SIMULATION OF REGIONAL GEOCHEMICAL SURVEY MAPS AT VARIABLE SAMPLE DENSITY

The production of geochemical maps of the world as proposed by the Int ernational Geochemical Mapping project (IGM) will require sampling of new areas at low densities and amalgamation of new data with existing geochemical data to ensure map production within reasonable time scale s and budgets. Assuming compatibility in sampling and analytical techn iques, two important considerations regarding sample density are: (i) how far can sample densities be reduced before meaningful geochemical patterns are lost, and (ii) how can datasets of different sample densi ty be amalgamated? These considerations are examined in the present st udy by applying two methods of computational data reduction simulating low density sampling to the British Geological Survey's high precisio n, high resolution (1 sample per 1.5 km(2)) stream sediment datasets f or Northern Britain, exemplified by Ni and B. A series of grids with g rid squares of 25 km(2), 100 km(2), 500 km(2) and 160000 km(2) corresp onding to sample densities recommended elsewhere for IGM (Table 1) are superimposed on the data. For each grid square the data are reduced b y (i) selecting a single sample at random, and (ii) calculating the me dian value. Results are presented as a suite of image processed maps c ontoured with similar percentile levels enabling comparisons of elemen t distributions to be made. The maps demonstrate that geochemical patt erns become distorted at sample densities lower than 1 per 25 km(2) us ing the random selection method. Random sub-sampling of existing datas ets with high sample densities is therefore unlikely to be successful. Employing the median value method, geochemical patterns are maintaine d with a reasonable degree of accuracy to densities as low as 1 sample per 500 km(2). The optimum reduced sample density for the Northern Br itain datasets for Ni and B is 1 per 25 km(2). The size of the geologi cal feature(s) and the magnitude of the geochemical variation are the principle factors controlling the resolution of geochemical patterns a t low sample densities. Hence it is unrealistic to recommend an optimu m sample density suitable for geochemical mapping throughout the world . Additional factors which influence the choice of sample density incl ude the objectives of the survey (eg, regional reconnaissance, mineral reconnaissance, environmental monitoring), logistical controls on sam pling (access, vegetation, climate etc.) and funding constraints. A sa mple density structure based on grid sizes of 25600 km(2), 6400 km(2), 1600 km(2), 400 km(2), 100 km(2) (Garrett, pers. commun., 1992) and 2 5 km2 which takes account of these various factors and allows surveys of different sample densities to be related to each other, is therefor e proposed for the International Geochemical Mapping project.