Geospatially enabled information Geospatially enabled information systems supporting forest decisions at systems supporting forest decisions at
the Millennium: a U.S. perspectivethe Millennium: a U.S. perspective
by Jeremy S. Fried
USDA Forest Service, Pacific Northwest Research Station
Forest Inventory and Analysis Program
Given 19 May 2000 at Hyytiälä Field Station, Finland
IntroductionIntroduction
My TaskMy Task Current
– No refereed literature; limited gray literature
Status– Relative to whose expectations?
Forest– Include natural resource, chaparral, non-commercial forest?
Information Systems– Only storage/retrieval/display or also models and analysis?– Spatial, quasi-spatial, aspatial?
Expert Opinion SurveyExpert Opinion Survey
20 key informant interviews
Experienced FIS practitioners who
– specify, design, implement and use spatially referenced
information systems intended to support decisions about the
management of forests in the U.S
Snowball sampling
QuestionsQuestions
What does the term “practical forestry information system” mean to you?
Please describe an example from within your organization. – What objectives does that system have? – How does it account for location? – What analysis functions are included (if any) and how are they
implemented? – What inputs are required? – Who are the intended users?
More QuestionsMore Questions
– What has been the biggest barrier to its adoption? To its
effectiveness?
– What do you see as the greatest accomplishment of the system?
How has it changed your organization?
– Did you consider another system before adopting this one?
How did you choose?
– Are you marketing your system to others? If so, which systems
do you see as competitors to yours?
CaveatsCaveats
Inherently biased towards reports of success
Constraints of corporate confidentiality
– Scarce documentation of corporate systems
– Even scarcer reporting in peer-reviewed outlets
Synthesis reflects my interpretations & not necessarily
the USDA Forest Service
Organization of FindingsOrganization of Findings Status of public sector FIS Status of private sector FIS Issues transcending organizational type Examples of interesting FIS cases Barriers to success Accomplishments of FIS Traps to avoid Nuggets of wisdom Discernable trends
U.S. ForestsU.S. Forests
Bureau of Land Management (BLM)Bureau of Land Management (BLM)
Responsibility on 25% of the U.S. land area
Substantial forest lands in the Pacific Northwest
Spatial data involved in 75% of information flow
Government Accounting Office (GAO) ReportsGovernment Accounting Office (GAO) Reports
ALMRSALMRS
Automated Land and Mineral Records System
– Abandoned after 15 years of development and
411 million USD expended
– Lessons learned: lack of management controls and systems
architecture were fatal
Locally in PNW, independently developed FIS are being
used for mapping and to support decisions
ALMRS debacle slowed FIS at NPS and BIA
#
U.S. National Forests
NNational Forests
U.S.
Portland
Legacy FISLegacy FIS
300 forest level FIS constructed over 25 years
– Diverse Purposes
Thematic content
Coding and classification systems
Adequacy of documentation and accuracy standards
– No embedded business rules
– Analysis rarely emphasized
– National system stymied by information infrastructure
Project 615Project 615
Client/server office automation for the USFS– Hardware/software acquisition
– Implementation
– Training
– GIS but one component
Seven year process– Massive, complex, lawsuits by losing bidders
Equipment began arriving in 1995– Vision for agency-wide FIS architecture followed
DatabasesDatabases
Existing vegetation Soil/ecology/geology/geomorphology/climate Aquatic features Fauna Human dimension Constructed/developed features Location information regarding ownership
Current StatusCurrent Status
Local/regional: Zone area province approach– Some success in use of FIS to support
Operational management Planning Outreach
– Continued emphasis on automated mapping and producing maps and data for the public
Ongoing communication among national and regional experts to shape NRIS– Took 3 years to agree on 15 core GIS layers
State FIS ProgressState FIS Progress
50 states with varied missions
– Regulation
– Technical advice and landowner assistance
– Active management of public forests
Thus, different objectives and needs
Washington farther along than most states
Forest IndustryForest Industry
Representing vegetationRepresenting vegetation
Homogeneous stands over time unrealistic
Stands as management and sampling unit
Homogeneity varies by region
Habitat type “stands” supplemented by successional
trajectories
Stands dynamically generated from plot data
Stands/activities as spatial events (in time/space)
Spatial Event ExampleSpatial Event Example
Stand event
Blow-down 1999
Budworm 1998
Clearcut 2000
Legend
A
B
D
C
Spatial-temporal GISSpatial-temporal GIS
Spatial Event SystemSpatial Event System
Offers flexibility to view land from different perspectives
Use of “region” model reduces redundancy
Append instead of replace means information never lost
Business rules and knowledgebase reduce entry/update
time and errors
Role of modelsRole of models
Models planned at design stage– Ensures inclusion of required data– Provides focus for the FIS effort
Most include or link to FORPLAN or other optimizers and schedulers
Several have extensive habitat analysis components
Lessons from Corporate FISLessons from Corporate FIS
Benefits just now beginning, after 15 yearsHigh success depends on
– Genuine and sustained commitment to Full deployment of FIS Using FIS as a basis for decisions
– Visionary leaders or– Visionary technical analyst/catalyst with access to
leadership
Transcendent IssuesTranscendent Issues
Top down or bottom up?Top down or bottom up?
