『Abstract
　This paper describes the approach to, and outcomes of, a manual analysis (i.e., a cognitive assessment of spatial and non-spatial data) of the uranium potential of 90 geological regions in Australia. For this analysis, the 14 principal uranium deposit types recognized by the International Atomic Energy Agency were grouped in six uranium system models (i.e., surficial, sedimentary, igneous-related, metamorphic/metasomatic, unconformity-related, and vein-related uranium systems) on the basis of similar genetic processes, environments of ore formation and ingredients mappable at the regional to continent scale. The newly proposed uranium systems models are structured according to the mineral systems approach and focus on the critical mineralization processes that must occur for a uranium deposit to form in a particular region. Our manual prospectivity analysis employed this approach to assess the probability of the critical genetic processes having occurred in each geological region. In this semi-quantitative, probabilistic evaluation, technical, quality and opportunity ranking schemes were used to rank each geological region based on the probability of occurrence of and potential for high-quality uranium deposits and opportunity for securing prospective ground. Based on this assessment, the geological regions with the greatest potential for discovery of potentially recoverable uranium resources are the Ashburton, Broken Hill, Litchfield, McArthur, Money Shoal, Murphy, Paterson, Pine Creek and Northeast Tasmania regions (i.e., quality ranking of 10.0), the Gawler and Polda regions (i.e., 9.0), and the Amadeus, Georgetown, Stuart, Tanami regions (i.e., 8.1). Most of these regions contain known unconformity-related or sandstone-hosted uranium deposits, although some of them are pure conceptual plays that have received relatively little attention in terms of uranium exploration. Maps based on the numerical output of the prospectivity analysis helped to inform area selection decisions and detailed follow-up studies, and focus time and resources. The template developed in this study can easily be modified to suit prospectivity analyses for other metals or a similar investigation in another country. As illustrated in Part II, the best possible approach to a complex, continent-wide prospectivity analysis is to harness the strengths of both manual and automated (i.e., sophisticated computational techniques applied to spatial data) approaches as these methodologies essentially address each other's limitations.

Keywords: Area selection; Conceptual targeting; Deposit classification scheme; Mineral systems approach; Prospectivity analysis; Uranium; Australia』

1. Introduction
2. Manual uranium prospectivity analysis
　2.1. Literature review
　2.2. Rationale and construction of uranium systems models
　2.3. GIS database
　2.4. Scope, design, conduct and results of the prospectivity analysis
3. Case studies
　3.1. Surficial uranium systems
　　3.1.1. Yilgarn Region (Western Australia)
　　3.1.2. Musgrave Region (Northern Territory, South Australia, Western Australia)
　3.2. Sedimentary uranium systems
　　3.2.1. Eromanga Region (New South Wales, Northern Territory, Queensland, South Australia)
　　3.2.2. Carnarvon Region (Western Australia)
　3.3. Unconformity-related uranium systems
　　3.3.1. Pine Creek Region (Northern Territory)
　　3.3.2. King Leopold Region (Western Australia)
4. Discussion
　4.1. New uranium deposit classification scheme
　4.2. GIS-assisted manual versus GIS-driven automated prospectivity analysis
　4.3. Scope of the manual uranium prospectivity analysis
5. Conclusions
Acknowledgements
References