I prodotti definiti da Geoland2 per l'analisi del territorio.
Daniela Iasillo - Planetek Italia srl
--
Parma, 16 novembre 2011. Nell'ambito della XV Conferenza Italiana ASITA si svolge il Workshop "GMES Land products developed in Geoland2: requirements and examples of products for analysis at a European and regional level."
Guarda anche il video
http://www.youtube.com/watch?v=MNeuj5ksZCA
New design approach on rockfall Embankment Thomas Frenez
La costruzione di rilevati paramassi in terra rinforzata sta diventando una soluzione comune per la protezione dal fenomeno della caduta massi. Questo tipo di strutture risulta infatti veloce e semplice da realizzare, e ha un impatto ambientale ridotto grazie al veloce attecchimento della vegetazione dopo la costruzione. Nonostante la semplicità di costruzione, il comportamento dinamico di tali strutture in risposta all’impatto di blocchi in roccia risulta complesso da modellare; nel corso degli anni sono stati proposti ed utilizzati numerosi modelli di calcolo, basati su concetti afferenti la balistica, sul principio dell’urto anelastico o su formulazioni geotecniche di tipo empirico. Alla luce delle richieste della nuova normativa italiana, gli autori si propongono di mostrare un caso di applicazione di un nuovo modello di calcolo (Carotti et al., 2003; di Prisco C. e Vecchiotti M., 2004) alla progettazione di un rilevato paramassi nel Comune di Ala (TN), finanziato dalla Provincia Autonoma di Trento. Lo strumento è in grado di valutare non solo la profondità di penetrazione del blocco all’interno del rilevato, ma anche gli effetti di una possibile attivazione di un meccanismo di rottura più ampio all’interno dello stesso.
Understanding and modeling masting in European tree speciesGiorgio Vacchiano
This document summarizes research on modeling and understanding masting in European tree species. It discusses how masting patterns can be reproduced spatially and temporally using context-dependent data to parameterize models. It also examines integrating masting processes mechanistically by relating it to underlying physiological mechanisms like resource accumulation. Challenges include relating seed production to multiple interacting factors and implementing processes not captured in some models. A resource budget model provides the best existing approach, but complete process-based masting models do not exist yet.
I prodotti definiti da Geoland2 per l'analisi del territorio.
Daniela Iasillo - Planetek Italia srl
--
Parma, 16 novembre 2011. Nell'ambito della XV Conferenza Italiana ASITA si svolge il Workshop "GMES Land products developed in Geoland2: requirements and examples of products for analysis at a European and regional level."
Guarda anche il video
http://www.youtube.com/watch?v=MNeuj5ksZCA
New design approach on rockfall Embankment Thomas Frenez
La costruzione di rilevati paramassi in terra rinforzata sta diventando una soluzione comune per la protezione dal fenomeno della caduta massi. Questo tipo di strutture risulta infatti veloce e semplice da realizzare, e ha un impatto ambientale ridotto grazie al veloce attecchimento della vegetazione dopo la costruzione. Nonostante la semplicità di costruzione, il comportamento dinamico di tali strutture in risposta all’impatto di blocchi in roccia risulta complesso da modellare; nel corso degli anni sono stati proposti ed utilizzati numerosi modelli di calcolo, basati su concetti afferenti la balistica, sul principio dell’urto anelastico o su formulazioni geotecniche di tipo empirico. Alla luce delle richieste della nuova normativa italiana, gli autori si propongono di mostrare un caso di applicazione di un nuovo modello di calcolo (Carotti et al., 2003; di Prisco C. e Vecchiotti M., 2004) alla progettazione di un rilevato paramassi nel Comune di Ala (TN), finanziato dalla Provincia Autonoma di Trento. Lo strumento è in grado di valutare non solo la profondità di penetrazione del blocco all’interno del rilevato, ma anche gli effetti di una possibile attivazione di un meccanismo di rottura più ampio all’interno dello stesso.
