. The values thus determined were combined using fuzzy algebraic 
sum and fuzzy algebraic product operators to generate basemetal favourability maps for the province. It was observed 
that the fuzzy algebraic sum operator gives excessive areas of high favourability, while the fuzzy algebraic product 
operator tends to diminish favourability. The values obtained from these operations were therefore combined using 
fuzzy gamma operators to generate final favourability maps. Known basemetal occurrences were overlaid on the 
favourability maps to validate the procedure. It was found that most of the known mineral occurrences correlate with 
areas of high-predicted favourability, although there are several areas of high favourability that do not have any mineral 
occurrences. Work is continuing to check whether such areas genuinely represent areas warranting further exploration, 
or whether the modelling techniques used need further refinement. 
1 INTRODUCTION 
Most statistical and probabilistic approaches to mineral potential modelling are based on the use of binary evidential 
maps, while real-world geodata is usually multi-class in nature. This necessitates reclassification of multi-class data into 
binary data, which may result in loss of valuable information. Moreover, the reclassification principles are normally 
based on available information, and may change, as more information becomes available. Models based on fuzzy set 
theory accept multi-class data and are sufficiently robust to assimilate the “informational fuzziness” (Zimmermann, 
1985) that is inherent in most geodata. The input parameters can be selected either by using empirical methods based on 
statistical (or heuristic) evaluation of the spatial association of various geodata with mineral deposits or by using a 
genetic model. In this study the second approach was used, the fuzzy membership values of the model parameters being 
assigned subjectively by experts. For building and testing the model, the south central part of the Aravalli metallogenic 
province in Rajasthan, western India, was selected (see Fig. 1). The area has been relatively well explored and this work 
is documented in the literature. An area of about 37500 sq. km, falling between latitudes 23°30" N and 26° N and 
longitudes 73°30" E and 75? E is used. This area includes a number of major Zn-Pb-Cu and Pb-Zn deposits and many 
small and minor occurrences of basemetals as well as abandoned mining pits. 
1.1 Geology and mineralisation of the test area 
Heron (1953) interpreted the geology of the Aravalli province in terms of three major Proterozoic orogenic cycles, 
represented by the Banded Gneissic Complex (BGC), the Aravalli Supergroup and the Delhi Supergroup. His scheme 
has remained the basic framework of reference for all subsequent revisions (e.g., Raja Rao, 1976; Roy, 1988; Sudgen et 
al., 1990; Gupta et al., 1995). The region is characterised by evidence of repeated tectonic deformation, metamorphism 
and magmatism (Roy et al., 1971; Naha and Halyburton, 1974; Roy, 1988; Sharma, 1988; Srivastava, 1988). 
  
1178 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000.