A case study of Jakarta Metropolitan Area, Indonesia

Modelling the spatial decisions of private developers:

Agung Wahyudi, Yan Liu, Jonathan Corcoran

School of Geography, Planning and Environmental Management (GPEM)The University of Queensland

AUSTRALIA

Agung Wahyudi S42817150

Why model the residential developer behaviour?

• Urban models aim to provide:• a better understanding of the mechanisms underpinning

urban system and;• Simulate the impact of a spatial policies on urban form

• There has been various urban models used to simulate urban growth and urban form.

• Models accounting for residential developers behaviour are largely missing from these models.• In particular, the representation of profit-driven

developers on searching for the most profitable areas, and the impact of this behaviour on land cover and land value.

Agung Wahyudi S42817150

The spatial context of this study

• Covers 6800 km2,

• Population: 28 million people (~10% of Indonesian). MEGAcity

• Jakarta (the capital of Indonesia) as the economic core.

Agung Wahyudi S42817150

Factors impacting developer decisions

• Developers consider • multi-dimension factors,

• various actors, as well as• details on the factor intrinsic to the site.

• In the model, we selected few factors to localize and to focus the impact of these factors on urban form.

• In the model, factors intrinsic to the site :

• Proximity of the targeted area from the city centre (CBD),• Proximity to the (toll) roads, and• Land value.

• Factors intrinsic to the developer : • Access to capital affects the decision (incl loan),

• Number of developers in the area.

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Conceptual framework – potential profit hypothetical curve

• Blue line: Raw land price before installment of infrastructure varies according to the distance from city centre

• Red line: Road construction improves site accessibility

• Green line: Added value increase equally as much as 30-∼100% of cost

• Purple line: Selling price 30%

• Monocentric assumption still applicable in JMASource: adapted from Winarso 2000

Land

val

ue

Agung Wahyudi S42817150

Method #1: The modules in agent-based urban growth model

Urban-agent-based MODEL

Module A:Spatial

dimension

Module B:Agents’

behaviours

a. Static layer b. Dynamic layer

Physical factorsDeveloper’s behaviour

Module C:Interaction

• The model has three modules: 1. environment, 2. agent, and 3. interaction

• The environment module represents the properties owned by the land; land cover type, land price, distance to CBD, distance to road

• The agent represents properties exhibited by the developers; the capital, number of developers

Environment Agent

Agung Wahyudi S42817150

Method #2: The workflow

Cost analysis

Land prices?

Find suitable area

Assess the area

REJECTExclude from

re-visitingBeyond capital

Within the capital

Development feasible? NO

Develop

Update land price

Find cellMin {land price}

START

Update land cover

Secure capital

Developers

Road construction cost

Site clearing cost

Expected selling profit

YES

Development decision

Agung Wahyudi S42817150

Method #3: The model interface

• The interface offers views on land cover, land value, distance to CBD, or distance to road.

• Developers’ parameters: number of developers, the searching radius a, initial capital, and loan.

• Monitoring panels (on the right).

Agung Wahyudi S42817150

Results #1:Urban land cover growth

• The movement of the developers: toward the outer most of study area.

• The developers capture the potential economic opportunity on the outer most area.

t=0 t=0+n

Agung Wahyudi S42817150

Results #2: Land value changes

• Land value in newly developed areas increase ( 300%) as developers construct ∼the infrastructure in these sites.

• Increasing land values prevent other developers moving into these areas.

t=0 t=0+n

Agung Wahyudi S42817150

Tentative conclusions and future work

• The model offers insight into how new residential areas and land values across JMA is shaped by the developer behaviour.

• Deviation of the simulated urban pattern from the observed coverage suggests that the profit oriented (profit maximization) seems only one dimension of the decision to develop. • Marketing

• Land banking

• Limitations: 1. Simple initial set of variables,2. No temporal dimension.

• Future work: 1. A typology of developers,2. Incorporate notion of land banking, and3. Investigate inclusion of a temporal dimension.

THANK YOU

@agungwah

Questions? Comments? Follow my research on

Agung Wahyudi S42817150

FAQ

• Why the model have no sensitivity analysis?• What is the impact of other factors?