Understanding and modeling masting in European tree speciesGiorgio Vacchiano
This document summarizes research on modeling and understanding masting in European tree species. It discusses how masting patterns can be reproduced spatially and temporally using context-dependent data to parameterize models. It also examines integrating masting processes mechanistically by relating it to underlying physiological mechanisms like resource accumulation. Challenges include relating seed production to multiple interacting factors and implementing processes not captured in some models. A resource budget model provides the best existing approach, but complete process-based masting models do not exist yet.
This document discusses prescribed burning programs for forest fire management in Italy. It notes that wildfires burn over 112,000 hectares per year in Italy, and climate change is increasing fire frequency and severity. Prescribed burning is used in Italy for several reasons: to regulate rural fire uses, maintain strategic fuel breaks around periodically large wildfires, reduce wildfire risk by increasing forest and plant resilience, and train fire operators. The document describes how prescribed burning plans are implemented and monitored in different regions of Italy, and their effects on reducing fuels and crown mortality in Mediterranean pine forests.
The document discusses the European bioeconomy and forest biomass. It provides background on the EU's Bioeconomy Strategy and Action Plan. Forests play a key role in Europe's circular bioeconomy, providing renewable resources for 25% of the EU's bioeconomy. Forest-based sectors currently employ over 3 million people in the EU.
The document describes the SILVA forest growth simulation model. It discusses trends in forest management, environmental policy, and information technology that created a need for complex simulation models. SILVA is a single tree-based model that simulates individual tree and stand development over time under different treatments and conditions. The model outputs growth, yield, financial, and ecological indicators to support sustainable forest management planning and decision making. The document provides examples of how SILVA has been used for management plans, testing thinning guidelines, economic evaluations, and climate change studies.
A natural stand of Pinus contorta was clearcut and regenerated. It currently has over 7000 trees per hectare. The objectives are to have full site occupancy of over 35% while maintaining vigor with less than 60% occupancy. Precommercial thinning will be conducted to reduce the stand density to 1600 trees per hectare when average diameter is 19 cm, then another thinning will reduce it further to 800 trees per hectare.
This document discusses modeling fire behavior through interactions between fire weather and fuel profiles of forest stand structures. It then provides statistics on an unmanaged Pinus contorta forest that experienced a stand-replacing fire, including stand age, top height, average diameter at breast height, volume, basal area, trees per hectare, relative density, and crown fire indices that indicate an active crown fire would occur.
This document introduces three tree species found in Yellowstone and northern Utah: lodgepole pine (Pinus contorta var. latifolia), Engelmann spruce (Picea engelmannii), and subalpine fir (Abies lasciocarpa). It provides details on lodgepole pine, noting it is adapted to high severity fires, light demanding, produces serotinous cones, and its fire regime varies by location. Engelmann spruce and subalpine fir are typically associated, are shade bearing, and late successional.
This document provides an introduction to modeling forest dynamics. It discusses different types of forest models including tree stand models that operate over 10-50 years and landscape models that operate over 50-100 years. It also summarizes various approaches to modeling including process-based models, empirical growth models, stand models with and without diameter distributions, individual tree models, gap models, and landscape models. The document concludes by discussing tools for visualization of forest modeling results and the aims of a training course on the Forest Vegetation Simulator (FVS) model.
The document describes a stand visualization system that allows users to model tree stands geometrically as a tree list with user-created or FVS output data. The system displays the tree stand with an overhead, profile, and perspective view and stores input data for each tree including species code, plant ID, status, diameter, height, lean angle, end diameter, crown radius, crown ratio, marking status, and X-Y-Elevation coordinates.
FVS is a tree growth and yield model that uses empirical equations to predict tree growth over time including diameter and height growth, crown changes, and mortality. It represents a variety of forest management actions and outputs stand statistics, measures of competition, species composition, economic values, fuel loads, and carbon accounting. Users input tree inventory data, site characteristics, and management prescriptions and FVS simulates forest growth and updates stand statistics over multiple cycles.
