3. Integrated analysis of spatial and attribute data - RTC, Regional ...

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Fitting a model‣Now you can plot the averagesemivariance versus average distance ofthe bins onto a graph.‣the empirical semivariogram.‣But the empirical semivariogram values cannot be used directly inthe ק matrix because you might get negative standard errors for thepredictions;‣instead, you must fit a model to the empirical semivariogram.‣Once the model is fit, you will use the fitted model whendetermining semivariogram values for various distances.104
Fitting a model to the empirical semivariogram‣Geostatistical Analyst provides the following functions to choose from tomodel the empirical semivariogram:‣Circular,‣Spherical,‣Tetraspherical,‣ Pentaspherical,‣Exponential,‣Gaussian,‣Rational Quadratic,‣Hole Effect,‣K-Bessel,‣J-Bessel, and‣Stable.‣The selected model influences the prediction of the unknown values,particularly when the shape of the curve near the origin differs significantly.‣The steeper the curve near the origin, the more influence the closestneighbors will have on the prediction.‣As a result, the output surface will be less smooth.‣Each model is designed to fit different types of phenomena more accurately.105
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International Training Course on
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What is GIS?A widely accepted defin
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What is GIS?‣Where do certain con
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It is one of the most important ele
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Geographic PositionThe Nature of Ge
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The Nature of Geographic DataSpatia
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Organizing Geographic Data ForAnaly
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The Components of GIS‣All of thes
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The Components of GISMethods includ
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The Components of GISSoftwareAll pa
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Data InputData QualityErrors in the
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Positional AccuracyData Qualityexpe
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SPATIALDATAMODELS26
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GIS Spatial Data ModelsRepresentati
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Raster Data ModelIn the raster data
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Raster Data ModelRaster file can be
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1. Traditional Raster Encoding34
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3. Quadtree raster encoding‣provi
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Vector Data ModelIn the vector data
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Vector Data Model‣The data model
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Topological ModelTopological relati
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Topological ModelOther names for No
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Some Basic Topological Relationship
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Triangulated Irregular Network (TIN
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GIS ANALYSIS FUNCTIONS50
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A Classification of GIS Analysis Fu
Page 54 and 55: 1. Maintenance and analysis of the
Page 56 and 57: Edge-matching :Maintenance and anal
Page 58 and 59: Maintenance and analysis of the spa
Page 60 and 61: Attribute query functions2. Mainten
Page 62 and 63: 3. Integrated analysis of spatial a
Page 72 and 73: Logical Operations on Raster: LOGIC
Page 74 and 75: Overlay Analysis‣One of the major
Page 76 and 77: Vector overlayThe process of subdiv
Page 78 and 79: Comparison of Vector and Raster Ove
Page 80 and 81: Connectivity (Network) Operations:
Page 82 and 83: Connectivity (Network) Operations:P
Page 84 and 85: Connectivity (Network) Operations:P
Page 86 and 87: Network FunctionsConnectivity (Netw
Page 88 and 89: Connectivity (Network) Operations:N
Page 90 and 91: The principles of geostatistical an
Page 92 and 93: Geostatistical Analyst‣A major ch
Page 94 and 95: Calculate the empirical semivariogr
Page 96 and 97: Modeling a semivariogram‣spatial
Page 98 and 99: Calculate the empirical semivariogr
Page 100 and 101: Binning the empirical semivariogram
Page 102 and 103: Calculating the empirical semivario
Page 106 and 107: Different types of semivariogram mo
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Page 110 and 111: Creation of g vector for the unmeas
Page 112 and 113: Make a prediction‣the weights dec
Page 114 and 115: ‣The kriging standard error value
Page 116 and 117: THANK YOU116
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