REFERENCE TEXTS:

Avery, T.E. & Berlin, G.L. 1992. Fundamentals of Remote Sensing and Airphoto Interpretation, 5th Ed., MacMillan Pub. Co., 472 p.

Bonham-Carter, G.F. 1994. Geographic information systems for geoscientists. Computer Methods in the Geosciences, v. 13, Pergamon. (principal text)

Drury, S. 1993. Image interpretation in Geology. Chapman and Hall, London.

Eastman, R.J. 1994. IDRISI - manuals. Clark University Graduate School of Geography.

Jensen, J.R. 1995. Introductory Digital Image Processing, a remote sensing perspective, 2nd edition. Prentice Hall Series in Geographic Information Science.

Lillesand, T.M. and Kieffer, R.W. 1993. Remote Sensing and Image Interpretation, 3rd Ed. J. Wiley & Sons, 720 p.

RadarSat International 1997. RADARSAT Geology Handbook.

Sabins, Jr., F.F. 1987. Remote Sensing: Principles and Interpretation. 2nd Ed. W.H. Freeman & Co., 449 p.

     Selected Bibliography, Geology and Mining

Anonymous. Feb. 8, 1993. Geo-haz Consultants. Summary of Procedures to Produce a Landslide Susceptibility Map. p. 1-2.

Anonymous. Sept. 1992. Computers and Mining. Gibbs Associates Vol. 8, no 1.

Anonymous. May 1992. Geographic Analysis Software. Coal magazine. p. 60.

Krist, Frank J., Daniel G. Brown. Sept. 1994. GIS Modeling of Paleo-Indian Period Caribou Migrations and Viewsheds in Northeastern Lower Michigan. PE&RS, Vol. 60, No. 9, p. 1129-1137.

McCalpin, James P. Jan. 1993. The Professional Geologist. Geohazards Mapping and Geographic Information Systems, Vol. 30, No. 1, p. 5-6.

Memmi, John M. Feb. 1995. Expertise and GIS Converge for Diamond Exploration. GIS World, Vol. 8, No. 2, p. 54-55.

Teeuw, Richard M., 1995. Groundwater Exploration Using Remote Sensing and a Low-Cost Geographical Information System. Hydrogeology Journal, Vol. 3, No. 3, p. 21-30.

    Software kindly made available by the Ontario Geological Survey under the Survey's Digital Data Royalty Licence Agreement:

Data Set 6 Bedrock Geology of Ontariobedseam.dxf

Data Set 11Tectonic AssemblagesTecseam.dxf

Data Set 12 Township and Areas of Ontario Lambert Conf.- Ont_lamb.dxf; UTM - Twp_z15,16,17,18.dxf

Data Set 13Drill Hole DatabaseASCII text files

Data Set 22 Topographic Map of OntarioBaseseam.dxf

Data 36 Geological compilation of the Timmins area, Abitibi Greenstone beltUTM NAD1927 1:20,000

ERLIS data set 1009Airborne Mag. and Electromag data for the Wawa area, Dighem III, CENTURION Data Display

    MAP PROJECTION SPECIFICATIONS FOR LAMBERT CONFORMAL - OGS Data set 12

The Township and Areas were digitized from hardcopy 1:50,000 scale NTS maps and assembled into an Ontario-wide fabric in Lambert Conic Conformal map projection. The following parameters define the planimetric reference grid:

Clarke 1866 ellipsoid a=6, 378,206.4 (equatorial radius) e=0.006768658 (eccentricity squared)

Standard parallels 49 degrees N latitude 77 degrees N latitude

Origin 92 degrees W longitude 0 degrees N latitude; Central Meridian 92 degrees W longitude

False Easting 1,000,000 metres

    MAP PROJECTION SPECIFICATIONS FOR LAMBERT CONFORMAL - GSC, Geological Map of Canada

    Lambert Conformal Conical Projection parameters

        Type
                 Lambert Conformal Conic projection
        Datum
                 North American Datum 1927 (NAD27)
        Units
                 metres
        Spheroid
                 Clarke, 1866
        Lambert standard parallels
                 49 00 00 N
                 77 00 00 N
       Projection origin
                 95 00 00 W (central meridian)
                 49 00 00 N
       False origin
                 (easting, northing)=(0, 0)