1. The document discusses sustainable forest management and outlines several key models and parameters for forest modeling including carbon stocking, wood yield, data availability, and differences between RPF and FVS-NE.
2. It describes a meeting of the Steering Committee where participants were welcomed and an opening of the meeting was provided.
3. Differences between RPF and FVS-NE are discussed and the document suggests what features participants would like to see added to these models.
This document discusses key concepts for designing effective density management regimes for thinning stands of trees, including:
1) Site index - a measure of site quality based on average dominant tree height that can be used to estimate future stand age.
2) Stand dynamics - the different stages of stand development with varying levels of relative density, competition, and site occupancy.
3) Size-density relationships and relative density - ways to quantify current density and desired future condition (DFC) to inform thinning plans. Relative density compares current stand density to the density at full site occupancy.
This document contains instructions and activities for a forest modeling workshop using the Forest Vegetation Simulator (FVS) and Stand Visualization System (SVS). The activities guide participants through simulations of forest stands using FVS, analysis of the output, and visualization of stand conditions over time using SVS. Participants are asked to compare thinning and no-management scenarios, assess stand growth and yield, and customize views of modeled stands in SVS.
This document discusses prescribed burning programs for forest fire management in Italy. It notes that wildfires burn over 112,000 hectares per year in Italy, and climate change is increasing fire frequency and severity. Prescribed burning is used in Italy for several reasons: to regulate rural fire uses, maintain strategic fuel breaks around periodically large wildfires, reduce wildfire risk by increasing forest and plant resilience, and train fire operators. The document describes how prescribed burning plans are implemented and monitored in different regions of Italy, and their effects on reducing fuels and crown mortality in Mediterranean pine forests.
The document discusses the European bioeconomy and forest biomass. It provides background on the EU's Bioeconomy Strategy and Action Plan. Forests play a key role in Europe's circular bioeconomy, providing renewable resources for 25% of the EU's bioeconomy. Forest-based sectors currently employ over 3 million people in the EU.
The document describes the SILVA forest growth simulation model. It discusses trends in forest management, environmental policy, and information technology that created a need for complex simulation models. SILVA is a single tree-based model that simulates individual tree and stand development over time under different treatments and conditions. The model outputs growth, yield, financial, and ecological indicators to support sustainable forest management planning and decision making. The document provides examples of how SILVA has been used for management plans, testing thinning guidelines, economic evaluations, and climate change studies.
A natural stand of Pinus contorta was clearcut and regenerated. It currently has over 7000 trees per hectare. The objectives are to have full site occupancy of over 35% while maintaining vigor with less than 60% occupancy. Precommercial thinning will be conducted to reduce the stand density to 1600 trees per hectare when average diameter is 19 cm, then another thinning will reduce it further to 800 trees per hectare.
This document discusses modeling fire behavior through interactions between fire weather and fuel profiles of forest stand structures. It then provides statistics on an unmanaged Pinus contorta forest that experienced a stand-replacing fire, including stand age, top height, average diameter at breast height, volume, basal area, trees per hectare, relative density, and crown fire indices that indicate an active crown fire would occur.
This document introduces three tree species found in Yellowstone and northern Utah: lodgepole pine (Pinus contorta var. latifolia), Engelmann spruce (Picea engelmannii), and subalpine fir (Abies lasciocarpa). It provides details on lodgepole pine, noting it is adapted to high severity fires, light demanding, produces serotinous cones, and its fire regime varies by location. Engelmann spruce and subalpine fir are typically associated, are shade bearing, and late successional.
This document provides an introduction to modeling forest dynamics. It discusses different types of forest models including tree stand models that operate over 10-50 years and landscape models that operate over 50-100 years. It also summarizes various approaches to modeling including process-based models, empirical growth models, stand models with and without diameter distributions, individual tree models, gap models, and landscape models. The document concludes by discussing tools for visualization of forest modeling results and the aims of a training course on the Forest Vegetation Simulator (FVS) model.
