1. The document describes a multi-agent simulation model developed to explore the future of vineyard landscapes in the Bandol wine-growing region of France. 2. The model simulates interactions between wine growers, urban development, and land use changes over time under different scenarios. 3. The model can provide insights into how key social, economic, and policy variables might impact the spatial patterns of vineyards and urbanization over 40 years. However, it has limitations and is not intended as a predictive tool.

1. Input 2012 Special Session: Spatial Strategic Foresight
Cagliari, May 12th2012
Prospecting the Evolution of a Suburban Wine-
growing Region through Multi-Agent Systems
Matteo CAGLIONI1, Giovanni FUSCO1, Paul MINVIELLE2, Diego MORENO1
1 UMR 7300 ESPACE, Université de Nice Sophia Antipolis
2 UMR 7303 TELEMME, Aix-Marseille-Université

2. Content Overview
1. Introduction
2. Methodology
3. Geosimulation
4. Conclusion

3. 1 The Bandol wine-growing region
N
Le Castellet
N La Cadière Le Beausset
d’Azur
0 5km
Evenos
St Cyr s/mer
Bandol Sanary
A wine-growing region between
Ollioules
Marseilles and Toulon 0 2 km
1941: Obtention of the AOC Label
Bandol AOC perimeter
AOC perimeter: 1570 ha planted in 2000 (RGA).

4. 1 The socio-economic context
• The wine-producing world : wine-growers / wine-
makers, the Bandol Association (ODG), the INAO
• The urban world : land developers, households,
municipal governments, metropolitan government
• Growing concern from ODG and INAO on the
consequences of municipal/metropolitan governments
plans on the future of wine-growing
social demand for a prospective research on
wine-growing landscape in the Bandol region

5. 1 Exploring the future of vineyard landscapes
• A research action within the PATERMED project (ANR
Systerra): exploring the future of vineyard landscapes in
the Bandol region – on going partnership with INAO and
ODG Bandol
• Urban / Rural interaction: urban pressure on agricultural
land + financial input from urban development into
winegrowing
• Importance of agent strategies and interactions resulting
in (and being shaped by) spatial structures

6. 2 Modelling urban / rural interaction
• Modeling choices : MAS approach + Sensitivity Analysis
for scenario building
• Which elements and process are to be included in the
model? What implementation within a MAS approach?
• What outputs are relevant in a spatially informed
strategic foresight?
1) Model development and
Two-phase modelling process:
exploration for a small virtual world
2) Model implementation and
validation with real-world data

7. 2 Input - Output Model Structure
future cadastral map
cadastral map
NetLogo
land use future land use
MODEL
exogenous
variables: Land use plan
-housing demand
-urban land price
-price of wine
-interest rate
- future wine growers’
structure
Synthetic Indicators:
- Wine-growing economy
- Landscape Ecology
wine growers’ structure -

8. 2 Semantic categories of space
Land use Land use plan Space under
urban pressure
URBAN EXISTING
- Consolidated city URBANISATION Pixels and
- Road network parcels
- Subdivisions NEW neighbouring
- Individual housing URBANISATION urban land
POSSIBLE uses
AGRICULTURAL
- Vineyards NEW
- Rural wasteland URBANISATION
- Other agriculture FORBIDDEN but
not for everyone
NATURAL
WATER BODIES

9. 2 Spatial structure of the agents
Agents Agents
wine parcels patches
parcel cells (landscape
grower
[list of cells] 25m x 25m ecology
[list of parcels] units)

10. Wine-grower agents:
2
lifecycle and social relationships
age capital
At the end of the active life (65years), how many children want to take over parent’s activity?
0 1 2+
Sell property or Property Property
Sharecropping transmission division

11. 2 Different contexts for land sale
1. 2. 3.
From winegrowers at the From winegrowers without From winegrowers
end of their career without residual financial capital and with parcel(s) under
children who want to take negative revenues urban pressure and
over the activity urbanizable
The winegrower agent sell (all) their The winegrower agent sells one
parcels and exits the system or more parcels and can buy
(eventually sharecropping agreement) other parcels further away
To other winegrower(s) To real estate promoters

12. 2 Winegrower’s economic function
independent independent independent
cooperative cooperative cooperative
∆Cumulated
capital = α S - t K - f ( S , dc ) - f ( c )
Bandol produce capital cost logistic costs fix costs
(including cost of living)
K capital
S surface [ha]
dc distance from the logistic center
α value of net winegrowing produce per ha
t interest rate

13. 2 Flow diagrams of processes in the model
Process of parcel purchase Process of parcel sale
Process of property transmission
Process of land development through subdivision Process of land development through individual housing

14. 3 A small wine-growing region
Land-
Land-Use Land-Ownership
Land-

15. 3 Trend Scenario after 20 years

16. 3 Trend Scenario after 40 years

17. 3 Increased subdivision development after 40 years

18. Increased individual housing development
3 after 40 years

19. 3 Lower Bandol wine price, after 40 years

20. 4 Conclusion: what the model can do
• Dialectics between agent micro-behaviours and
emergence of meso- and macro- spatial structures
• Role of basic social and economical interaction within
vineyards development
• Role of land ownership structure and demographic
variables within vineyards and urban development
• Impacts of urban pressure, land-use plans and
exogenous economic variables on vineyards landscapes

21. 4 Conclusion: what the model cannot do
• Land-use plans and urban dynamics are exogenous
• Very limited modeling of interaction with different
agricultural activities
• Topological / accessibility properties of road networks are
not modeled
• Landscape modeling is limited to land-use quantification
(no qualitative aspects like perceptions, heritage
conservation, nor 3D rendering of landscapes)

22. Conclusion: the role of a MAS model in
4
Spatial Strategic Foresight
• Not a prediction model, but a tool to explore the possible
futures of the landscape under coherent sets of
hypotheses
• Integration of socio-economic and spatial processes,
beyond the black box of CA modeling
• But : danger of over-complexifying process modeling
• A precious tool to understand the role of key variables
and policies in a spatially informed strategic foresight
next step: scenario building
For the model as well as for the strategic foresight approach,
validation will come from real-world application.

23. Thank you for your attention
matteo.caglioni@unice.fr
giovanni.fusco@unice.fr

24. Weak urban pressure, after 40 years

25. Higher Bandol wine price, after 40 years

26. Lower urban land price, after 40 years

27. Higher urban land price, after 40 years

28. Lower children take over probability, after 40 years