Difference between revisions of "LEaRNForME"

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{{DSS description, Identification
 
{{DSS description, Identification
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|Acronym=
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|Flag=yellow
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|Name=
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|Acronym=LEaRNForME
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|Contact person=
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|Name=Landslide Erosion and Runoff: Neural Forest Estimation ModEls
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|Contact email=
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|Contact person=Gianfranco Scrinzi
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|Type of the owner organization=
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|Contact email=gianfranco.scrinzi@entecra.it
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|Website=
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|Type of the owner organization=research institution
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|Description=
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|Website=http://www.targetstars.org/ricerca_ex_isafa/riselvitalia43/index_eng.htm
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|References=
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|Description=LEaRNForME is an instrument for the land planning able to recognise the role of the vegetation cover in controlling some hydro geological instability phenomena. This evaluation will give the opportunity to introduce environmental issues into forest planning.
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|Development start year=
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|References=Andrenelli et al., 2007; Scrinzi et al., 2006; Gregori et al., 2007; Scrinzi et al., 2005
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|Development start year=2001
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|Institutional framework=research prototype (R&D project)
 
}}
 
}}
 
{{DSS description, FORSYS problem types classification
 
{{DSS description, FORSYS problem types classification
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|Temporal scale=
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|Temporal scale=long term (strategic), short term (operational)
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|Spatial context=
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|Spatial context=spatial with no neighbourhood interrelations
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|Spatial scale=
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|Spatial scale=forest level, stand level
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|Decision making dimension=
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|Decision making dimension=single decision maker
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|Objectives dimension=
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|Objectives dimension=single objective
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|Goods and services dimension=
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|Goods and services dimension=market wood products, non-market services
 
}}
 
}}
 
{{DSS description, Utilisation scope
 
{{DSS description, Utilisation scope
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|Status=
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|Status=not upgraded/not upgraded recently)
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|User profile=
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|User profile=public land managers (i.e. state-owned
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|Initial deployment effort=
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|Initial deployment effort=<= 1 hour
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|Adaptation effort=
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|Adaptation effort=parametrised by the user
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|Maintenance organization=
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|Maintenance organization=CRA-MPF - Trento - Italy
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|User support organization=
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|User support organization=CRA-MPF - Trento - Italy
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|Support team size=
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|Support team size=4
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|Number of real-life applications=
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|Number of real-life applications=<=10
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|Last utilisation year by users=
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|Last utilisation year by users=2008
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|Typical use case=
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|Typical use case=N/A
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|Number of users=
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|Number of users=<=10
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|Utilisation in education=
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|Utilisation in education=presentation/demo
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|Manual=
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|Manual=Yes
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|Accessibility=
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|Accessibility=open source/public access
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|Deployment cost=
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|Online demo=http://www.targetstars.org/ricerca_ex_isafa/riselvitalia43/index_eng.htm
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|Installation requirements=
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|Deployment cost=0
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|Country=
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|Installation requirements=PC Pentium IV, Arcview 3 + Spatial Analyst
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|Country=Italy
 
}}
 
}}
 
{{DSS description, Functional description
 
{{DSS description, Functional description
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|Species=
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|Species=N/A
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|Silvicultural regime=
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|Silvicultural regime=user defined
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|Forest management goal=
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|Forest management goal=natural hazards
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|Risk evaluation=
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|Risk evaluation=natural hazards
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|Input data requirements=
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|Input data requirements=Biophysical data
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|Modelling dimension=
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|Modelling dimension=Forest indicators
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|Planning scenario=
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|Planning scenario=N/A
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|Parameterised GUI=
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|Parameterised GUI=No
 
}}
 
}}
 
{{DSS description, Models and techniques to support decision making
 
{{DSS description, Models and techniques to support decision making
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|Optimisation algorithm=
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|Optimisation algorithm=N/A
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|MCDM methods=
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|MCDM methods=MultiCriteria Risk Analysis  (MCRA)
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|Knowlegde management methods=
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|Knowlegde management methods=artificial intelligence
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|Forest models=
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|Forest models=growth models
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|Ecological models=
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|Ecological models=N/A
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|Social models=
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|Social models=N/A
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|Data mining=
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|Data mining=artificial neural networks
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|Uncertainty evaluation=
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|Uncertainty evaluation=N/A
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|2D map interface=
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|2D map interface=Yes
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|3D map interface=
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|3D map interface=No
 
