lecture 9 managing a gis project. gis analysis collect and process data to aid in decision making ...

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