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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
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1. Maintenance and analysis of the
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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 64 and 65: 3. Integrated analysis of spatial a
- Page 66 and 67: 3. Integrated analysis of spatial a
- Page 68 and 69: 3. Integrated analysis of spatial a
- Page 70 and 71: 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 104 and 105: Fitting a model‣Now you can plot
- Page 106 and 107: Different types of semivariogram mo
- 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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