Definition of Spatial Analysis

1. Definition of Spatial Analysis • Spatial analysis - The process of modeling, examining, and interpreting model results. • Spatial analysis is useful for • evaluating suitability and capability • estimating and predicting • interpreting and understanding

2. Spatial Analysis - cont. • There are four traditional types of spatial analysis: • Topological overlay and contiguityanalysis • Surfaceanalysis • Linear analysis • Rasteranalysis • Retrieval/classification/measurement • Overlay (arithmetic, various conversions) • Neighborhood • Connectivity

3. Definition of Spatial Analysis • Spatial data analysis involves the application of operations to coordinate and relate attribute data. • Spatial analyses are applied to solve problems related to geographic decisions • Identify high crime area • Selection of a best location for a new business • Extent of sage brush infestation in Idaho. • Spread of a disease • Etc…

4. Definition of Spatial Analysis - cont. • Spatial operations could be applied sequentially • An output could serve as input • Sequence of spatial operations is important Bolstad, 2005

5. Definition of Spatial Analysis - cont. • one input can have many outputs • many inputs can have one output Bolstad, 2005

6. Spatial Operations • Local operations • Neighborhood operations • Global operations Bolstad, 2005

7. GIS Analysis Functions Four broad categories

8. 1. Retrieval, Classification, & Measurement Functions • Retrieval • Selective Search • Classification/Reclassification (Overlays, combine) • Identifying a set of features as belonging to a group • Defines patterns • Measurement • Distances, lengths, perimeters, areas

9. Selection • Selection operations • Involve identifying features based on several conditions or criteria • The attributes or geometry of features are checked against the conditions or criteria • You can write the selected features into new output data layer • You can use the selection for other analysis • Examples

10. Select: • State = Arkansas • States = entirely north of Arkansas • States_area>84,000 sq. mi. • States both entirely north of Arkansas and larger than 84,000 sq. mi. Bolstad, 2005

11. Functions of Spatial Analysis • Conditional selection • Set Algebra • Less than (<) • Greater than (>) • Equal to (=) • Not equal to (<>) • Boolean Algebra • Conditions OR, AND, and NOT Bolstad, 2005

12. Examples of Expression in Boolean Algebra Bolstad, 2005

13. Select by Location - cont. • Selecting options • That Meet • That Overlap • That Contains • That are Contained by • That are Entirely Contained By • That are Spatially Equal • That Touch

14. Examples of Selection by Location States adjacent to Missouri Bolstad, 2005

15. Examples of Selection by Location - cont. States containing a portion of Mississippi River or its tributaries are selected Bolstad, 2005

16. Classification • Categorization of geographic objects based on a set of conditions • Also known as reclassification or recoding • Spatial data operation can be used along with selection operation • Example: classify polygons based on size Bolstad, 2005

17. Classification - cont. • Classification is an operation to create a new group of classes from an existing set of classes • Classification is governed by a a table or array (decided by user before hand) Bolstad, 2005

18. Classification - example • Classification of land use for obtaining your required information

19. Classification - cont. • Binary classification • You need to have two classes • 0 and 1 • True or false • A and B • Some other two level classifications Bolstad, 2005

20. Automatic Classification • Automatic classification • Good for many classes in one feature file (when it is practically not possible to manually classify into groups) • Requires classification schemes (algorithms or mathematical formula) which will combine various classes into a single group • Equal interval • Defined interval • Natural breaks (Jenks) • Standard deviation

21. Classification Examples Quantile classification Bolstad, 2005

22. Retrieval: Selective Search addresses selected because they fall within circle

23. Reclassification (Vector) Dissolving to aggregate polygons

24. Reclassify by Area Size Work with areas > 80 acres

25. Reclassify by Contiguity Work with individual forest stands, rather than the class forest as a whole.

26. Reclassify values Work with elevations between 20 and 40 feet Change feet to meters

27. Buffer • one of the most common spatial analysis tools • specific distance representation around a feature  • The distances can either be constant or can vary depending upon attribute values.  • When features are close together, their buffers may overlap. The user can choose to preserve the overlaps or remove them. • The buffer operation creates a new polygon data set

28. Examples of Buffer Bolstad, 2005

29. Examples of Buffer

30. Vector Distance Operation: Buffers & Setbacks Diagram of simple buffers and a setback. NOTE: buffers go outward from lines or areas; setbacks run inside of areas (not lines). Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems. p 154. fig. 6-1.

31. Buffer Creation: Illustrated Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems. p 60. fig. 6-3.

32. 2. Overlay Functions • Arithmetic • addition, subtraction, division, multiplication • Logical • find where specified conditions occur (and, or, >, <, etc.) • Raster & Vector methods differ • Vector good for sparse data sets • Raster grid calculations easier • Overlay(demo – addition)

33. Overlay • Another common spatial analysis tool • Allows the user to identify areas where features in two layers overlap.  • A new data set is often created from these overlaps.  • In a Union Overlay, all features are included in the new data set but the features that overlap represent a new feature.  • In an Intersect Overlay, only the areas that overlap are contained in the new data set.

34. Overlay Example • Analysis Tools • select Overlay • Intersect tool • Analysis Tools • select Overlay • Union tool

35. Examples Bolstad, 2005

36. Overlay Example - cont. • Vector overlay Bolstad, 2005

37. Overlay: Combining Attributes Select attributes of interest for a given location (Raster & vector methods do this differently, but the results are similar)

38. Vector based Overlay • 3 main types of vector overlay • point-in-polygon • line-in-polygon • polygon-on-polygon

39. Vector based overlay point-in-polygon example

40. Vector based overlay line-in-polygon example

41. Vector based overlay polygon-in-polygon example

42. Raster Based Overlay:Simple Addition Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems. p 144. fig. 5-12.

43. Raster Overlay: Boolean Combine Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems. p 125. fig. 5-3.

44. Raster Overlay: Composite Combine

45. Overlay Example - cont. Raster overlay

46. Vector Overlay: Composite Structure Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems. p 127. fig. 5-5.

47. 3. Neighborhood Functions • Basic Functions • Average, diversity, majority, minimum/maximum, and total • Parameters to define: • Target location(s) • Specification of neighborhood • Function to perform on neighborhood elements

48. 3. Neighborhood Function (cont) • Search Operation • most common neighborhood operation • Example • count the number of customers within 2 miles of the grocery store

49. 3. Neighborhood Functions (cont) • Point or Line in Polygon Operation • Vector Model • specialized search function • Raster Model • polygons one data layer • points or lines in separate data layer • Buffers(demo - point, line, polygon)

50. Neighborhood Functions:4 x 4 Window Processing