}}
 
}}
 
{{DSS description, Support for knowledge management processes
 
{{DSS description, Support for knowledge management processes
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|Tool dissemination=
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|Tool dissemination=N/A
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|Supported KM processes=
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|Supported KM processes=Knowledge Assessment
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|Integrated KM techniques to analyze and apply knowledge=Artificial Intelligence
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|KM tools used during the development of the DSS=Artificial Intelligence
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|Kind of knowlegde and information processed=Explicit Knowledge, Tacit Knowledge
 
}}
 
}}
 
{{DSS description, Support for participatory planning
 
{{DSS description, Support for participatory planning
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|Participatory planning tasks supported=
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|Participatory planning tasks supported=evaluating options
 
}}
 
}}
 
{{DSS description, Development process
 
{{DSS description, Development process
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|Number of forest specialists in the development team=
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|Number of forest specialists in the development team=5
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|Development team size=
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|Development team size=5
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|User access control=
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|User access control=no
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|Team profiles=
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|Team profiles=N/A
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|Software development methods=
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|Software development methods=N/A
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|User-friendliness of GUI=
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|Number of developer months=1
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|Number of developer months=
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|Development cost=0
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|Development cost=
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|Percentage of HR cost=1
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|Percentage of HR cost=
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|Technical documentation=No
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|Technical documentation=
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|Number of users on participating in specification=1
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|Number of users on participating in specification=
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}}
 
}}
 
{{DSS description, IT environment & IT requirements
 
{{DSS description, IT environment & IT requirements
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|Operating system=
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|Operating system=Windows
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|Programming language=
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|Programming language=C++
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|System type=
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|System type=extension (based on standard software), stand-alone GUI
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|Communication architecture=
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|Communication architecture=N/A
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|Database=
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|Database=N/A
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|GIS integration=
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|GIS integration=ESRI
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|Optimisation package=
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|Optimisation package=N/A
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|Application architecture=
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|Application architecture=N/A
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|Format of the input data=
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|Format of the input data=text file, database
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|Format of the output data=
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|Format of the output data=maps, pre-programmed summaries
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|Internal data management=
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|Internal data management=database, temporary files
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|Data validation=
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|Data validation=N/A
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|GUI technology=
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|GUI technology=N/A
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|Scalability=
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|Scalability=No
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|Spatial analysis=
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|Spatial analysis=N/A
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|Related tools=
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|Integration with other systems=N/A
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|Integration with other systems=
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|Computational limitations=N/A
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|Computational limitations=
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}}
 
}}
 
{{DSS description, Commercial information
 
{{DSS description, Commercial information
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|Can be used commercially=
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|Can be used commercially=No
 
}}
 
}}
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[[Category:Not finished articles]]
 
[[Category:Not finished articles]]
 
[[Category:Decision support system]]
 
[[Category:Decision support system]]

Revision as of 16:35, 18 October 2011

Template:DSS description, Identification Template:DSS description, FORSYS problem types classification Template:DSS description, Utilisation scope Template:DSS description, Functional description Template:DSS description, Models and techniques to support decision making Template:DSS description, Support for knowledge management processes Template:DSS description, Support for participatory planning Template:DSS description, Development process Template:DSS description, IT environment & IT requirements Template:DSS description, Commercial information

General System description

System name: Landslide Erosion and Runoff: Neural Forest Estimation ModEls

Acronym: LEaRNForME

Brief overview

LEaRNForME is an instrument for the land planning able to recognise the role of the vegetation cover in controlling some hydro geological instability phenomena. This evaluation will give the opportunity to introduce environmental issues into forest planning.

Scope of the system

The schema of LEaRNForME

A procedure has been conceived and implemented in order to support the forester in classifying each homogeneous land unit for:

  • predisposition to instability phenomena (termed "propensity") such as shallow landslides, water erosion and runoff generation;
  • vegetation cover functionality in contrasting these events.

