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Understanding Geographic Information Systems: Analysis, Data Maintenance, and Spatial Modeling

This document provides an in-depth overview of Geographic Information Systems (GIS) analysis and modeling. It covers essential questions pertaining to location, timing, and future predictions, followed by the organization and maintenance of geographic data. Key concepts include managing spatial and attribute data, integrated analysis, and various measurement techniques. The importance of data layers (points, lines, polygons) and overlay techniques (arithmetic and logic) in GIS is emphasized. This resource is aimed at facilitating efficient GIS practices for enhanced spatial analysis.

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Understanding Geographic Information Systems: Analysis, Data Maintenance, and Spatial Modeling

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  1. Geographic Information Systems GIS Analysis and Modeling

  2. 1. Geographic Analysis • Geographic questions: where, when, why, and how • The purpose of the analysis is to answer questions about: - what existed at where, when, why, and how - what will happen at where in the future or in other locations

  3. 2. Organizing Geographic Data • Data layers (shape file etc.) • Feature types: points, lines, polygons • Object types: geometric or thematic e.g. Development streets - line layer1 water - line layer2 parcels - polygon layer1 soils - polygon layer2

  4. 3. Maintenance of the Spatial Data • Format transformation - Spatial data files must be transformed into the data structures and file formats used internally by a GIS software package • Geometric transformation - Different data layers should be registered to a common coordinate system

  5. 4. Maintenance of Attribute Data • Attribute editing - List, add, delete, redefine, etc. • Attribute query - Retrieve attributes according to certain criteria

  6. 5. Integrated Analysis of Spatial and Attribute Data • The power of GIS lies in its ability to analyze spatial and attribute data together • Retrieval, classification, and measurements • Overlay

  7. 5. (1) (i) Retrieval • Selective search without modifying the original data (for output) http://www.sdsmt.edu/online-courses/geology/mprice/geo416/lecture9.ppt

  8. 5. (1) (ii) Classification • Attribute data - cerate a new attribute item based on existing ones • Spatial data -spatial features may be aggregated to larger entities e.g. Recode in a raster environment Dissolve in a vector environment • Single layer vs. multiple layers (overlay)

  9. Classification Raw data Classified data http://www.geog.leeds.ac.uk/courses/level2/geog2750/geog2750_15.ppt

  10. 5. (1) (iii) Measurement • Distances between points • Nearest distances • Functional distances • Lengths of lines • Perimeters and areas of polygons • Centroid of an area • Area of a profile • Volume • Shape • Narrowest and broadest distances across a polygon • Sinuosity of a line

  11. 5. (1) (iii) Measurement • Distances between Points - Euclidian distance

  12. 5. (1) (iii) Measurement • Nearest distances The Closest Facility

  13. 5. (1) (iii) Measurement • Functional Distance Three-minute response time from a fire station, City of Phoenix http://www.esri.com/mapmuseum/mapbook_gallery/volume17/public2.html

  14. 5. (1) (iii) Measurement • Lengths of lines • Perimeters and areas of polygons

  15. 5. (1) (iii) Measurement • Centroid of an area • It is used to represent a polygon by a single point • Several methods to identify a centroid: mean value of vertices’ coordinates, center of the enclosing circle or rectangle, http://www.geoict.net/tgipage/Teaching/UNIT%207--PPT.pdf

  16. 5. (1) (iii) Measurement • Area of a profile • Volume

  17. 5. (1) (iii) Measurement • Shape - how to measure shape of an area? - a compact shape has a small perimeter for a given area • compare perimeter to the perimeter of a circle of the same area - shape = perimeter / area • Narrowest and broadest distances across a polygon

  18. 5. (1) (iii) Measurement • Sinuosity of a line - the ratio of the actual length to the straight line length between point A and point B

  19. 5. (2) Overlay • Arithmetic overlay • Logic overlay • Weighting input layers • Raster vs. vector overlay

  20. 5. (2)(i) Arithmetic Overlay • adding layers, subtracting, multiplication, division, etc. • Raster Input data layer A Input data layer B Output data layer

  21. 5. (2)(i) Arithmetic Overlay • Arithmetic operation on two data layers using the vector data model Attribute data Spatial data Input data layer A Input data layer B Output data layer

  22. 5. (2)(ii) Logic Overlay • Finding areas where certain conditions occur • Boolean logic Mary Ruvane, UNC –Chapel Hill

  23. 5. (2)(iii) Weighting Input Layers • Professional experiences • Expert votes • Empirical or analytical models

  24. 5. (2)(iv) Raster vs. Vector Overlay • Raster - Every cell is executed, and the overlay result is a new layer • Vector - The operation is executed only for areas of interest • - New attribute items are created • - New layers may be created that carry both the original and new attributes - The operation is generally more complex than raster overlay

  25. Raster Overlay Vector Overlay http://www.geoict.net/tgipage/Teaching/UNIT%207--PPT.pdf

  26. Readings • Chapter 5,6,9,10

  27. 3.(3) Conflation • The procedure of reconciling the positions of corresponding features in different data layers (e.g. snapping).

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