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Geographic Information Systems

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Presentation on theme: "Geographic Information Systems"— Presentation transcript:

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)

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

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

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,

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
- 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

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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