an intelligent information system for forest management
DESCRIPTION
An Intelligent Information System for Forest Management. NED/FVS Integration. Credits. USDA Forest Service H. M. Rauscher M. J. Twery, S. Thomasma, P. Knopp University of Georgia J. Wang W. D. Potter D. Nute F. Maier. Presentation Overview. Introduce NED NED Decision Process - PowerPoint PPT PresentationTRANSCRIPT
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
An Intelligent Information System for Forest Management
NED/FVS Integration
![Page 2: An Intelligent Information System for Forest Management](https://reader030.vdocuments.site/reader030/viewer/2022032708/56812dda550346895d932943/html5/thumbnails/2.jpg)
Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
Credits
USDA Forest ServiceH. M. RauscherM. J. Twery, S. Thomasma,
P. Knopp
University of GeorgiaJ. Wang
W. D. PotterD. NuteF. Maier
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
Presentation Overview
• Introduce NED
• NED Decision Process
• NED Software Architecture
• NED/FVS Integration
• Future Directions
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
• NED is
a set of Decision-Support Tools
designed to provide analysis for integrated prescriptions
for managing forests for multiple values
up to a landscape scale.
NED: a set of tools forNatural Resource Decision Support
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
1. Create the goals & measurement criteria
2. Inventory & current condition analysis
3. Design alternative courses of action
4. Forecast the future through simulation
5. Assign values to the measurement criteria
6. Evaluate how well goals have been met
7. If not satisfactory, go back to step 1
The NED Decision Process
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
![Page 7: An Intelligent Information System for Forest Management](https://reader030.vdocuments.site/reader030/viewer/2022032708/56812dda550346895d932943/html5/thumbnails/7.jpg)
Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
1. Create the goals & measurement criteria
2. Inventory & current condition analysis
3. Design alternative courses of action
4. Forecast the future through simulation
5. Assign values to the measurement criteria
6. Evaluate how well goals have been met
7. If not satisfactory, go back to step 1
The NED Decision Process
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7
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29
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20
5
16
33
26
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32
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3025
27
7
7
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28
34
18
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12
Pond
Open
Housesites
Foodplots
Pasture
Xmastrees
Secondary Paved Road
Woods Roads
Stands
Map Legend
0.7 0 0.7 1.4 Miles
N
EW
S
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
Inventory
• Management Unit
• Stands
• Plots
• Overstory Observations
• Understory Observations
• Ground Observations
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
1. Create the goals & measurement criteria
2. Inventory & current condition analysis
3. Design alternative courses of action
4. Forecast the future through simulation
5. Assign values to the measurement criteria
6. Evaluate how well goals have been met
7. If not satisfactory, go back to step 1
The NED Decision Process
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Pond
Pine
Hardwood
Field/Open
Christmas Tree
Housesite
Pasture
Park-Like Hardwood
Large Pine
Pine-Hardwood
Map Legend
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
1. Create the goals & measurement criteria
2. Inventory & current condition analysis
3. Design alternative courses of action
4. Forecast the future through simulation
5. Assign values to the measurement criteria
6. Evaluate how well goals have been met
7. If not satisfactory, go back to step 1
The NED Decision Process
![Page 14: An Intelligent Information System for Forest Management](https://reader030.vdocuments.site/reader030/viewer/2022032708/56812dda550346895d932943/html5/thumbnails/14.jpg)
![Page 15: An Intelligent Information System for Forest Management](https://reader030.vdocuments.site/reader030/viewer/2022032708/56812dda550346895d932943/html5/thumbnails/15.jpg)
Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
1. Create the goals & measurement criteria
2. Inventory & current condition analysis
3. Design alternative courses of action
4. Forecast the future through simulation
5. Assign values to the measurement criteria
6. Evaluate how well goals have been met
7. If not satisfactory, go back to step 1
The NED Decision Process
![Page 16: An Intelligent Information System for Forest Management](https://reader030.vdocuments.site/reader030/viewer/2022032708/56812dda550346895d932943/html5/thumbnails/16.jpg)
Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
![Page 17: An Intelligent Information System for Forest Management](https://reader030.vdocuments.site/reader030/viewer/2022032708/56812dda550346895d932943/html5/thumbnails/17.jpg)
Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
1. Create the goals & measurement criteria
2. Inventory & current condition analysis
3. Design alternative courses of action
4. Forecast the future through simulation
5. Assign values to the measurement criteria
6. Evaluate how well goals have been met
7. If not satisfactory, go back to step 1
The NED Decision Process
![Page 18: An Intelligent Information System for Forest Management](https://reader030.vdocuments.site/reader030/viewer/2022032708/56812dda550346895d932943/html5/thumbnails/18.jpg)
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
1. Create the goals & measurement criteria
2. Inventory & current condition analysis
3. Design alternative courses of action
4. Forecast the future through simulation
5. Assign values to the measurement criteria
6. Evaluate how well goals have been met
7. If not satisfactory, go back to step 1
The NED Decision Process
![Page 22: An Intelligent Information System for Forest Management](https://reader030.vdocuments.site/reader030/viewer/2022032708/56812dda550346895d932943/html5/thumbnails/22.jpg)
Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
NED Software Architecture
Intelligent Information System for decision support, featuring the unification of:
• Knowledge Base• Database• Model Base
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
NED Software Architecture
• Blackboard System
• Semi-Autonomous Prolog Agents
• MS Access Data Storage
• Graphical Interface in C++
• Distributed Processing Capabilities (DCOM)
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Blackboard
PrologClauses
MS AccessDatabases
AGENTS
Inference EnginesKnowledge Models
Meta-knowledge
Temporary Data Files
Simulators
GIS
Visual Models
HTML Report
s
Interface Modules Control Flow
Information Flow
NED Software Architecture
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
NED/FVS Integration
FVS:
• One of the Model components in NED
• Controlled by Intelligent Agent
• Simulates User’s Treatment Plan
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
NED/FVS Integration
FVS Agent uses metadata to:
• Pick or recommend FVS variant (NE/SN)
• Create keyword and stand files from NED (MS Access) data
• Run FVS (locally or remotely)
• Convert FVS results to NED format
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FVS AGENT
Blackboard
FVS
Control Flow
Information Flow
NED/FVS Integration
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Plan Screen Shot
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Treatment Screen Shot
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
NED/FVS Integration
The Payoff:
• Transparent use of FVS
• Creates keyword file based on NED treatment plan
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
Future Directions
• FVS: One of many simulators used in NED• Coming Soon
– SVS– Silvah – Landscape visualization
• Automatic Data Source Registration• Intelligent Processing of High Level
Queries
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Northeastern Research StationSouthern Research Station
The University of Georgia Artificial Intelligence Center
http://www.fs.fed.us/ne/burlington/ned/
Further Information