Both aspects have to be described and modelled by means of distinctive sets of variables; neural network analysis is then applied to a comprehensive set of study cases. The resulting evaluations of predisposition and functionality are combined into four different indexes with descriptive and planning significance:

  • equilibrium level, a rough estimation of the balance between tendency and cover protection;
  • protection value, assessment of the ability of the vegetation in controlling land degradation;
  • constraint level, grade of limitation with respect to timber-oriented management compatible with the assessed protection value;
  • action priority, preliminary screening of land units requiring ameliorative practices.

At present only the models devoted to the protection from shallow landslides and soil water erosion are operating; analogous procedure for runoff generation is in progress. To try the online-models go to this Web page: http://www.isafa.it/scientifica/assestamento/riselvitalia43/modelli_eng.htm/.

System origin

LEaRNForME was developed during 2001-2007 by Gianfranco Scrinzi, David Galvagni and Giacomo Colle in the Forest Monitoring and Management Unit (Unità di ricerca per il Monitoraggio e la Pianificazione forestale) (http://mpf.entecra.it/) of Italian Council for Research in Agriculture (Consiglio per la Ricerca e la Sperimentazione in Agricoltura) (http://sito.entecra.it).

Support for specific issues

LEaRNForME assists the forestry on site where shallow landslide, water erosion and runoff generation are instability phenomena.

Support for specific thematic areas of a problem type

  • Forest planning.
  • Territorial planning.
  • Protection.
  • Prevention.

Capability to support decision making phases

  • Intelligence: the system use a fully automatic, congruent, progressive and recordable procedure.
  • Design: forest planner input data to evaluate propensity and protective functionality of forest.
  • Choice: results give operational and descriptive indexes for sustainable management.
  • Monitor: implemented for test areas.

Related systems

Data and data models

Typical spatial extent of application

The typical spatial extent of application is the forest management plan. There isn’t a base spatial unit for the output, it’s depend on what extension data input refer. But the minimum reasonable unit is the forest plot. Definitely we can say that the typical spatial extent of application is the single property scale.

Forest data input

The forest data input are about vegetation cover and forest management disturbances.

Type of information input from user (via GUI)

The user provides basic input data about the site conditions (lithology, aspect, slope, vegetation cover, erodibility, land use, practices, disturbances, etc.). In the shallow landslides model, the users input data to evaluate propensity to instability phenomena concerning: lithology, strata bedding, aspect, slope, climatic aggressiveness, drained area and seismicity. To evaluate vegetation cover protective functionality, the user input data about category of vegetation types, vegetation types, dominating vegetation cover, cover gaps, secondary vegetation cover, forest management disturbances, other disturbances, forest engineering practices, forest engineering practices. In the soil water erosion model the user input data to evaluate the propensity to instability phenomena concerning erodibility, climatic aggressiveness, heat load index, topographic factor. To evaluate vegetation cover protective functionality, the user input data concerning land use categories, land use, dominating vegetational cover, bushes cover, grasses cover, dead materials cover, agro-forest management disturbances, practices, slope.


Models

The system use Artificial Neural Network (ANN) models.

Forest models

Social models

Decision Support

Definition of management interventions

The shallow landslides form
The soil water erosion form

The intersection of the vegetation functionality and land propensity to an instability phenomenon through complex mathematical functions gives four useful indices for soil conservation purposes. The user has to interpret this following indices.

  • equilibrium level: this index provides a rough estimation of the balance between land tendency to the analysed geomorphologic phenomenon and cover protection. The “balanced” situation corresponds to conditions of almost equivalent levels of Propensity and Functionality; in these cases one can suppose that the protective action of the vegetation cover is adequate to face the onset of the degradation phenomena under examination. When the warrant provided by the vegetation increases the situation may be classified as “quiet”. On the opposite, the increase of Propensity generates a more or less unbalanced situation which may be defined as “uncertain” or “worrying” according to the algebraic difference between the two indexes;
  • protection value: it assesses the ability of the vegetation in controlling land degradation. The protection value is classified into three classes (“high”, “fair” and “negligible”) according to a set of sigmoid functions;
  • constraint level: this index expresses the degree of limitation with respect to timber-oriented management in relation to the assessed protection value. The classes of constraint are three: “none or negligible”, allowing the adoption of even very intensive cultural systems; “intermediate”, in which only cutting and harvesting techniques that assure the integrity of root apparatus and soil should be allowed; “maximum”, where only cares devoted to the enhancement of the protective functionality of the vegetation cover should be permitted (woodlands destined primarily to the environmental protection);
  • action priority: this index assumes some planning importance by representing a preliminary screening of land units requiring ameliorative practices both for increasing the vegetation cover and for runoff control. The conceptual approach is addressed to prevent the degradation phenomena rather then to reclaim compromised situations. The model provides three classes of “action priority” (“high”, “intermediate” and “negligible”).

