lecture 9 managing a gis project. gis analysis collect and process data to aid in decision making ...
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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
Get data Measures Models Data collection techniques
Analyze data Determine methodology Evaluate results, alternatives
Make maps, graphs, and reports
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.
Decompose the problem into parts The problem
Broad goals More specific goals
Data layers Measurements
Decompose the problem into parts
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 – ????????
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
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
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
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
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 ( *, /)
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
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.
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
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
Data elements Identify the smallest piece of data
Bee Landfill site Parcel
How do model them Points lines polygons Rasters Vectors
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?
Geographic layers Identify the layers required
Landfill site – parcels, roads, flood, slope, soil, geology, sensitive areas (water, rats), historic areas, parks…
Issues influencing analysis
Time - deadline Money People Data Interaction with decision makers Interaction with stake holders
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
Get the data
Buy it Down load it Digitize it Scan it Address match it
But first…. Is it spatial or attribute
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, …
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
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
Determine methodology
Streets StBufBuffer
Sensitive Good/BacReclass
StSen
Complete
AttributeQuery
Not sensitiveNear street
Out of floodGood slope
Select by location
Final sites
FloodZone
Slope Reclass
Union
Suitablezones
Union
Good/Bac
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
Buffering
Proximity analysis Creates new polygons representing specified
distance
Buffer 50 meters Buffer by attribute values
Buffer 100 meters, do not dissolve interior borders
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-ID RIV# DISTANCE X-COORD Y-COORD
1 37 1007.35 458.35 8502.69
2 37 643.84 762.26 7584.36
3 42 93.32 854.45 5241.64
4 42 503.69 251.94 4568.25
Determine where along the river to test for contaminationPollution points
Rivers
+
Dissolving features
Simplify data based on common attribute values
In ArcToolbox, Dissolve is under Data Management Tools > Generalization
9 15
66 15
915
66
2nd
1st
mai
n
Input shapes withattribute values
Fewer output shapes with attribute values
2nd
mai
n
1st1st 1st
Extraction (Clip)
Input roads...
Clipped roads (red) inside circle
Compare with roads (green) selected using select-by-location
Overlay theme
Output theme inherits overlay theme’s attributes
Input theme
Overlay analysis and geoprocessingPoint-in-polygon Line-in-polygon Polygon-on-polygon
Example: Union
Flood
Zone
Flzo
Attributes of FloodFLOOD-ID FLOOD_CODE
0123456
-805010501010
Attributes of ZoneZONE-ID ZONE
01234
INDRESCOMRES
Attributes of FlzoFLZO-ID FLOOD_CODE ZONE
-INDINDINDINDINDRES
.
...
.
.
0123456
-508050101010
1
23
4
56 7
89
10
11 12
13
1
2 34
5 6
12
3
4
Linear / network routing
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
A sample project
Site a new Hockey shop in Redlands Evaluating suitability Uses topological overlay analysis
Identify the question
Where are suitable sites for a new hockey shop?
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
Identify and gather data
Data needed: Streets Existing hockey shops Parcels with zoning information
Determine methodology
Hockey HockBufBuffer
Streets Ramps RampBufBufferExtract(Query)
HockRamp
Complete
AttributeQuery
Away from shopsClose to ramps
Zoned commercial
Select by location
Final sites
Zone
StreetsAttribute
Query
Union
Suitablezones
Union
Process the data
Perform the steps in the methodology
Interpret the results Create a final map and report
Hockey Shop Siting Project
Potential Hockey Shop Locations
Existing shops
Potential shops