The document describes a stand visualization system that allows users to model tree stands geometrically as a tree list with user-created or FVS output data. The system displays the tree stand with an overhead, profile, and perspective view and stores input data for each tree including species code, plant ID, status, diameter, height, lean angle, end diameter, crown radius, crown ratio, marking status, and X-Y-Elevation coordinates.
FVS is a tree growth and yield model that uses empirical equations to predict tree growth over time including diameter and height growth, crown changes, and mortality. It represents a variety of forest management actions and outputs stand statistics, measures of competition, species composition, economic values, fuel loads, and carbon accounting. Users input tree inventory data, site characteristics, and management prescriptions and FVS simulates forest growth and updates stand statistics over multiple cycles.
1. The document discusses sustainable forest management and outlines several key models and parameters for forest modeling including carbon stocking, wood yield, data availability, and differences between RPF and FVS-NE.
2. It describes a meeting of the Steering Committee where participants were welcomed and an opening of the meeting was provided.
3. Differences between RPF and FVS-NE are discussed and the document suggests what features participants would like to see added to these models.
This document discusses key concepts for designing effective density management regimes for thinning stands of trees, including:
1) Site index - a measure of site quality based on average dominant tree height that can be used to estimate future stand age.
2) Stand dynamics - the different stages of stand development with varying levels of relative density, competition, and site occupancy.
3) Size-density relationships and relative density - ways to quantify current density and desired future condition (DFC) to inform thinning plans. Relative density compares current stand density to the density at full site occupancy.
This document contains instructions and activities for a forest modeling workshop using the Forest Vegetation Simulator (FVS) and Stand Visualization System (SVS). The activities guide participants through simulations of forest stands using FVS, analysis of the output, and visualization of stand conditions over time using SVS. Participants are asked to compare thinning and no-management scenarios, assess stand growth and yield, and customize views of modeled stands in SVS.
2. Orario Attività docenti
9,00 - 9,30
Apertura giornata con presentazione obiettivi, logistica.
Distribuzione materiale divulgativo e didattico
Raccolta dati partecipanti
Dott.ssa Roberta Berretti
Dott. Davide Ascoli
Dott. Giorgio Vacchiano
9,30 - 11,00
Introduzione ai danni da vento in foresta.
Fattori responsabili e strategie di prevenzione.
Introduzione agli strumenti di supporto all’analisi della
suscettibilità allo schianto dei popolamenti.
Dott. Giorgio Vacchiano
11,00 - 11,15 Pausa caffè
11,15 - 12,30
Utilizzo di diagrammi di gestione della densità come
strumenti di supporto empirici per l’analisi della
suscettibilità allo schianto.
Dott. Giorgio Vacchiano
12,30 - 13,30 Pranzo
13,30 - 17,00
Introduzione all’uso di ForestGALES.
Descrizione dell’interfaccia.
Simulazioni con parametri di default.
Simulazioni con parametri calibrati.
Applicazione ad un caso studio in un comprensorio
forestale piemontese
Dott. Giorgio Vacchiano
2
3. 4- ForestGALES
Realizzato con il contributo congiunto di Unione Europea, Stato Italiano e Regione Piemonte nell’ambito del Programma di Sviluppo Rurale 2014-2020
- Operazione 1.1.1, 1.2.1 e 1.3.1, Azione 2 – Anno 2017-2018
Dott. Giorgio Vacchiano
gvacchiano@gmail.com
3
6. Installazione
• Windows
• 30 Mb liberi
• Lanciare ForestGALES25_SetUp.exe (admin)
• In alternativa, scompattare ForestGALES25_Extract.exe
• Collegamento nel menu avvio
• Disinstallazione da Pannello di Controllo
6
9. Parametri di simulazione I
9
• Species: ‘Norway spruce’
• Soil group: ‘Gleyed mineral soils - B’
• Rooting: ‘Shallow (<80 cm)’
• Current spacing: 2.8 m
• Top height: 20 m
• DBH: 20 cm
• DAMS score: 15
10. Parametri di simulazione II
10
• Species: ‘Norway spruce’
• Soil group: ‘Gleyed mineral soils - B’
• Rooting: ‘Shallow (<80 cm)’
• Current spacing: 2.8 m
• Top height: 22 m
• DBH: 20 cm
• DAMS score: 15
11. Logica di ForestGALES
• Qual è la forza necessaria a schiantare o ribaltare l’albero?
