FFIREDESSYS

From forestDSS
Revision as of 20:02, 11 September 2009 by Francisco Girón Gesteira (Talk | contribs)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

General System description

System name:

Acronym: FFIREDESSYS

Brief overview

FFIREDESSYS is a decision support system that estimates the structural forest fire risk on a global scale, introducing the use of fuzzy sets and fuzzy algebra concepts.[[Category:]]

Scope of the system

The purpose of the FFIREDESSYS is to be used as a pilot system and to lead the way for further fuzzy systems development in the near future. This is the first DSS which use fuzzy algebra in this domain and from this point of view the FFIREDESSYS is globally unique.

System origin

  • Developed by L.S. Iliadis in 2003.
  • how was it developed
  • is it a commercial product
  • does it have real-life application cases

Support for specific issues

Is the system designed to take into account specific uses? E.g. guidance on ways to characterize biodiversity, economic-biodiversity tradeoff analysis methods, risk assessment methods, landscape analysis methods, timber harvest effects, climate change effects, biological effects (pests, pathogens, invasives), fire,...

Support for specific thematic areas of a problem type

  • Silvicultural
  • Certification
  • Conservation
  • Restoration
  • Transportation
  • Development choices / land use zoning
  • Policy/intervention alternatives
  • Sustainability impact assessment (SIA)
Structure of the IFFIRES integrated system

Capability to support decision making phases

(NOTE I do not quite know what to do with this, as I do not understand it myself, although it seems related to system use)

(Click here to see a more detailed explanation)

  • Intelligence (+ explicit description of the support given by the DSS)
  • Design (+ explicit description of the support given by the DSS)
  • Choice (+ explicit description of the support given by the DSS)
  • Monitor (+ explicit description of the support given by the DSS)

Related systems

Data and data models

Typical spatial extent of application

Define the scale of use for the application (user defined, regional, multi-owner forest single ownership forest, Multiple scale interaction)

Forest data input

Describe the basic forest input (forest level, stand level, or individual tree level), and appropriate meta-data, such as data provenance (Areal coverage, Sample of plots, stands, Contiguous forest cover). GIS information is to be considered here, namely include cover tyes and type of information (raster or vectorial, necessity of topological information) If necessary describe surrogate sources of information

If necessary describe other types of required data (economic, social)

Type of information input from user (via GUI)

Describe what is the information that the user directly inputs in the system if any): expert knowledge, opinion, goals and production objectives, preferences, stand/site information....

Models

Forest models

Growth, Yield, Carbon, Wood quality, biodiversity and habitat suitability, environmental and external effects (fire, storms, pests, diseases, climate change, etc)

Social models

historical and cultural values of sites, values due to peace and quiet, esthetic values, values due to recreational activities, ethical values): E. g. Recreation, Health, Game


Decision Support

Definition of management interventions

Define what is available for the manager to intervene in the forest: time of harvest, plantations, thinnings, reconversions... Existence of prescription writer, simple enumeration of all possibilities, scenario simulation , etc.

Typical temporal scale of application

Define the temporal scale of the application: E.g., operational and immediate level, Tactical planning (short term) and strategic level.

Types of decisions supported

  • Management level
    • strategic decisions
    • administrative decisions
    • operating control decisions
  • Management function
  • planning decisions
    • organizing decisions
    • command decisions
    • control decisions
    • coordination decisions
  • decision making situation
    • unilateral
    • collegial
    • Bargaining / participative decision making

Decision-making processes and models

  • Logic modeling
  • Operations research modeling
    • Direct approaches
    • Heuristic manipulation of simulation models
  • Business modeling
  • Simulation (with and without stochasticity)
  • Multiple criteria/ranking
  • Other

Output

Types of outputs

Types of outputs produced (tables, maps, 3-D visualizations, pre-programmed summaries, etc)

Spatial analysis capabilities

  • integrated capabilities
  • facilitates links to GIS (wizards, etc.)
  • provides standard data import/export formats
  • allows spatial analysis (e.g. topology overlays (e.g. multi layering of different maps, selection of objects based on selection criteria, aggregation by attributes (e.g. areas of similar characteristics), Linking by logical means, Statistics by area, analysis with digital terrain model)

Abilities to address interdisciplinary, multi-scaled, and political issues

Evaluate interactions between different basic information types (biophysical, economic, social). Produce coordinated results for decision makers operating at different spatial scales facilitate social negotiation and learning

System

System requirements

  • Operating Systems: The DSS runs on any type of Pentium PC that uses Windows 98, Windows 2000, Windows XP and Windows NT. The system is not portable only to Unix machines.
  • Other software needed (GIS, MIP packages, etc...)
  • Development status: an initial version was developed (2004)

Architecture and major DSS components

Developed using MS Visual Basic. LEORUN is the environment for the execution of the LEONARDO packed Knowledge Bases. It is an auto run system that has been developed in the laboratory of Forest Informatics of Democritus University of Thrace, Greece.

Usage

Describe the level of use: Research level use, Industry use, Government use

Computational limitations

It does not have any special memory requirements.

User interface

It has a friendly user interface that uses menus, screens and pop-up menus. The choices are done by the use of keyboard buttons.

Documentation and support

Describe the connection to Help-system and possibilities for assistance, as well as the required training and user support levels

Installation

  • Prerequisite knowledge: Level of effort to become functional
  • Cost: (purchase price, development costs, demonstrated return on investment, cost of use, training costs, licence and maintenance costs)
  • Demo: allows the download/utilization of a trial version. If yes, where is it available and what are the trial conditions.

References

Cited references


External resources

ILIADIS L.S. (2005): A decision support system applying an integrated fuzzy model for long-term forest fire risk estimation. Environmental Modelling & Software, 20, 613-621.