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Lecture 9

Lecture 9. Managing a GIS project. GIS analysis. Collect and process data to aid in decision making Use the data to make decisions Identify alternatives Understand the system Information = models + data (P. A. Burrough). Stages in a GIS project. Define problem Goals and objectives

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Lecture 9

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  1. Lecture 9 Managing a GIS project

  2. GIS analysis • Collect and process data to aid in decision making • Use the data to make decisions • Identify alternatives • Understand the system • Information = models + data (P. A. Burrough)

  3. Stages in a GIS project • Define problem • Goals and objectives • Get data • Measures • Models • Data collection techniques • Analyze data • Determine methodology • Evaluate results, alternatives • Make maps, graphs, and reports

  4. Define the problem • Where can we put the new landfill site? • Will San Francisco and Atlanta have killer bees? • We need to make parcel and tax maps.

  5. Decompose the problem into parts • The problem • Broad goals • More specific goals • Data layers • Measurements

  6. Decompose the problem into parts

  7. Decompose the problem into parts • The problem – Landfill site • Broad goals – Protect ground water • More specific goals – Porous soil • Data layer - Soils • Measure – Soil types, sand, clay, loam, silt • Broad goals – Must be accessible • More specific goals – Near a road • Data layer - Roads • Measure – Street names (lines or polygons?) • Broad goals – Sound ground • More specific goals – Away from faults, low slope • Data layer - Fault lines, slope of land • Measure – ????????

  8. Measuring/Collecting the data • How are these measured? • Data layer and measure – Soils - soil types • Data layer and measure – Roads • Data layer and measure – Fault lines • Data layer and measure – Slope of land

  9. Measuring/Collecting the data • Direct measures • Data layer and measure – Soils - soil types • Data layer and measure – Roads • Data layer and measure – Fault lines • Proxy measures • Data layer and measure – Slope of land • Derived from elevation data

  10. Measurement units Will San Francisco and Atlanta have killer bees? • Can these layers be compared with map algebra or any math? • Bees and other bees • 50 degrees and colder • Vegetation, trees • Elevation, 1200 feet • Rainfall, 14 inches per year

  11. Measurement units • How many feet is 10 degrees • Redlands • Population: 65,000 • Elevation: 1,200 • August average temp: 98 • Degrees west 117 • State size rank 48th largest city • Total 66,463

  12. Measurement scales • Nominal – Names soils, vegetation (=) • Ordinal – Order, 1st, 2nd, 3rd (< >) • Interval – Temps, elevation (+, -) • Ratio – Has a defined 0, Zero is absence of the value, Money ( *, /)

  13. Use the same measure • The problem – Landfill site • Broad goals – Protect ground water (Cost of liner) • More specific goals – Porous soil • Data layer and measure – Soils - soil types • Broad goals – Must be accessible (Cost of adding road) • More specific goals – Near a road • Data layer and measure – Roads • Broad goals – Sound ground (Black out areas) • More specific goals – Away from faults, low slope • Data layer and measure – Fault lines, slope of land

  14. Is the problem New or old • New • Will San Francisco and Atlanta have killer bees? • Has the problem been solved before • Where should we put the landfill? • Is there a system currently in place • Get parcel maps upon citizen request.

  15. How is the current problem solved? Get parcel maps upon citizen request. • What are the inputs • Request with address or parcel number • What process happens • Search for parcel map in cabinets • What data layers are used • Streets, parcels • What are the outputs • Maps, reports, charts how many, how often

  16. Learn the current system Will San Francisco and Atlanta have killer bees? • What process happens • Bee hives make queens, they move out and make new hives • What variables (may become data layers) • Bees and other bees • 50 degrees and colder • Vegetation • Elevation • Rainfall

  17. Data elements • Identify the smallest piece of data • Bee • Landfill site • Parcel • How do model them • Points lines polygons • Rasters • Vectors

  18. Geographic area • Identify the size of the study area • Bee - world • Landfill site - county • Parcel - city • What scale are the output maps? • What scale should the data be collected at?