• Per schianto: modello fisico
• Per ribaltamento: dati empirici, talvolta estrapolati
• Qual è la minima velocità del vento in grado di esercitare tale forza
(velocità critica)?
• L’attrito opposto dall’albero al vento è funzione del raggio di chioma
• Qual è la probabilità che si verifichi un vento di velocità pari o
superiore a quella critica?
• Ventosità media (sistema DAMS in Regno Unito)
• Eventi estremi tramite distribuzione di Weibull (c, k)
• Tempo di ritorno medio tra due eventi sufficienti a causare danno
• Wind Damage Risk Status (WDRS): 1 = >100 anni, 6 = <10 anni
• WHC: wind hazard coefficient (vecchio sistema UK)
11
12. 12
1,2 – green; 3,4 – orange; 5,6 – red, as shown in Table 2.
Table 2 Wind damage risk status (WDRS) and associated return periods.
WDRS Return period
1 >100 years
2 100–50 years
3 50–33 years
4 33–20 years
5 20–10 years
6 <10 years
Unlike the Windthrow hazard class (WHC) classes, the risk status of a site
If the risk status for stem breakage is greater than for overturning, then ste
13. 13
• Previsione con misurazioni in campo
• Previsione con tavole alsometriche
• Previsione lungo il turno
Popolamento
singolo
Modalità batch (lista
di popolamenti)
Modalità sperimentale
(criteri definiti dall’utente)
14. Predictions using field measurements
14
The Stand characteristics box (Figure 10) allows you to describe the stand for which you
to calculate the risk of damage.
Figure 10 Stand characteristics box.
Distanza media tra i fusti (0.6-10 m)
Nome del popolamento
Tipo di suolo
Profondità del suolo per le radici
In alternativa: piante/ha
15. Table 1 Soil groups available within ForestGALES, indicating the soil types within each group.
A Freely-draining
mineral soils
B Gleyed mineral
soils
C Peaty mineral soils D Deep peats
Brown earth
(freely-draining)
Ironpan
(freely-draining)
Podzol
(freely-draining)
Calcareous soil
Rankers and
skeletal soils
Littoral soils
Man-made soils
Ironpan (gleyed)
Podzol (gleyed)
Brown earth (gleyed)
Surface-water gley
Ground-water gley
Ironpan (peaty)
Podzol (peaty)
Peaty gley
Juncus (or basin) bogs
Molinia (or flushed
blanket) bogs
Sphagnum (or flat
or raised) bogs
Unflushed blanket bog
Eroded bog
Rooting
This describes the depth of rootable soil in the stand. The options are: 1 Shallow <80 cm and
2 Deep 80 cm.
15
16. 16
Figure 12 Tree characteristics box.
The options that can be selected from the Tree characteristics box are:
Species
The main species in the stand. Options are:
Scots pine
Douglas fir
Corsican pine
Noble fir
Altezza dominante (5-75 m)
Diametro medio (5-50 cm)
Specie
The options that can be selected from the Tree characteristics box are:
Species
The main species in the stand. Options are:
Scots pine
Douglas fir
Corsican pine
Noble fir
Lodgepole pine
Grand fir
European larch
Sitka spruce
Japanese larch
Norway spruce
Hybrid larch
Western hemlock
Pino silvestre
Douglasia
Pino laricio
Abete bianco
Pinus contorta
Abies grandis
Larice
Picea sitchensis
Larix kaempferi
Abete rosso
Larice ibrido
Tsuga heterophylla
Betulla
Faggio
Quercia
• Birch
• Beech
• Oak
17. 17
Figure 13 DAMS box.
