scholarly journals Agent-based Housing Market Microsimulation for Integrated Land Use, Transportation, Environment Model System

2013 ◽  
Vol 19 ◽  
pp. 841-846 ◽  
Author(s):  
Adam Rosenfield ◽  
Franco Chingcuanco ◽  
Eric J. Miller
Keyword(s):  
Land Use ◽  
Housing Market ◽  
Model System ◽  
Agent Based ◽  
Environment Model

scholarly journals An agent-based transportation impact sketch planning (TISP) model system

2021 ◽  
Vol 14 (1) ◽  
pp. 219-253
Author(s):  
Ayad Hammadi ◽  
Eric J Miller
Keyword(s):  
Land Use ◽  
Architectural Design ◽  
Travel Demand ◽  
Transportation Network ◽  
Geographic Location ◽  
Model System ◽  
Demand Model ◽  
Control Variables ◽  
Agent Based ◽  
Traffic Impact

A traffic impact sketch planning (TISP) model is presented for the estimation of the likely travel demand generated by a major land-use development or redevelopment project. The proposed approach overcomes the problems with the non-behavioral transportation-related studies used in practice for assessing the development design impacts on the local transportation system. The architectural design of the development, in terms of the number and type of dwellings, by number of bedrooms per unit, and the land-use categories of the non-residential floorspace, are reflected in the TISP model through an integrated population and employment synthesis approach. The population synthesis enables the feasible deployment of an agent-based microsimulation (ABM) model system of daily activity and travel demand for a quick, efficient, and detailed assessment of the transportation impacts of a proposed neighborhood or development. The approach is not restricted to a certain type of dataset of the control variables for the geographic location of the development. Datasets for different geographic dimensions of the study area, with some common control variables, are merged and cascaded into a synthesized, disaggregate population of resident persons, households and jobs. The prototype implementation of the TISP model is for Waterfront Toronto’s Bayside Development Phase 2, using the operational TASHA-based GTAModel V4.1 ABM travel demand model system. While the conventional transportation studies focus on the assessment of the local traffic impacts in the immediate surroundings of the development, the TISP model investigates and assesses many transportation related impacts in the district, city, and region, for both residents and non-residents of the development. TISP model analysis includes the overall spatiotemporal trips distribution generated by the residents and non-residents of the development for the auto and non-auto mobility systems and the simulated agents diurnal peaking travel times. The model results are compared with the trips estimates by a prior project traffic impact study and the Institute of Transportation Engineers (ITE) Trip Generation Manual (TGM) rates of weekday trips for the relevant land uses. Future extensions and improvements of the model including the generalization and full automation of the model, and the bi-level macro-micro representation of the transportation network are also discussed.

scholarly journals The role and significance of planning in the determination of house prices in Australia: Recent policy debates

2021 ◽  
pp. 0308518X2198894
Author(s):  
Peter Phibbs ◽  
Nicole Gurran
Keyword(s):  
Land Use ◽  
Housing Market ◽  
Land Use Planning ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Evidence Base ◽  
Urban Housing ◽  
Price Inflation ◽  
Depth Analysis

On the world stage, Australian cities have been punching above their weight in global indexes of housing prices, sparking heated debates about the causes of and remedies for, sustained house price inflation. This paper examines the evidence base underpinning such debates, and the policy claims made by key commentators and stakeholders. With reference to the wider context of Australia’s housing market over a 20 year period, as well as an in depth analysis of a research paper by Australia’s central Reserve Bank, we show how economic theories commonly position land use planning as a primary driver of new supply constraints but overlook other explanations for housing market behavior. In doing so, we offer an alternative understanding of urban housing markets and land use planning interventions as a basis for more effective policy intervention in Australian and other world cities.

scholarly journals Theoretical foundations of human decision-making in agent-based land use models – A review

2017 ◽  
Vol 87 ◽  
pp. 39-48 ◽  
Author(s):  
J. Groeneveld ◽  
B. Müller ◽  
C.M. Buchmann ◽  
G. Dressler ◽  
C. Guo ◽  
...  
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Agent Based ◽  
Human Decision ◽  
Land Use Models ◽  
Theoretical Foundations

scholarly journals Deforestation in Amazonia impacts riverine carbon dynamics

2016 ◽  
Vol 7 (4) ◽  
pp. 953-968 ◽  
Author(s):  
Fanny Langerwisch ◽  
Ariane Walz ◽  
Anja Rammig ◽  
Britta Tietjen ◽  
Kirsten Thonicke ◽  
...  
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Atlantic Ocean ◽  
Amazon Basin ◽  
Inorganic Carbon ◽  
Carbon Dynamics ◽  
Model System ◽  
Atmospheric Co2 ◽  
Terrestrial Productivity

Abstract. Fluxes of organic and inorganic carbon within the Amazon basin are considerably controlled by annual flooding, which triggers the export of terrigenous organic material to the river and ultimately to the Atlantic Ocean. The amount of carbon imported to the river and the further conversion, transport and export of it depend on temperature, atmospheric CO2, terrestrial productivity and carbon storage, as well as discharge. Both terrestrial productivity and discharge are influenced by climate and land use change. The coupled LPJmL and RivCM model system (Langerwisch et al., 2016) has been applied to assess the combined impacts of climate and land use change on the Amazon riverine carbon dynamics. Vegetation dynamics (in LPJmL) as well as export and conversion of terrigenous carbon to and within the river (RivCM) are included. The model system has been applied for the years 1901 to 2099 under two deforestation scenarios and with climate forcing of three SRES emission scenarios, each for five climate models. We find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90 %) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO2 concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO2 concentrations increase riverine inorganic carbon amount by up to 20 % (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60 % due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40 % under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean.

scholarly journals Comparison of empirical methods for building agent-based models in land use science

2007 ◽  
Vol 2 (1) ◽  
pp. 31-55 ◽  
Author(s):  
Derek T. Robinson ◽  
Daniel G. Brown ◽  
Dawn C. Parker ◽  
Pepijn Schreinemachers ◽  
Marco A. Janssen ◽  
...  
Keyword(s):  
Land Use ◽  
Empirical Methods ◽  
Agent Based Models ◽  
Agent Based

An open framework for agent based modelling of agricultural land use change

2014 ◽  
Vol 61 ◽  
pp. 19-38 ◽  
Author(s):  
Dave Murray-Rust ◽  
Derek T. Robinson ◽  
Eleonore Guillem ◽  
Eleni Karali ◽  
Mark Rounsevell
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Agent Based ◽  
Open Framework ◽  
Agent Based Modelling
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