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. 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 48 th largest city Total 66,463

12. Measurement scales Nominal – Names soils, vegetation (=) Ordinal – Order, 1 st, 2 nd, 3 rd ( ) 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 StreetsStBuf Buffer SensitiveGood/Bac Reclass StSen Complete Attribute Query Not sensitive Near street Out of flood Good slope Select by location Final sites FloodZone Slope Reclass Union Suitable zones Union Good/Bac

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

29. 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 POL-IDRIV#DISTANCEX-COORDY-COORD 1371007.35458.358502.69 237643.84762.267584.36 34293.32854.455241.64 442503.69251.944568.25 Determine where along the river to test for contamination Pollution points Rivers +

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

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

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

33. 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 HockeyHockBuf Buffer StreetsRampsRampBuf Buffer Extract (Query) HockRamp Complete Attribute Query Away from shops Close to ramps Zoned commercial Select by location Final sites Zone Streets Attribute Query Union Suitable zones Union

41. Process the data Perform the steps in the methodology

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