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Multiplicative Cascade Processes and Information Integration for Predictive Mapping : Volume 19, Issue 1 (11/01/2012)

By Cheng, Q.

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Book Id: WPLBN0003974732
Format Type: PDF Article :
File Size: Pages 12
Reproduction Date: 2015

Title: Multiplicative Cascade Processes and Information Integration for Predictive Mapping : Volume 19, Issue 1 (11/01/2012)  
Author: Cheng, Q.
Volume: Vol. 19, Issue 1
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2012
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Cheng, Q. (2012). Multiplicative Cascade Processes and Information Integration for Predictive Mapping : Volume 19, Issue 1 (11/01/2012). Retrieved from http://hawaiilibrary.net/


Description
Description: State Key Lab of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100083, Wuhan 430074, China. This paper presents a new model proposed on the basis of multiplicative cascade process (MCP) theory for integrating spatial information to be used for mineral resources prediction and environmental impact assessment. Probability of a spatial point event is defined as the probability that a small map calculating unit (map unit) randomly selected from a study area contains one or more points. The probability that such unit randomly selected from a subarea with known spatial binary map patterns (evidential layers) contains one or more points is defined as the posterior point event probability. In this paper, processes of integrating multiple binary map patterns that divide the study area into smaller areas with updated posterior probabilities are viewed as multiplicative cascade processes resulting in a new log-linear model for calculating conditional probabilities from the multiple evidential input layers. The coefficients (weights) involved in this model measuring degree of spatial correlation between point event and the evidential layers are found to be associated with singularity indices involved in multifractal modeling. It is demonstrated that the model is simple and easy to be implemented in comparison with the existing weights of evidence model which is commonly applied in spatial decision modeling. In addition, the posterior probability as the end product of a multiplicative cascade process can be used to describe multifractality and singularity which are useful properties for characterizing spatial distribution of predicted point events. A case study of tin mineral potential mapping in the Gejiu mineral district in China is used to illustrate principles and use of the modeling process. Four binary layers: formation of limestone, buffer distance for intersections of three groups of faults, local and regional geochemical anomalies of elements As, Sn, Cu, Pb, Zn and Cd, were combined for mapping potential areas for occurrence of tin mineral deposits.

Summary
Multiplicative cascade processes and information integration for predictive mapping

Excerpt
Blenkinsop, T. G.: The Fractal Distribution of Gold Deposits, in: Fractals and Dynamic Systems in Geoscience, edited by: Kruhl, J. H., Springer-Verlag, 247–258, 1994.; Agterberg, F. P.: Computer programs for exploration, Science, 245, 76–81, 1989a.; Agterberg, F. P.: Systematic approach to dealing with uncertainty of geoscience information in mineral exploration, in: Application of Computers and Operations in the mineral industry, edited by: Weiss, A., Proc. 21st APCOM Symp., Las Vegas, Nevada, Colorado Society of Mining Engineers, Littleton, 165–178, 1989b.; Agterberg, F. P.: Multifractal modeling of the sizes and grades of giant and supergiant deposits, Int. Geol. Review, 37, 1–8, 1995.; Agterberg, F. P.: New applications of the model of de Wijs in regional geochemistry, Math. Geol., 39, 1–26, 2007a.; Agterberg, F. P.: Multifractal simulation of geochemical map patterns, in: Geologic modeling and simulation: Sedimentary Systems, edited by: Merriam, D. F. and Davis, J. C., Kluwer, New York, 327–346, 2001.; Agterberg, F. P.: Mixtures of multiplicative cascade models in geochemistry, Nonlin. Processes Geophys., 14, 201–209, doi:10.5194/npg-14-201-2007, 2007b.; Agterberg, F. P. and Bonham-Carter, G. F.: Deriving weights of evidence from geoscience contour maps for prediction of discrete events, Proc. 22nd APCOM Symp. (Berlin, Germany), Tech. Univ. Berlin, 2, 381–396, 1990.; Bonham-Carter, G. F.: Geographic Information Systems for Geoscientists: Modelling with GIS, Pergamon, Oxford, 398 pp., 1994.; Bonham-Carter, G. F., Agterberg, F. P., and Wright, D. F.: Integration of geological data sets for gold exploration in Nova Scotia, Photogr. Eng. Remote Sens., 54, 1585–1592, 1988.; Carlson, C. A.: Spatial distribution of ore deposits, Geology, 19, 111–114, 1991.; Cheng, Q.: The gliding box method for multifractal modeling, Comput. Geosci., 25, 1073–1079, 1999.; Cheng, Q.: Fractal and multifractal modeling of hydrothermal mineral deposit spectrum: application to gold deposits in the Abitibi Area, Canada. J. China Univ. of Geosci., 14, 199–206, 2003.; Cheng, Q.: Multifractal distribution of eigenvalues and eigenvectors from 2-D multiplicative cascade multifractal fields, Math. Geol., 37, 915–927, 2005.; Cheng, Q.: Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China, Ore Geol. Reviews, 32, 314–324, 2007a.; Cheng, Q.: Multifractal imaging filtering and decomposition methods in space, Fourier frequency, and eigen domains, Nonlin. Processes Geophys., 14, 293–303, doi:10.5194/npg-14-293-2007, 2007b.; Cheng, Q.: Non-linear theory and power-law models for information integration and mineral resources quantitative assessments, Math. Geosci., 40, 503–532, 2008.; Cheng, Q. and Agterberg, F. P.: Multifractal modeling and spatial statistics, Math. Geol., 28, 1–16, 1996.; Cheng, Q. and Agterberg, F. P.: Fuzzy weights of evidence method and its application in mineral potential mapping, Nat. Res. Res., 8, 27–35. 1999.; Cheng, Q. and Agterberg, F. P.: Singularity analysis of ore-mineral and toxic trace elements in stream sediments, Comput. Geosci., 35, 234–244, 2009.; Cheng, Q., Bonham Carter, G. F., Agterberg, F. P., and Wright, D. F.: Fractal modeling in the geosciences and implementation with GIS, in: Proc of the 6th Canadian Conference on GIS, Ottawa, June 6, 10, 1, 565–577, 1994a.; Cheng, Q., Agterberg, F. P., and Ballantyne, S. B.: The separation of geochemical anomalies from background by fractal methods, J. Explor. Geochem., 51, 109–130, 1994b.; Cheng, Q., Zhao, P., Zhang, S., Xia, Q., Chen, Z., Chen, J., Xu, D., and Wang, W.: Application of singularity in mineral deposit prediction in Gejiu district: Information integration and delineation of target areas, Earth Science, 34, 243–252, 2009 (in Chinese with English abstract).

 

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