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Basic Spatial Analysis

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  1. Basic Spatial Analysis May 30, 2013 Institute of Space Technology, Karachi

  2. Spatial Analysis • Involves applications of operations to coordinates and related attribute data

  3. Chapter 9 of your text book.

  4. Spatial Data Analysis • Spatial analyses are applied to solve problems related to geographic decisions • Examples: • Identify high crime areas • Generate a list of road segments that need repaving • Select a best location for a new business Input Layer  Spatial Operation Output Layer

  5. Sequence of Spatial Operations Single Spatial Operations

  6. Challenge!!!! • Selecting appropriate spatial operations and applying them in the appropriate order

  7. Spatial Data Analysis Application of operations to coordinates and related attribute data • Non Spatial Queries(standard Database queries) • How long is River Indus? • Population of Pakistan? • etc. • Spatial Queries • Neighboring countries of Pakistan? • List of provinces through which Indus river flows?

  8. Spatial Data Analysis • Since attribute data is related to spatial objects therefore we can not separate operations on attribute data from operations on coordinate portion of spatial data

  9. Spatial Operations • Applied to one or more input layers to produce one or more output data layers • One to One • Conversion of raster data into vector • One input – Many outputs • Slope and aspect produced from raster elevation model • Many inputs – one output • To calculate data averages from different layers

  10. Spatial Operations

  11. Spatial Operations • Depends on type of data model used • Specific operations available in the GIS software • In many instances it’s more efficient to convert data between data models and apply the desired operations and convert results back to the original data model

  12. Spatial Operations Outputs • Non Spatial outputs • Spatial operation produces scalar value, a list, or a table with no explicit geometric data attached • Spatial • New data layer is produced

  13. Spatial Scope Spatial operations may be characterized by their spatial scope • Local Operations • Neighborhood Operations • Global Operations

  14. Spatial Data Analysis • Selection • Reclassification • Dissolving • Buffering • Overlay

  15. Selection • Features are identified based on given criteria Example: in a political map of European countries, select all names and population of countries with more than 50M inhabitants Above is an example of set algebra • >, <, =, & <> • Used either alone or in combination

  16. Selection Thematic map of countries of western Europe (and their population); selection of countries with more than 50M people

  17. Selection: Set Algebra

  18. Selection • Boolean Algebra • Conditions: AND, OR, NOT • Combines set algebra and create compound spatial selection

  19. Expression In Boolean Algebra

  20. Selection by Location • Adjacency • Containment

  21. Reclassification • Classification of spatial objects based on spatial or non spatial data • Example: classification of Polygons based on size • Examples of Reclassification • Equal Interval • Equal Area • etc.

  22. Dissolve • Combines or dissolve similar features within a data layer • Adjacent polygons with identical values are merged into a single polygon

  23. Proximity • Modifies existing feature or creates new features that depend on distance • Available water represented by Points and distance function applied to these points to create raster data layer containing the distance to nearest water feature.

  24. Proximity: Distance Calculations • Distance values are calculated using Pythagorean formula • Calculated from cell center to cell center (when applied to raster data)

  25. Buffers • Commonly used proximity function • Represents specific distance around a feature • May be determined for point, line, or area features • Also for both types of data models

  26. Overlay • Overlapping different themes (multiple layer operation) • Areas where features in different layers overlap • Both spatial and attribute data is combined • Clip, Intersect and union are special cases of overlay

  27. Vector Overlay • Clip • Only the areas that overlap are contained • Cookie cutter approach • Intersect • Combines data from both layers but only for a given region where both layers contain data • Union • Both overlapping and non-overlapping areas are contained

  28. Overlay - Examples

  29. Raster Overlay • Cell by cell combination of 2 or more data layers • Typically applied to nominal or ordinal data

  30. Geoprocessing in ArcGIS Set of software functions used to manipulate and transform spatial data (single layers or multiple sets of layers), to create new information • Map Overlay functions: combining layers to create single output • Extraction • Intersection • Dissolve • Buffer • Append and Merge

  31. Extraction • Clip: cookie cutter function • Layers to be clipped: point, line, polygon • Clipping layer: • When the Input Features are polygons, the Clip Features must also be polygons • When the Input Features are lines, the Clip Features can be lines or polygons. • When the Input Features are points, the Clip Features can be points, lines, or polygons. • Erase: Opposite of clip

  32. Intersection & Union • Intersect • Merges attributes between layers, points-lines-polygons • Union • Combines two polygon layers, keeping all areas and merging attributes

  33. Intersection & Union

  34. Dissolve • Combines and dissolves similar features within a data layer

  35. Buffers • Creates region at specific distance from one or more features

  36. Buffers • Undissolved Buffer • Separate Polygons • Dissolved Buffers • Merged Polygons

  37. Append and Merge • Combine 2 layers into 1 • Merge “edges” of adjoining layers with identically matching polygons and attributes • Append data while maintaining the attributes contained in the selected layer

  38. ARcGIS Tool for Geoprocessing • To be covered in Lab

  39. a. Clip tool ArcTool Box- Analysis Tools – Extract - Clip b. Erase tool ArcTool Box – Analysis Tools – Overlay - Erase c. Intersect tool ArcTool Box – Analysis Tools – Overlay – Intersect d. Union tool ArcTool Box - Analysis Tools – Overlay - Union e. Dissolve tool Arc Tool Box – Data Management Tools – Generalization - Dissolve f. Buffer tool ArcTool Box - Analysis Tools – Proximity - Buffer g. Append tool Arc Tool Box – Data Management Tools-General – Append h. Merge tool Arc Tool Box – Data Management Tools- General – Merge

  40. Using Model Builder • Models are built to automate geoprocessing workflow

  41. References • • • • NCRG Training Courses, “Introduction to GIS” Prepared by Training, R&D Division • GIS Fundamental by Paul Bolstad

  42. Union Query • Union operation from relational algebra • Applied ONLY to thematic maps with same attribute schema Example: union of the map containing European countries with more than 10M inhabitants and the map containing European countries with less than 10M inhabitants. The two maps both have schema (name, population)

  43. Union Query Thematic map of countries (and population) of western Europe with more than 10M inhabitants Thematic map of countries (and population) of western Europe with less than 10M inhabitants