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

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Calculate the empirical semivariogram‣The Semivariogram/Covariance Cloud allows you to examine the spatialautocorrelation between the measured sample points.‣Since closer locations should be more alike, in the semivariogram the closelocations (far left on the x-axis) should have small semivariogram values (low onthe y-axis)‣As pairs of locations become farther apart (moving to the right on the x-axis ofthe semivariogram cloud), they should become more dissimilar94
Understanding a semivariogram—the range, sill, and nugget‣ Sample locations separated by distances closer than the range are spatiallyautocorrelated, whereas locations farther apart than the range are not.‣range= The distance where the model first flattens out‣sill = The value that the semivariogram model attains at the range (the valueon the y-axis).Theoretically, at zero separation distance (i.e., lag = 0), the semivariogram valueshould be zero.However, at an infinitesimally small separation distance, the difference betweenmeasurements often does not tend to zero.This is called the nugget effect.For example, if the semivariogram model intercepts the yaxis at 1.34, then 95thenugget is 1.34.
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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
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
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Page 86 and 87: Network FunctionsConnectivity (Netw
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Page 90 and 91: The principles of geostatistical an
Page 92 and 93: Geostatistical Analyst‣A major ch
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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