1 / 66

GIS Analysis Functions

GIS Analysis Functions. INLS 110-111 GIS Digital Information: Uses, Resources & Software Tools. GIS Analysis Functions. Four broad categories Retrieval/classification/measurement Overlay (arithmetic, various conversions) Neighborhood Connectivity.

jela
Télécharger la présentation

GIS Analysis Functions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. GIS Analysis Functions INLS 110-111 GIS Digital Information: Uses, Resources & Software Tools

  2. GIS Analysis Functions • Four broad categories • Retrieval/classification/measurement • Overlay (arithmetic, various conversions) • Neighborhood • Connectivity

  3. 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

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

  5. Reclassification (Vector) Dissolving to aggregate polygons

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

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

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

  9. 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.

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

  11. 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)

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

  13. Overlay: 4 Basic Rules #1 Enumeration Rule: Each Attribute preserved in output #2 Dominance Rule: One value wins

  14. Overlay: 4 Basic Rules #3 Contributory Rule: each attribute value contributes to result #4 Interaction Rule: pair of values contribute to result

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

  16. Vector based overlay point-in-polygon example

  17. Vector based overlay line-in-polygon example

  18. Vector based overlay polygon-in-polygon example

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

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

  21. Raster Overlay: Composite Combine

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

  23. 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

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

  25. 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)

  26. 3. Neighborhood Functions (cont) • Thiessen Polygons Operation • defines the individual area of influence around a point • used to predict values at surrounding points from a single point observation • can produce polygons with shapes unrelated to phenomenon being mapped

  27. Example: Neighborhood Function Thiessen Polygons

  28. Neighborhood Functions:Implementing Used for calculating the mean, standard deviation, sum, or range of values within the immediate or extended neighborhoods.

  29. Neighborhood Functions:4 x 4 Window Processing

  30. Neighborhood Functions:Annulus Neighborhood Processing

  31. Neighborhood Functions:Circular Neighborhood Processing

  32. Neighborhood Functions:Wedge Neighborhood Processing

  33. Neighborhood Functions:Example Zone theme: Watersheds Value theme: Elevation Statistic type: Mean Output: Mean elevation of each watershed

  34. Neighborhood Functions:10x10 averaging filter on a DEM

  35. 4. Connectivity Functions • Used to accumulate values over an area being navigated • Parameters to define: • specification of way spatial elements are connected • rules that specify allowed movement along interconnections • a unit of measurement

  36. 4. Connectivity Functions (cont). • Proximity Operation • measure of the distance between features • not restricted to distance; can be noise, time, pollution, etc. • Parameters to define: • target location • unit of measure • function to calculate proximity (distance/time/noise) • area to be analyzed

  37. Example: Connectivity (Raster) Proximity Operation: Distance From Neighbor

  38. Example: Connectivity (Vector) Proximity Operation: Road Buffer

  39. Example: Connectivity (Vector) Proximity Operation: Buffer Generation

  40. Example: Connectivity (Vector) Proximity Operation: Buffer Types Points Lines Polygons

  41. Example: Connectivity (Vector) Proximity 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.

  42. 4. Connectivity Functions (cont). • Contiguity Operation • spatial units are connected - defines “unbroken area” • Contiguity measures: • size of neighboring area(s) • shortest/longest straight line distance across adjacent area(s) • specific shape of neighboring area(s)

  43. Contiguity Functions Combines adjacent units together when they share a common attribute

  44. 4. Connectivity Functions (cont). • Network Operations • set of interconnected lines that represent a set of features through which resources flow • Common network functions • shortest path problem (route optimization) • location-allocation modeling (resource allocation) • traveling salesperson problem (route optimization) • route tracing (prediction of network loading)

  45. Example: Connectivity (Vector) Network Function: Location-Allocation

  46. Spread Functions: Travel Time – Creating Friction Surface

  47. Spread Functions: Travel Time – Friction Surface Friction Surface Data Layer Start Point Data Layer Cumulative Travel Time Data Layer

  48. Spread Functions: Travel Time – Map

  49. Spread Function: Calculation of Distance

  50. Spread Function: Equidistant Travel Zones from Target (A)

More Related