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

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The principles of geostatistical analysis90
Geostatistical analysis‣Sample points taken at different locations in a landscape and creates(interpolates) a continuous surface.‣The sample points are measurements of some phenomenon such as:‣oil spill,‣ elevation heights‣Soil and rock properties‣Climate measurements‣Etc.‣The Geostatistical Analyst derives a surface using the values from themeasured locations to predict values for each location in the landscape.91
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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
Page 40 and 41: Vector Data Model‣The data model
Page 42 and 43: Topological ModelTopological relati
Page 44 and 45: Topological ModelOther names for No
Page 46 and 47: Some Basic Topological Relationship
Page 48 and 49: Triangulated Irregular Network (TIN
Page 50 and 51: GIS ANALYSIS FUNCTIONS50
Page 52 and 53: 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 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
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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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