Typical temporal scale of application

Planning and operational level.

Types of decisions supported

  • Management and sylvicoltural actions.
  • Strategic decisions.
  • Operating control decisions.

Decision-making processes and models

Output

Types of outputs

The outputs of LEaRNForME Web system are qualitative indices. The outputs of LEaRNForME in stand-alone system are maps and table.

Spatial analysis capabilities

LEaRNForME in stand-alone system integrates weighted overlay capabilities using GIS functions.

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

System

System requirements

The Web application runs on multiplatform environment, only an Internet access and a Web browser is required. The stand-alone application requires ArcView 3.x and MS Access.

Architecture and major DSS components

LEaRNForME is both a stand-alone and a Web application. LEaRNForME is a modular system.

Usage

Forest management and planning, educational.

Computational limitations

No limitations for the Web application; in the stand-alone GIS application it depends on hardware and software used.

User interface

The user has to fill the tables for each instability phenomena: in some case he has to select between the proposed values in the pull down menu. It’s not necessary specific computer knowledge for using the system, but geological and forestry comptences is required to choose the appropriate classes for each variable.

Documentation and support

Information about LEaRNForME can be found at the Ri.Selv.Italia project website.

Installation

Installation not needed.


References

Cited references

External resources

  • Andrenelli M.C., Colle G., Galvagni D., Giannetti F., Gregori E., Scrinzi G., Zorn G.– Assessing the protective role of the forest cover against hydrogeological disturbances:a GIS-based tool for forest planning - IUFRO International Conference: "NATURAL HAZARDS AND NATURAL DISTURBANCES IN MOUNTAIN FORESTS" - Trento, ITALY (September 18th-21th, 2007);
  • Gregori E., Andrenelli M. C., Zorn G., 2007 – Soil and hillslope management using scenario analysis and runoff-erosion models: a critical evaluation of current techniques. International Conference in Florence, ITALY (7th-9th May 2007);
  • Andrenelli M. C., Galvagni D., Gregori E., Scrinzi G., Zorn G. Colle G., , 2006 – Propensione all’erosione idrica del suolo: un approccio valutativo in ambiente gis mediante l’utilizzo di reti neurali. - Convegno Nazionale SISS : "Suolo Ambiente Paesaggio", Imola 27-30 giugno 2006;
  • Scrinzi G., Gregori E., Giannetti F., Galvagni D., Zorn G. Colle G., Andrenelli M. C., 2006 – Un modello di valutazione della funzionalità protettiva del bosco per la pianificazione forestale: la componente stabilità dei versanti rispetto ai fenomeni franosi superficiali. Forest@ 3 (1): 98-155;
  • Scrinzi G., Gregori E., Giannetti F., Galvagni D., Zorn G., Colle G., Andrenelli M. C., 2005 - Boschi e fenomeni franosi superficiali: modello per la valutazione dell'azione protettiva. Estimo e Territorio (Ed agricole - il Sole24ore), anno LXVIII - n.12 - dicembre 2005, pp.30-47;
  • Scrinzi G., Gregori E., Giannetti F., Galvagni D., Zorn G. Colle G., Andrenelli M. C., 2005 – Un modello di valutazione della funzionalità protettiva del bosco per la pianificazione forestale: la componente stabilità dei versanti rispetto ai fenomeni franosi superficiali., 66 p.

Every documentation about LEaRNForME and research processes can find in the http://www.targetstars.org/ricerca_ex_isafa/riselvitalia43/index_eng.htm

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