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Spatial Analysis and Modeling GEO 442 1. What is Analysis? The process of identifying a research question Modeling that question Investigating model.

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Presentation on theme: "Spatial Analysis and Modeling GEO 442 1. What is Analysis? The process of identifying a research question Modeling that question Investigating model."— Presentation transcript:

1

2 Spatial Analysis and Modeling GEO 442

3 1. What is Analysis? The process of identifying a research question Modeling that question Investigating model results Interpreting the results

4 2. What is Spatial Analysis? Same process but with spatial data Example: Topological overlay An analysis procedure for determining the spatial coincidence of geographic features

5 3. What is modeling? A representation of reality used to –simulate a process –understand a situation –predict an outcome –analyze a problem A model is structured as a set of rules and procedures

6 4. What is Spatial Modeling? Use geographic data to; èdescribe, èsimulate, èor predict real-world problems or systems.

7 3 categories of spatial modeling these can be applied to geographic features within a GIS: –geometric models, distance between features, generating buffers, calculating areas and perimeters –coincidence models, such as topological overlay –adjacency models (pathfinding, redistricting, and allocation)

8 5. Two spatial models for storing geographic data Raster data model - matrix of square cells Vector data model - data stored as coordinates. Similar, represent a layer or set of geographic features like points, lines, and polygons. Different in the way they model or represent spatial data.

9 Vector data model Point, line and polygon objects on a map are stored as as a collection of x and y coordinate pairs in a table. The x and y coordinates represent the point’s distance from an origin point. Points stored as a single pair of x and y coordinates Lines, store the x and y coordinates of the beginning point (from node) of the line and the end point (to node) of the line. Curves or changes in direction - series of x,y coordinate pairs, (vertices), at each direction change between the beginning point and end point of the line. Area (polygon) - enclose it with a line, making the beginning and ending points of the line equal. Polygons which share a boundary are called adjacent.

10 The diagram below shows how real-world objects can be represented on a computer monitor by x,y coordinates. The coordinate pairs 1,5 3,5 5,7 8,8 and 11,7 represent a line (road) The coordinate pairs 6,5 7,4 9,5 11,3 8,2 5,3 and 6,5 represent a polygon (lake). The first and last coordinates of the polygon are the same; a polygon always closes.

11 To keep track of many features, each is assigned a unique identification number or tag. Then, the list of coordinates for each feature is associated with the feature’s tag. The objects you see in a vector theme are actually saved in the theme table

12 Raster data model Location is the main focus of representing geographic features. Earth is treated as one continuous surface. Each location is represented as a cell. Cells are organized into a matrix or rows and columns called a grid.

13 Each row contains a group of cells with values representing a geographic phenomenon. Cell values are numbers, which represent nominal data such as land-use classes or elevation. Cells are identified by their position in the grid. Notice that in a grid, cells have eight (8) neighbors (except those on the outside edges); four at the corners and four at the sides.

14 Like the vector data model, the raster data model can represent discrete point, line and area features. A point feature is represented as a value in a single cell, a linear feature as a series of connected cells that portray length, and an area feature as a group of connected cells portraying shape.

15 Because the raster data model is a regular grid, spatial relationships are implicit. Therefore, explicitly storing spatial relationships is not required as it is for the vector data model.

16 Main component of spatial analyst is the grid theme (raster data model)

17 6. What is a grid theme? A grid divides geographic space into uniform blocks called cells. Used to represent terrain elevation or other phenomena that change gradually across a surface.

18 Elevation grid looks smooth, but, as the zoomed-in graphic at the bottom indicates, it's really composed of thousands of small cells. Each cell, stores an elevation value for the space it covers (about 16,000 square feet per cell for this grid.)

19 Two types of grids: Integer grids store cell values as integers Floating-point grids store values with decimal points

20 7. What is a Surface? Grid themes represent a continuous surface Continuous data, such as elevation or air temperature over an area. Surfaces can be represented by models built from regularly or irregularly spaced sample points on the surface (Interpolation).

21 The top graphic below shows a set of sample elevation points used to generate a surface model. The bottom graphic shows a spatial model actually created from the points.

22 8. Using Spatial Analyst Extension Creates, queries, maps and analyzes data that form continuous geographic surfaces. uElevation uAir temperature uPrecipitation uChemical concentrations (pollutants)

23 Map Algebra Uses math-like expressions that return numeric values to an output grid. Expressions are entered into the Map Calculator in the Avenue syntax.

24 Querying Grids Select areas spatially by defining a Boolean query based on the values of one or more grid themes. Output will be a grid theme with areas that match the query given a value of 1 (TRUE) and areas that do not match the query given a value of 0 (FALSE).

25 Classification Ordering a theme's data values into a specified number of groups according to a particular method. The values in the classified theme are not changed in any way. Floating point grid theme - default classification method is Equal Interval, can be changed to Standard Deviation. Integer grid theme - can be classified by any of the five methods available: Equal Area, Equal Interval, Natural Breaks, Quantile, or Standard Deviation.

26 Contours and Surfaces Can create isolines (a line theme) or a continuous surface (a grid theme) using a point theme of sampled points. Both help analyze continuous change of an attribute over space (elevation, temperature, soils pH level).

27 Cost surface Grid defining the impedance, friction, or cost to move through a cell. Used to determine the least cost path between a source and destination (travel time, dollars, fuel).