100% bottom up incompatible systems; can’t aggregate to a corporate view
100% top down guarantees consistent systems that receive no local buy-in or local usefulness, and thus usually poor quality data
Mixed approach ?– Energetic/decisive leadership: potential for timely system that
meets many needs– Consensus/committee leadership: painfully slow progress, and
ultimately ?
Evolutionary FIS?Evolutionary FIS?
Most organizations attracted to FIS by desire to automate
map applications
Widely held hope that if you build the database for
mapping, analysis will follow
– This has rarely occurred
– Those who most successfully integrate FIS with their core
business have not followed this path
1 db, 2 db, 3 db, 4…and more1 db, 2 db, 3 db, 4…and more
Tendency to manage FIS components separately, e.g.,
roads/infrastructure, land records, natural resources
– Departmental desire for autonomy?
– Rarely makes using the FIS easier
Critical need: ensuring common database to support
operations and strategic planning
Data qualityData quality
Lineage of pre-existing or legacy data Accuracy specifications often linked to map purposes,
not analytic purposes Analytic limitations due to inadequate accuracy
sometimes not known until analysis (e.g., overlay) propagates errors
Plenty of re-doing in FIS; contributes to time and cost overruns
Melding FIS to the core businessMelding FIS to the core business
Top Priority: analyzing the business process to identify FIS needs
Top Priority: assembling a high quality databaseConflicting view on ordering these priorities
– Build database first, think about analysis later?– Create schematics for analysis, then build database?
Above all, avoid FIS for FIS sake
SoftwareSoftware
No longer matters ESRI products dominate U.S. FIS Oracle database dominates ArcView widely deployed as “front end” Customized A/I and AV interfaces common Custom-built GIS all but extinct Custom-built FIS rarely resold Lots of “general case” decision support tools but few
with broad distribution
Reasons for CooperationReasons for Cooperation
Mixed ownership– Roads– Fire protection
Landscape level processes – Habitat– Hydrologic impacts– Insects and disease infestations
Reduce typical lag of 5-10 years between concept and implementation through partnering
Forms of CooperationForms of Cooperation
Sharing FIS data and costs Interagency vegetation mapping project
– Support Northwest Forest Plan (owls) Mixed grain FIS
– Fine grain on own lands– Coarse grain (RS generated) on others lands
Integrated taxonomic information system (on web) National Biological Information Infrastructure
– Built on FGDC standards User boards/geospatial advisory committees
Data, data, everywhere…Data, data, everywhere…
Almost all federally collected data is free
– Orthophotos
– DEMs
– Digital line graphs
(roads, contours, hydrology on base map)
– Land use/cover
– TIGER (address coded roads and census)
Helps jump start FIS efforts at many organizations
Example 1: National FISExample 1: National FIS
National FISNational FIS Resource Planning Act (RPA) Assessments
– Multi-resource– Status, change and forecasts– Constructed from a national FIS (FIA) and other data
FIA component has– Over 50,000 spatially referenced inventory plots– A nationally standardized plot design– Numerous, precisely measure tree attributes– Plot confidentiality restrictions which make attribute data
unrestricted and location secret to all outside FIA
RPA outputsRPA outputs
Aggregate reporting of status and change for all resources by county, state, region
Projections over time Current and predicted indicators of ecosystem health
– Endangered plants– Endangered animals– Stream flow– Sediment– Habitat structure
What else is FIA FIS good for?What else is FIA FIS good for? Monitoring coarse grain disturbances Numerous aspatial and spatial relationships
– Harvest, owner type, timber price– Forest health, climate event, insect activity– Development, forest attributes, owner type, site– Habitat abundance and distribution
