GIS Applications and Preparing for a Career in Geographic Information Science

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GIS Applications and Preparing for a Career in Geographic Information Science Michael Wing Assistant Professor OSU Forest Engineering Department

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GIS Applications and Preparing for a Career in Geographic Information Science. Michael Wing Assistant Professor OSU Forest Engineering Department. Presentation Topics. Summary of two recently completed GIS applications that focused on forested resources in Oregon - PowerPoint PPT Presentation

Transcript of GIS Applications and Preparing for a Career in Geographic Information Science

Page 1: GIS Applications and Preparing for a Career in Geographic Information Science

GIS Applications and Preparing for a Career in Geographic

Information Science

Michael WingAssistant Professor

OSU Forest Engineering Department

Page 2: GIS Applications and Preparing for a Career in Geographic Information Science

Presentation Topics

Summary of two recently completed GIS applications that focused on forested resources in Oregon

Suggestions for your development as a geographic information scientist

Page 3: GIS Applications and Preparing for a Career in Geographic Information Science

Using Geostatistics to Quantify LWD Distribution

Examined geostatistical tests for their usefulness in quantifying LWD distributions

Part of a study to test the effects of adding LWD to streams LWD is critical for aquatic habitat quality

Hudson Creek in Oregon’s southern coast rangeLocations of all LWD measured prior and

following introduction of LWD into a stream

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N

0 5 10 Meters

Flow

PointsPoints with volumesVolume by surface

Figure 1. Examples of data models used in geostatistical analyses.

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Survey R n (locations)

z (1.96)

Interpretation

Pre 0.97 108 -0.58 Failed to reject null- points randomly distributed Post 0.87 192 -3.34 Null rejected- tendency towards clumping

Year 1 0.85 183 -3.84 Null rejected- tendency towards clumping Year 2 0.79 266 -6.26 Null rejected- tendency towards clumping Year 3 0.88 272 -3.49 Null rejected- tendency towards clumping

Table 1. Nearest neighbor results for Hudson Creek.

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0 5 10 15 20

lag (m)

0.0

0.5

1.0

1.5

PrePostYear 1Year 2Year 3

Figure 2. Semi-variance of large woody debris centroid volumes.

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0 5 10 15 20

lag (m)

0.002

0.003

0.004

0.005

PrePostYear 1Year 2Year 3

Figure 3. Semi-variance of large woody debris lattice volumes

Page 8: GIS Applications and Preparing for a Career in Geographic Information Science

Results

All three tests captured differences in spatial variation over time geostatistics show potential for use as a

descriptive toolThird data model using a semi-variogram

provided the most useful results modeled the entire surface of the stream captured increased spatial variation of LWD

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Role of GIS for LWD ProjectAllowed us to create three different data

models: point point with LWD volume entire stream surface area by LWD volume

(regions data model)Enabled two spatial statistical tests using

three data models flexibility in formatting data for statistical tests

Page 10: GIS Applications and Preparing for a Career in Geographic Information Science

Visibility Analysis ofMcDonald Forest

Part of OSU’s research forests (29 km2)Quantify visibility of all forest area based

on detailed user countsCreate a map for the entire forest that

representsing visibility

Page 11: GIS Applications and Preparing for a Career in Geographic Information Science

0 1 2 Miles

Use Estimates (quantile distribution)27 - 213218 - 628653 - 1,3211,323 - 3,3943,437 - 21,620

Boundary

Total use estimates for McDonald Forest

Roads: 104 kmTrails: 40 kmApproximately 65,000 recreational visits in 1994.

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Results in quantifying visibility for each 10 m cell in the forest Raster or vector data structure can be returned

Data InputsDEM (10 meter resolution)Stand heightRoad and trail locations

user densities for each road and trailObserver height, view distance radius, vertical offset

Data Output

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Visibility (number of people)01 - 1018710188 - 2885128852 - 5460054603 - 219270

Roads and trailsForest boundary

McDonald Forest Visibility Results

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Visibility (number of people)01 - 1018710188 - 2885128852 - 5460054603 - 219270

Forest boundary

Number of users27 - 271278 - 926951 - 29442973 - 21620

Peavy Visibility Results

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Role of GIS- Visibility Analysis

Processed visibility algorithmManipulated data inputsNo need for other softwareProject nearly impossible without GIS

about 250 road and trail segments ability of GIS to automate processing helped

avoid errors

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Opportunities using spatial toolsScientist

Charting research direction Interpreting and publishing research results

Analyst Working with scientists to understand project goals Statistical analysis Database organization

Technician Conducting spatial processing tasks Preparing output

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Local GIS jobs in Jan./Feb Corvallis, GIS Specialist- GS 9/11 (USFS PNWR)Corvallis, GIS Intern- $10-12/ hr, part time to start

(E&S Environmental Chemistry)Corvallis, Photo Interpreter and GIS specialist-

$12-$16/hr, part time to startSalem, GIS Analyst II- $3,100 to $4,064 month

(City of Salem)Roseburg, GIS Assistant- $12/hr, 34 weeks (Fed.

Agency)

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Professional involvement…

ACSM, ASPRS, AGU, SAF, HydrophilesOSU ASPRS winter term meetings

ArcInfo developments Focus on NT (Windows 2000) rather than

UNIX DOQs (1 m resolution is complete) SSCGIS resurrected for the next biennium

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Your professional developmentFocus your education on a discipline

Geology, hydrology, forestry, biometrics, oceanography, fish & wildlife

Make spatial tools a supporting disciplineBecome familiar with many software packages and

know their uses/limitations S-Plus, SAS Access, DBase, Excel ArcInfo (GRID), ArcView (SA, 3D), MapInfo Imagine, IDRISI

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Your professional developmentFamiliarity with data structures

Vector, raster, TINs, regionsFamiliarity with data sources

DOQs, DRGs, DEMs, DLGs, Imagery, SSCGIS data themes

Scale/resolution of these sources is a defining factor of their utility

Statistics A key for many disciplines

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Data utilityAll data are abstractions of the real worldError sources abound and confound

Collection errors Input errors Date of collection, updates

• USGS 7.5 minute quads are typically over 20 years old

Scale/resolution• Data collection purpose

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Don’t wait for data…Precious time is wasted anticipating data

arrivalData completion/arrival schedules are always

overly optimistic Complete doesn’t mean available 10 m DEMs for Oregon’s westside are

completeConcentrate research efforts on available data

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Your role with spatial toolsCartographerGeographer (M. Jordan and A. Einstein)StatisticianData accumulator / administratorData processorNetwork administratorThe pinnacle: Spatial Scientist

Appreciate, integrate, and delegate the above skills and disciplines into your research efforts

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Future Trends in GISIncreased use and growth in most disciplines

GIS and remote sensing technology have evolved to become the single most significant tools for natural resource research and mgmt.

Data will continue to be produced at finer resolutionThe future appears to be modularWindows NT (Windows 2000) basedPeriod of user dominance will continue

easier to use, easier to get in trouble