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            GEOSTATISTICS - GSTAT
        Gstat is a computer program for geostatistical modelling, prediction and simulation, copyright 1992, 1998 (C) Edzer J. Pebesma. The Gstat program is free software and can be redistributed and/or modified under the terms  of the GNU General Public License as published by the Free Software Foundation. Information about the source code and documentation of Gstat are available at: http://www.geog.uu.nl/gstat/

     Idrisi32 provides three interactive interfaces to Gstat functions:

     1. Spatial Dependence Modeller
     2. Model Fitting
     3. Kriging and Simulation

     Exploratory Data Analysis
     In addition to the variogram modelling options in the Spatial Dependence Modeler and Gstat, other Idrisi32 modules have been revised to provide better support for geostatistical analysis. These include interactive displays, histogram analysis (HISTO), moving window statistics (via a new version of the FILTER module), spatial autocorrelation assessment (AUTOCORR), trend analysis (TREND) and scattergram analysis (SCATTER).

    The most fruitful exploratory data analysis is achieved by viewing and describing a data set through a variety of means, and reviewing such representations in light of other ancilliary information known about the sampled phenomenon.

     Spatial Dependence Modeler
 The Spatial Dependence Modeller is an interactive interface that accesses a combination of Clark Labs and Gstat functions for creating h-scatterplots, surface variogram models, directional variogram models, and additional summary statistics. Spatial continuity can be modelled using the following methods: semivariogram (moments estimator or Cressie robust estimator), covariogram, correlogram, cross variogram, cross covariogram, or cross correlogram. Results can be saved and copied to documents. Data transformations allow on-the-fly application of the log transform, standard, and indicator transform.

     Variograms can be omnidirectional or directional. An omnidirectional variogram combines all possible directions (i.e., all sample pairs) in a single variogram. It can be represented as a curve, or it can be extended to create a surface variogram (grid). The figure above shows both the surface and the
directional variograms. The raster grid represents statistical space in which lag distance zero is located in the center and lag distances increase outward in all directions. The attribute of each pixel represents an average of variogram values for the particular distances and directions (i.e. separation vectors) defined by the pixel location. Lag separation distances can be regularly or irregularly spaced. The surface representation may be used to determine the maximum and minimum directions of spatial continuity.

     Model Fitting
 The Model Fitting interface allows for interactive fitting of different mathematical structures to the variogram. Ten structure types are available: spherical, exponential, gaussian, linear with sill, linear, power, logarithmic, circular, pentaspherical, and periodic. The fitting method algorithms accessed in Gstat include Weighted Least Squares, Weighted Least Squares with normalized weights, and Restricted Maximum Likelihood (REML).

     The top graph of the interface reflects the model to be fit and geometric anisotropies (when present), while the lower graph serves as a visual tool for viewing the independent structures. The three independent structures provided can be used for modeling nested structures, including zonal anisotropies.

     Kriging and Simulation

     The Kriging and Simulation interface provides access to simple and ordinary kriging and cokriging, stratified kriging and Gaussian conditional and unconditional simulation (including multiple simulations). It includes data transformation (log and standardization), multiple methods for setting the neighborhood parameters for local kriging interpolation, and cross-validation of the sample data. A mask image can be used to limit regions to be interpolated. In addition, this mask image can identify regions (called strata) to be interpolated separately.

     References:

 “Conditional simulation and the value of information,” In: Geostatistics for the next Century, R. Simitrakopoulos (ed.), Kluwer Academic Publishers, 209-217, 1994, (Solow, A.R. and Ratick, S.J.).

 A Method for Incorporating Topographic Uncertainty in the Management of Flood Effects Associated with Changing Storm Climate, Phase I report to: the U.S.  Department of Commerce, Economics of Global Change Program,  National Oceanographic and Atmospheric Administration, April, 1994. (S. Ratick, A.  Solow, J. Eastman, W. Jin, H. Jiang).

 “Assessing the Vulnerability of Coastal Communities to Extreme Storms:  The Case of Revere, MA., USA,” Mitigation and Adaptive Strategies for Global Change 3: 59-82, 1998.  (G. E. Clark, S. C. Moser, S. J. Ratick, K.Dow, W.B.  Meyer, S.Emani, W. Jin, J. X. Kasperson, R.E. Kasperson and H.E. Schwartz).

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