  19. Geographic layers • Identify the layers required • Landfill site – parcels, roads, flood, slope, soil, geology, sensitive areas (water, rats), historic areas, parks…

  20. Issues influencing analysis • Time - deadline • Money • People • Data • Interaction with decision makers • Interaction with stake holders

  21. Stages in a GIS project • Define problem • Goals and objectives • Get data • Measures • Models • Data collection techniques • Analyze data • Determine methodology • Evaluate results, alternatives • Make maps, graphs, and reports

  22. Get the data • Buy it • Down load it • Digitize it • Scan it • Address match it • But first…. Is it spatial or attribute

  23. Get the spatial data • What layers are needed • Raster or vector • What features to represent • What projection • What scale • Date • Legally usuable? • What data format • How big of an area, city, state, …

  24. Get the attribute data • What format, Access, Oracle, SQL server • Will you mix formats, shapefiles and coverages • How much space will be needed 100 mb, gb, tb • Will tables be normalized, which form, • Will tables have a primary key to other tables • Which you use codes, will you have metadata to describe • 1 - River • 2 - Road • 3 - Agriculture • 4 - Buildings

  25. Stages in a GIS project • Define problem • Goals and objectives • Get data • Measures • Models • Data collection techniques • Analyze data • Determine methodology • Evaluate results, alternatives • Make maps, graphs, and reports

  26. Determine methodology Reclass Sensitive Good/Bac Union StSen Buffer Streets StBuf Union Complete FloodZone Not sensitive Near street Out of flood Good slope AttributeQuery Suitable zones Select by location Reclass Good/Bac Slope Final sites

  27. Analysis functions • Create buffer zones • Near/distant • Polygon operations / Overlay polygons • Linear • Drive time • Route from a to b • Visit 20 sites • Line of sight

  28. Buffer 50 meters Buffer 100 meters, do not dissolve interior borders Buffer by attribute values Buffering • Proximity analysis • Creates new polygons representing specified distance

  29. Rivers + Pollution points Near • Calculate distance from all points in one cover to features in another • For each point, Adds the feature number of the closest feature and the distance from the point to that feature Determine where along the river to test for contamination

  30. 15 9 9 15 15 66 66 Input shapes withattribute values Fewer output shapes with attribute values 2nd 2nd main main 1st 1st 1st 1st Dissolving features • Simplify data based on common attribute values • In ArcToolbox, Dissolve is under Data Management Tools > Generalization

  31. Clipped roads (red) inside circle Compare with roads (green) selected using select-by-location Extraction (Clip) Input roads...

  32. Input theme Overlay theme Overlay analysis and geoprocessing Point-in-polygon Line-in-polygon Polygon-on-polygon Output theme inherits overlay theme’s attributes

  33. Attributes of Flood Flood FLOOD-ID FLOOD_CODE 2 3 - 0 80 1 4 1 50 2 10 3 50 4 6 10 5 5 10 6 Zone Attributes of Zone 2 ZONE-ID ZONE 1 3 0 1 IND 2 RES 4 3 COM 4 RES Attributes of Flzo 5 Flzo FLZO-ID FLOOD_CODE ZONE 7 13 1 6 - - 0 8 2 50 IND 1 3 9 80 IND 10 2 50 IND 3 10 IND 4 12 11 10 IND 5 4 10 RES 6 . . . . . . Example: Union

  34. Linear / network routing

  35. Stages in a GIS project • Define problem • Goals and objectives • Get data • Measures • Models • Data collection techniques • Analyze data • Determine methodology • Evaluate results, alternatives • Make maps, graphs, and reports

  36. A sample project • Site a new Hockey shop in Redlands • Evaluating suitability • Uses topological overlay analysis

  37. Identify the question • Where are suitable sites for a new hockey shop?

  38. Identify the issues • Criteria: • Close to freeway ramps • Within 2000 meters • Away from existing hockey shops • 1500 meters away • Zoned commercial • On a major street

  39. Identify and gather data • Data needed: • Streets • Existing hockey shops • Parcels with zoning information

  40. Determine methodology Extract(Query) Buffer Streets Ramps RampBuf Union HockRamp Buffer Hockey HockBuf Union Complete Zone Away from shops Close to ramps Zoned commercial AttributeQuery Suitable zones Select by location AttributeQuery Streets Final sites

  41. Process the data • Perform the steps in the methodology

  42. Interpret the results • Create a final map and report Potential Hockey Shop Locations Potential shops Hockey Shop Siting Project Existing shops

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