Whining from the applications side of the fence
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MODELLING TECHNIQUES FOR MAPPING IN FOREST INVENTORIESGretchen Moisen, Tracey Frescino
US Forest Service, FIA
Whining from the applications side of the fence
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...and not a thoughtto think.
Data, dataeverywhere...
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Outline
1. Need for new info2. Data3. Models 4. Maps and applications5. Now what
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Need for new information:Traditional reports
• Inventory status and trends in forested ecosystems nationwide
1928 McSweeney-McNary Act
1978 Renewable Resources Act
1998 Farm Bill
• Regional estimates of forest area, tree volume, growth and mortality
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Research to develop new products………In addition to estimates of
population totals…….• Make maps! Show how
forest resources are distributed throughout the landscape
• Use those maps: wildlife, fire, harvest….• Automate data retrieval,
visualization, and analysis tools• Build web-based delivery systems• Just do it
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Need for new information:Development of an interdisciplinary system
• Dialogue with users, define problems
• Build data base, prepare data
• Build and test models
• Test products in real applications
• Get it out and get feedback
QUESTIONS
FIELD DATA
DIGITAL DATA
MODELS
EVALUATION
DELIVERY
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Outline
1. Need for new info
2. Data
3. Models
4. Maps and applications
5. Now what?
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DataSix Ecoregions
• Regional diversity• Forested ecoregions• Within state bounds• Sample across all
owners
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Data:Plot-level Response Variables
Continuous:• Basal area• Biomass• Crown cover• Growth• QMD• Stand age• TPA• Volume
Catagorical:
• Forest/nonforest class
• Select forest type
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Data:
Sample plots
UT1 F: 821 NF: 533
UT2 F: 829 NF: 491
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Data: Sample plots MT1 (F: 1277 NF: 294)MT2 (F: 1612 NF: 2108)
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Data:
Sample plots
AZ1 F: 712 NF: 135
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Process:Many RS-based Predictor Variables
• Raw imagery: TM, MODIS, AVHRR
• NLCD 30 m resolution 19 classes, 8 broad groups
• DEMs: elevation, aspect, slope, hillshade, topographic class
• Spatial coordinates• Other: Soils, TEUs, Precip
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Outline
1. Need for new info2. Data3. Models 4. Maps and applications5. Now what?
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• Extract data from each layer at each FIA location
• Build a model for each FIA variable
Example: Tree cover ~ f(Cover-type, Elev, Aspect, Slope)
Models:Establishing relationships with predictors
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………cover type
……….elevaton
……….aspect
……….slope
to predict
……….crown cover
over unsampled areas
Through the final model, use
Models:Predicting over large areas
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ModelsResponse discrete x continuous x interactions
Forest type
Basal area
Biomass
Crown cover
Growth
QMD
Age
TPA
Volume
NLCD
Soils
Elevation
Aspect
Slope
Hillshade
X
Y
X,Y
Elev, Asp, Slope
NLCD(others)
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Models:Simple Benchmarks
• Discrete variables
Yhat=NLCD class• Continuous variables
Yhat=mean(Y) w/i
NLCD classes• SIMPLE..is it enough?
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Numerous model building tools…..
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Kkjiijk
Kjiij
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GAM
MARS
CART
ANN
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Model Test Using Simulated DataCART LM
GAM MARS ANN
X1,…, X10 ~ Unif(0,1)
Y = 2sin(π*X1*X2) +
.4(X3-.5)2 +
.2(X4) + .1(X5)
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Residual Plots: BIOTOT in UT2CARTNLCD
GAM MARS ANN
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Overview of Analyses
Responses Continuous: BIOTOT,
CRCOV, QMDALL,
STAGE
Discrete: F/NF, F1/F2
Predictors NLCD, AVHRR, topography, UTMs
Technique NLCD, GAM, CART,
MARS, ANN
Evaluation
Criteria
Continuous: RMSE, PWI,
RHO, Runtime
Discrete: PCC, Kappa,
Runtime
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Evaluation criteriaModeling Continuous: RMSE, PWI,
RHO, Runtime
Discrete: PCC, Kappa,
Runtime
System Data preparation requirements?
Nest modelling and prediction within a GIS?
User Do the maps help solve real problems?
Can users drive?
Models fuel estimation and EDA as well?
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Outline
1. Need for new info
2. Data
3. Models
4. Maps and applications
5. Now what?
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Building maps:F/NF, BA, CRCOV, VOL, STAGE, QMD
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Fishlake Applications
Build and test large-scale models predicting…- Presense of cavity
nesting birds- Elk calving sites
…using FIA-generated maps of habitat predictor variables
Tom Edwards, Randy Schultz
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Applications:Web Delivery
• JPEG preview• PDF map• Build a map (Generate a map based on user-defined criteria)
Tracey Frescino, Frank Spirek
http://www.fs.fed.us/rm/ogden/index.html ► Techniques Research
Warning: These maps are prototypes under development. They are NOT final products
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Applications: Interactive Display Environment
• Interactive tool for visualize, summarize, and query resource information
Tracey Frescino
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Outline
1. Need for new info
2. Data
3. Models
4. Maps and applications
5. Now what?
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Future Work:Refining Interdisciplinary System
• Continue dialogue
• Refined retrieval system
• New predictor variables
• Streamlined modeling box
• NFS test applications
• Refined web-based delivery
QUESTIONS
FIELD DATA
DIGITAL DATA
MODELS
EVALUATION
DELIVERY
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Future Work:New Applications
• Prediction for new applications: assessment of resources lost to wildfire or I&D, extension to other
wildlife species
• Improved precision on population estimates
• Improved analyses