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GIS Lecture 8 Spatial Data Processing PowerPoint Presentation
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GIS Lecture 8 Spatial Data Processing

GIS Lecture 8 Spatial Data Processing

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GIS Lecture 8 Spatial Data Processing

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  1. GIS Lecture 8 Spatial Data Processing

  2. Outline • Extracting Features by Attributes • Location Proximities • Geoprocessing Tools • Model Builder

  3. Extracting Features

  4. Attribute Query Extraction • You have tracts for state but want one county only

  5. Attribute Query Extraction • Select tracts by County ID

  6. Export Selected Features • Right-click to export selected features

  7. Add Exported Layer

  8. Location Proximities

  9. Select by Location • Identify spatial relationships between layers • Finds features that are within another layer. Input: County Census TractsCan’t use Select By Attributes Output:City tracts only

  10. Select by Location • Select feature to extract tracts to (city outline)

  11. Select by Location • Selection, Select By Location

  12. Export Selection and Add Layer

  13. Other Select by Location Queries • Toxic release sites within 1 mile of a river

  14. Other Select by Location Queries • Points near points • Schools within ½ mile of polluting companies

  15. Other Select by Location Queries Polygons intersecting lines Municipalities that intersect Interstates

  16. Other Select by Location Queries Linesintersectingpolygons

  17. Other Select by Location Queries • Buildings whose centers are in emergency zones

  18. Geoprocessing Tools OverviewClipping Features

  19. Geoprocessing Tools • GIS Operation to manipulate data • Typically take input data sets, manipulate, and produce output data sets • Often use multiple data sets

  20. Geoprocessing Tools • Clip • Dissolve • Intersect • Union • Append

  21. Clipping Features

  22. Clip “Cookie cutter” to select features =

  23. Clipping Features (Points, Lines, Polygons) X Y Z = = =

  24. Line (Arc) Clipping Input layer - Streets Clip layer – Central Business District (selected) Output layer - Streets within Central Business District

  25. Clip Geoprocessing Tool

  26. Difference Between Clipping and Select by Location Clip: Clean “cut” Select by Location:Dangle edges

  27. Dissolving Features

  28. Dissolve Aggregates items that have the same value # Item 1 C 2 R 3 C 4 I

  29. Dissolve Example • You have states but need regions

  30. Dissolve Functions • ArcToolBox or Command Line Window

  31. Dissolve Field Field with a common value for each feature (e.g. Sub_Region)

  32. Statistics Field Aggregated field can be summarized using a statistics type (i.e. state population can be aggregated by population for each region)

  33. Resultant Dissolved Regions Layer

  34. Appending Features

  35. Append • Appends features together

  36. Append Streets • Separate street layers for neighborhoods

  37. Append Streets • Choose both street layers to append

  38. Resultant Layer • One street layer with all records and field items

  39. Union Features

  40. Union • Use Union when you want to overlay two polygon layers so that the resulting output layer • a) has the combined attribute data of the polygons in the two inputs, and • b) contains all the polygons from the inputs, whether or not they overlap.

  41. Union Start with Pittsburgh ZIP codes and Neighborhoods

  42. Union • Attributes tables contain different data

  43. Union Union neighborhoods and ZIP Codes to include the zip on each neighborhood polygon

  44. Union • Result: Polygons are unioned with same information • Tips: Same Projections, Order of Layers

  45. Intersecting Features

  46. Intersect • Use Intersect when you want to overlay a layer with the polygons in another layer so that the resulting output layer • - has the combined attribute data of the features in the two inputs, and • - only contains features that fall within the spatial extent of the overlay polygons

  47. Intersect Flood zones that intersect buildings

  48. Intersect Result is only building polygons that intersect floodzones with combined data fields

  49. Model Builder

  50. Model Builder • Workflow processes can be complicated • Automates and strings functions together