Rough guess method
In the DAMS box, select Calculation then click the Apply... button. The calculation box will
appear. Selecting the Rough guess box (Figure 14) will give the opportunity to estimate the
DAMS score. Select the options that best describe the site based on region within GB,
elevation, shelter and aspect. Press Apply to copy the resulting DAMS score to the query form,
or Cancel to close the window without copying the value across. This method is particularly
useful for making general comparisons between sites. An example of this method of obtaining
DAMS is shown on page 37 (Example 5).
Figure 14 Rough guess box.
appear. Selecting the Rough guess box (Figure 14) will give the opportunity to estimate the
DAMS score. Select the options that best describe the site based on region within GB,
elevation, shelter and aspect. Press Apply to copy the resulting DAMS score to the query form,
or Cancel to close the window without copying the value across. This method is particularly
useful for making general comparisons between sites. An example of this method of obtaining
DAMS is shown on page 37 (Example 5).
Figure 14 Rough guess box.
Grid reference method
In the DAMS box, the user can select Grid reference and then enter the grid reference of
the site; the DAMS score, if available, will be displayed. Example 6 (page 37) shows the use of
the grid reference method for obtaining DAMS.
Figure 15 Exact calculation box.
Upwind edge effect box
The Upwind edge effect box (Figure 16) is used to describe whether
edge has been created adjacent to the stand being modelled. Brown
were originally not at the stand edge) are often a place where wind d
Upwind edge effect box
The Upwind edge effect box (Figure 16) is used to describe whether a new
edge has been created adjacent to the stand being modelled. Brown edge
were originally not at the stand edge) are often a place where wind damag
edge has been created then the Brown edge button should be pressed. Th
can then be altered. The default value is 0 m. The effect of a gap increases
until the size equals 10 x mean tree height, after which the effect remains a
An example of changes to the upwind edge is shown on page 34 (Example
Figure 16 Upwind edge effect box.
DAMS (ventosità, 5-32):
da griglia di coordinate o…
Calcolo grezzo del DAMS Calcolo esatto del DAMS
Nei pressi: margine adattato
o di nuova creazione (“brown”)
Larghezza della buca (0-10 H d’albero)
20. 20
Esercizio 1a
Analizzare il rischio utilizzando Predictions using yield models…
Species: ‘Scots pine’
Soil group: ‘A – freely draining mineral soil’
Rooting: ‘Shallow (<80 cm)’
Yield Class: 6
Thinning regime: Intermediate Thinning with no delay
Initial spacing: 1.4 m
Age: 80
DAMS score: 15
Upwind edge effect: Windfirm edge
21. 21
Esercizio 1b
Selezionare Yield class 12 e esaminare Tree Details… per comprendere
il significato del sistema di tariffe usato; Esaminare la variazione nella
velocità critica del vento.
Esaminare la variazione nella velocità critica del vento selezionando
(a parità di altri fattori):
- Initial spacing = 2.4 m
- Thinning regime: No thin (nessun diradamento)
- Brown edge – size of gap 20 m
- DAMS score = 22
- Rooting: deep rooting >80 cm
- Soil: C - peaty mineral soil
23. Tavole alsometriche personalizzate
23
Modello in yldmdlsuserdefinedyieldmodel.xls
Volume per hectare (m3
/ha)
In each case data refer to the main crop after thinning. This is the format of the Forestry
Commission yield models.
Table 3 Layout of a yield model for use in ForestGALES.
Age (years) Top height
(m)
Trees/ha Mean DBH
(cm)
Basal area
(m2
/ha)
Mean tree
volume
(m3
)
Volume
(m3
/ha)
20 7.4 2781 11 26 0.03 71
25 9.2 2300 13 32 0.06 90
30 10.9 1900 15 38 0.10 120
Naming user-defined yield models
The file should be saved as a text file with a file extension of .yld. If ForestGALES is to recognise
the model then it must be named in a specific way. This consists of an 8 character name.