Criteria and indicators computation Carbon flux Invasive exotics “Wall-to-wall” estimates of forest attributes Detailed species maps
Example 2: Collaborative FISExample 2: Collaborative FIS
ARGIS: a participatory FISARGIS: a participatory FIS
Collaborative approach with
– Networked laptops
– Electronic meeting architecture
– Built-in decision support system
– Structured public feedback
Features of Participatory FIS– Query
– Entry
– Annotation
– Relational links
– Simultaneous or anonymous input
– Geographic exploration
– Prioritization
– Database linkage to spatial changes
– Geographic negotiation
– Automation of summary displays for group review and meeting documentation
Example 3: Integrated Example 3: Integrated FIS/Planning SystemsFIS/Planning Systems
EP(x): Ecosystem Planning ExpressEP(x): Ecosystem Planning Express
Began as UC Berkeley research effort under the North Coast pilot and Sierra pilot projects
Morphed to Terra Vision planning system in collaboration with Louisiana Pacific Co. and VESTRA Resources
Evolved to EP(x) and used for sustained yield plans and habitat conservation plans for Louisiana Pacific Co. and Pacific Lumber
Spatiallized FORPLANSpatiallized FORPLAN
EP(x) is a departure from FORPLAN– bigger variety and number of prescriptions
– outputs include ecosystem state variables
– detailed tracking of spatial distribution of ecosystem attributes
– interpretation of ecosystem from perspective of vertebrate wildlife
Based on wildlife habitat relations (WHR)
BarriersBarriers
Takes one year per application for users to come up to speed on the new way of doing things
Hardware and software remain obstacles, especially in agencies (disk storage, software)
Long time and high costs before results are produced can lead to softening of support
Institutional– firewalls, inflexible contracts, strict rules for national consistency
FIS’s Greatest AccomplishmentsFIS’s Greatest Accomplishments
FIS seen as important part of everyone's job
More communication among staff across disciplines and
with public
More thinking from non-traditional perspectives
Users who edit/update feel pride of ownership
Rapid (6 week) FIS update from inventory makes
information current and highly relevant
TrapsTraps
Buying bargain priced FIS technology without projecting
needs and data budget
Individuals driven by personal agendas hijacking the FIS
Reinventing the wheel by forgoing technology because
“not invented here”
AdviceAdvice
Spend time & money early on business analysis and system planning to ensure that system will – Solve real problems – Contain highly accurate spatial and inventory data
Expect data entry/correction to absorb 75% of time Use small extent pilot with full database & analytic functions Plan to update dynamic themes Don’t be afraid to bring in people with skills you need
TrendsTrends
More progress in last 5 years than previous 10
Analysis time frames lengthening
Grain of analysis becoming more fine
More acceptance of remote sensing
Production of wall-to-wall forest coverages
Use of FIS to track activity in development zones
Fuzzing of traditional administrative boundaries
ConclusionsConclusions
Whither Analysis?Whither Analysis?
FIS is more than a data sponge/filing cabinet, but– Biggest use of FIS is still map production
Duerr’s 1979 vintage concept of FIS includes problem ID and prediction capability– Not everyone “get’s it”
System origins limit analytic destiny FIS with strong inventory foundations best positioned to
support analysis
Complex, information rich problems usually
result in simplistic solutions; the more
knowledge we have, the more difficult (not
easier) decisions become.
The Information Fallacy
The Role of FISThe Role of FIS FIS only useful if you
– treat FIS as strategic business resource and– use the information generated to guide management
FIS has no value if decisions are political Some regard federal agencies as reactive and political, so
if– Pre-conceived notion of best outcome, or– Concern that information will lead to lawsuit,– Then increased information reduces manager’s discretion
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