28 Proximity Analysis Analyze the distance between features, find the closest feature in another theme Create discreet distance buffers to find features within a distance of other features. A buffer is a zone of specified distance around a feature.

29 Overlay Analysis Compare two or more themes (layers) to reveal new relationships between features in the different themes. New grid theme that contains only the features that meet the requirements of your query. Map Query - ( [ Landuse. desc] = "Agr" ) and ( [Flood Zone] = 1 )

30 Visualization Visualization techniques are used to create topographic and thematic maps, statistical graphs and to visually render surfaces. Hillshading - visualization tool to display hills and valleys in relief. Calculates the effects of illumination on a surface Histograms - another important visualization tool available. A histogram is a chart of the distribution of cell values in a grid theme. Useful to see if the values are skewed to one side of the mean or normally distributed.

31 9. Extending - Spatial Analyst Chapters 1. Start ArcView 2. Choose spatial analyst extension (file - extensions) 3. Notice how ArcView interface changes 2 new menus (Analysis and Surface) Histogram button Contour tool 4. Navigate to extending ArcView datasets (c:\extend) to begin exercises 5. Answer questions for Chapters 8 - 14

32 Spatial Analysis In order to solve any problem by Geographic information System (GIS) modeling a series of steps must be followed These steps are typical for addressing any problem with some difference in details for each problem domain

33 Spatial Analysis Single layer operations (proximity) Multiple layer operations (Union, Intersect) Network analysis (shortest path) Surface analysis (TIN, Aspect, Slope) Grid analysis (flow direction, diffusion)

34 Steps for Spatial Analysis Establish analysis objectives and criteria Prepare data for spatial analysis (spatial + attribute) Perform spatial operations (buffering, overlay, feature extraction) Perform tabular analysis using arithmetic and logical operations;

35 Reselect

36 Buffer

37 Intersect

38 Erase

39 Flow chart for database Geographic database ArcView shape files Spatial analysis A system Transform to real- world co-ordinates Import to ARC/INFO Create topology Build and Clean Check feature accuracy Digitisation AutoCAD Attribute dBASEI V.

40 Evaluate and interpret the results (validity and checking by producing plots and reports) Refine the analysis by identifying the shortcomings and limitations of the analysis Produce final maps and tabular report of the results. Steps for Spatial Analysis- Continue

41 Example for spatial analysis Finding suitable dumping site How can I find a suitable dumping site, that is economically, legally, and environmentally sounded?

42 Find a suitable dumpsite using GIS Groundwater contamination Surface water contamination Soil contamination Water and air quality Noise pollution Human health due to methane and carbon Marine environment Factors to be considered

43 Economy Atmosphere Surface water Biotic life Soil Water Legality Dumping site Environment Groundwater

44 Data collection Geology, Groundwater Rivers, Coastal line Soil, Landuse Airport, Roads Settlements, Hotels Spatial + Attribute data

45 Add attribute data Digitization under AutoCad Transform to real coordinate Import to ARC/INFO Create topology Build and Clean Check feature accuracy Geographic database ArcView- shape files Geographic analysis Steps for data preparation

46 Feature extraction from a GIS database Feature extraction from a GIS database can be done using commands such as CLIP, ERASE, IDENTITY, and RESELECT. Logic such as SELECT, ASELECT, NSELECT and boolean operators (=,, >, =, <=, EQ, NE, GT, LT,GE, LE, CN, IN). These commands can be used to identify areas that met the desired criteria.

47 Perform spatial operations Feature extraction from a GIS database (Reselect) Map overlay (Intersect, Union, Mapjoin) Proximity searches (Buffering)

48 Geographical objects Landuse Topography Soil type Utility Rivers Roads District Lots

49 Example Project Steps Layer 1: Lake Layer 2: Forest Layer 3: Soil Drainage Layer 4: Loggable Species Layer 8: Species And Soils SpreadRecode Layer 5: Drained Soils Layer 6: Near Lake Layer 7: Away From Lake OverLay Layer 9: Loggable Sites Recode

50 Produce final maps and tabular report of the results

51 System design User interaction Reselect Geology Land use Soil Rainfall Buffer Roads Rivers Intersect suitable zones for each factor Suitable zones The best zones

52 User interaction Select suitable layer for dumping: Geology Rainfall Productivity Land use B1 24202500 Getah C2 24404000 Kelapa C3 24606000 Padi D3 2480 Pekan D4 Final zones Help

53 Data about geology

54 Screening

55 Example for groundwater selection

56 Confirmation of the selection

57 Suitable groundwater zones

58 Unsuitable zones around rivers

59 Spatial Modelling Step 1: State your research question(s). Then create a flowchart to organize the data and analyses that you will perform to explore/answer your research question(s) (I will give you an example flowchart).

60 The following is an example of a research project with a sample flow chart uYour city is looking into alternative energy sources that will provide clean and inexpensive power for residents. The city has decided to look into solar power since coal pollutes, oil may run short, nuclear is hazardous. uYour data set consists of elevation points and power lines. uYou need to generate a list of criteria in aiding you in this siting problem.

61 To do so you use this diagram:

62 èThe list of criteria you develop define your spatial model. èSome spatial analysis problems can be very complex, involving many data sets and processing tasks. èIt is often helpful to create a flowchart of the analysis to organize the data and tasks.

63 The flow chart outlines the solar energy station siting model that would be performed in this research project:


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