1. The first two characters indicate species; these are shown in Table 4.
Nome del file:
2 caratteri per la specie
2 caratteri per la tariffa (02–30)
2 caratteri per il regime selvicolturale
2 caratteri per la distanza di impianto in dm = (106/ piante per ha)0.5
24. 24
Table 4 Species and thinning codes for naming user-defined yield models.
Species code Species Thinning code Thinning regime
SS Sitka spruce IZ Intermediate thinning no delay
NS Norway spruce IF Intermediate thinning five years delay
SP Scots pine IT Intermediate thinning ten years delay
LP Lodgepole pine LZ line thinning no delay
CP Corsican pine LF line thinning five years delay
EL European larch LT line thinning ten years delay
JL Japanese larch CZ crown thinning
HL Hybrid larch NO non-thinning
DF Douglas fir T1 user-defined thinning regime
GF Grand fir T2 user-defined thinning regime
NF Noble fir T3 user-defined thinning regime
WH Western hemlock
A user-defined model for yield class 18 Sitka spruce for a non-standard thinning regime
planted initially at 2.0 m spacing would therefore be saved as SS18T120.yld.
The file should be saved in the directory yldmdlsXX where XX is the two letter species code
indicated in Table 4.
If a new model is created with an identical name to a model that already exists, then the old
Salvare da Excel come Formatted Text (Space delimited)(*.prn)
con estensione .yld (nome e estensione tra virgolette)
nella sottocartella yldmdlsXX, dove XX è il codice della specie
25. 25
Esercizio 2
Creare una tavola alsometrica personalizzata utilizzando
I dati di Cantiani (2000) per le peccete della Val di Fiemme
(scegliere una delle quattro classi di fertilità disponibili)
Selezionare la tavola creata in Predictions using yield models…
Verificare i dati che compaiono selezionando Tree Details…
NB: le simulazioni si arrestano all’età massima indicata nella tavola.
26. 26
Batch mode
Permette la simulazione simultanea di più popolamenti o particelle.
Ogni particella è simulata indipendentemente dalle altre.
I dati sono letti da una tabella di input e restituiti in un file di output.
La tabella di input è preparata interattivamente o letta da file esterno.
Per creare un file esterno è consigliato:
- Inserire una riga di dati interattivamente
- Salvare la tabella di input risultante
- Modificare il file salvato in Excel (mantenendo formati ed estensione)
Open file… carica la tabella di input esterna
Calculate risks… avvia la simulazione
Save outputs… esporta i risultati come file di testo
27. 27
Table 5 Modes available for multiple stand predictions.
Mode Outputs
Predictions using field
measurements
Return period for overturning, wind damage risk status for
overturning, return period for breakage, wind damage risk
status for breakage.
Predictions using yield models Model used, current top height (m), current DBH (m), current
spacing (m), return period for overturning, wind damage
risk status for overturning, return period for breakage, wind
damage risk status for breakage.
Predictions through time* Model used, age to reach WDRS 1 to 6 for overturning,
age to reach WDRS 1 to 6 for breakage.
* Double clicking on any of the input lines in this mode will open the graphics display window as for a
single stand. In this way it is possible to observe differences between the risk for all the stands entered as
inputs.
Controls box
28. 28
Esercizio 3
Inserire interattivamente i dati di 3 popolamenti utilizzando la
modalità Predictions through time e la tavola alsometrica creata da
Cantiani (2000) per almeno uno dei tre popolamenti.
Avviare la simulazione, interpretare i risultati e esportarli in file di testo.
NB: doppio click su una riga dell’output apre il grafico del tempo di
ritorno del vento dannoso lungo il turno per il popolamento
selezionato.
29. 29
Research mode
Options… Research Mode
1) Modificare i parametri di default (FGParameters.txt nella cartella root)
Options… Restore defaults resetta i parametri ai valori iniziali
# comment lines
§ Snow density (kg/m3) [150]
§ Von Karman constant [0.4]
§ Air density (kg/m3) [1.2226]
§ Acceleration due to gravity (m/s2) [9.81]
§ Number of tree heights from edge assumed to be in forest [9]
§ Size of gap regarded as infinite (in tree heights) [10]
§ Limit defining resolution of Forest GALES model [0.01]
30. 30
§ Element drag coefficient (CR) [0.3]
§ Surface drag coefficient (CS) [0.003]
§ Constant (CW) [2]
§ Roughness [not used]
§ Height above zero plane at which we require wind speed (m) [10]
§ Ua: used in calculation of annual exceedance probability [5]
§ Four parameters used in calculation of Uc for annual exceedance probability
§ Weibull_K [1.85]
§ Code for Weibull_A calculation [1: Entered directly; or 2: Calculated from DAMS]
§ Weibull_A [if code is 1] [6]
§ Two parameters for calculating Weibull_A from DAMS [if code is 2]
A_Weibull = DAMStoWeibull_A1 + DAMStoWeibull_A2 * DAMS
§ Multiplier defining number of sections in each 1m length of trunk [1]
e.g. multiplier = 2 to have 0.5 m sections; multiplier = 0.5 to have 2 m sections
(more sections means more accuracy but slower computation time)
Mode… Batch Weibull:
Per scpeficifare Weibull_A e Weibull_K
diversi per ciascun popolamento
(altrimenti sempre costanti)
Batch-Weibull mode
There is also a new mode: Batch-Weibull mode. When
this mode appears at the top of the ForestGALES wind
Batch-Weibull window.
Figure 26 Batch-Weibull mode icon.
This mode uses field measurements (see the sections st
User manual and Table 7), but Weibull_A and Weibull_
stand in the Weibull Box (Figure 27).
Figure 27 Weibull box.
31. Weibull_A e Weibull_K
• Analisi statistica dati di vento orari o triorari
• Per il calcolo di K le calme non si conteggiano
• Atlante eolico regionale (es. Trentino)
• A = 1.13 * (velocità media)
• Vm da atlante eolico nazionale 1x1 km, vento a 25 m
• K = 1.45 medio per l’Italia
31
34. 34
2) Modificare i parametri delle specie (cartella SpeciesParamFiles nella
cartella root, nome del file XXParameters.txt, con XX = codice della specie)
U1-U6 disponibili per specie personalizzate
§ Multiplier and intercept for linear conversion from Top height (m) to Mean height (m):
MeanHt = Multiplier*TopHt + intercept [1.0467, -2.1452]
§ Parameters to calculate crown width (m) as function of DBH (cm), and code for form of equation
Linear (code =1): Param1*DBH*100 + Param2 [set param3 = 0] [0.1346, 0.6418]
Power (code =2): Param1*DBH^Param2 + Param3
§ Parameters to calculate crown length (m) as function of H (m), and code for form of equation
Linear (code =1): Param1*Height + Param2 [0.3667, 2.4682]
Exponential (code =2): Param1*exp(Param2*height)
§ Stem density (kg/m3) [850]
§ Canopy density (kg/m3) [2.5]
§ Modulus of rupture [3.4E7]
§ Knot factor [1]
§ Modulus of elasticity [5.9E9]
§ Streamlining parameters C, N
§ Root bending term: RootBendK
35. Esercizio 4
• Effettuare una simulazione personalizzata del rischio da
schianto da vento (Single stand, prediction through
time) con i seguenti parametri:
• Specie U1
• Parametri modello di ampiezza di chioma: [0.11, 0.6]
• Tavola alsometrica di Cantiani per l’abete rosso a Paneveggio
• Weibull_K = 1.45
• Weibull_A calcolato da velocità media del vento a 25 m per
Courmayeur
35
