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Our Research

Our research focuses on several key areas employing spatial analysis methodologies and metrics, as well as  dynamic simulation models. Both ‘off-the-shelve’ commercial software and software developed by us are used.

Examples of research at our LISA Lab include

-Complexity analysis and dynamic simulation

-Creative cities/firms/industries simulation models

-Energy efficient cities, urban form and decision making

-Land  Use Change and Scenarios for City and Regional Planning

-Spatial analysis and urban spatial metrics (in particular metrics for urban growth and shrinkage)

-Integrated Land Use and Transport Models

- Big Data, data mining, data validation and model calibration


In the sections that follow, you will find some examples of policy questions and research aims under the examples of the dynamic models and analysis t we have developed.

We also recommend the following papers for a comprehensive review on the foundations of of metrics, models, algorithms and frameworks approaches:



Please feel free to send us an email requesting more information, the papers and the models, we are more than happy to exchange ideas and cooperate with you.

****In order to run our models you will need to download the free platform: netlogo programming language (   (for the more recent models, for the oldest ones you will need C and C++. Some general knowledge in GIS and coding will be needed if you plan to add/adapt our code (we will be very thankful if you send us your changes to the model, we will recognize your contribution to the models's development)

The models & metrics 

11. Metrics for growth and shrinkage

 ----Comprehensive portfolio of spatial metrics for growth and shrinkage;  contribute to the development of quantitative methods that quantify these patterns, focusing on spatial metrics and aiming at filling the gaps in the current methods; present a set of metrics (both new metrics and metrics adapted from the literature) which can be used to measure spatial patterns of growing and shrinking cities, and perform an empirical application of these metrics. Understand the process of land use change, particularly the structural factors behind growth and shrinkage; identify particular spatial patterns that are characteristic of growing and shrinking cities, taking into account that these two processes can occur simultaneously and at different spatial scales; 

Work developed by Jose Pedro Reis and Elisabete A. Silva

Case studies Espinho and Vila Real, Portugal

More than 300 spatial metrics were surveyed


In order to know more about our work on this subject please see following papers: 

Reis, J.P. and E. A. Silva (2015)Spatial Metrics to Study Urban Patterns in Growing and Shrinking Cities. (with J. Reis). Urban Geography. in press

Reis, J.P. and E. A. Silva (2014) Measuring space: a review of spatial metrics for urban growth and shrinkage (with J. Reis). In: The Routledge Handbook of Planning Research Methods (Eds. Elisabete A. Silva, Patsy Healey, Neil Harris and Pieter van den Broeck), Routledge – 2015 – 530 pages

10. The complex interactions between urban land use and transport systems - a dynamic simulation model

What are the complex interactions between urban land use and transport systems? what are its spatial and temporal attributes and dynamics? What are the key concepts of urban spatial structure, accessibility and commuting behaviour? A Multiagent-based model to simulate the complex residential-job location choice behaviour of household agents. It ultimately seeks to explore how the interaction among the behavioural processes of households selecting a place to live and a place to work, lead to the emergence of urban spatial structure and commuting behaviour (i.e. origin, destination, distance, cost and time).

Work developed by Ransford Acheapong and Elisabete A. Silva

Case study: Kumasi, Ghana

In order to know more about our work on this subject please see following papers:

Acheapong, R. and E. A. Silva (2015) Land Use-Transport Interaction Modelling: A Review of the Literature and Future Research Directions. Journal of Transport and Land Use (with R. Acheapong). in press  -


8. From Big Data Sets to Collective Human Behavior Patterns and Urban Spatial Structure

How to analyzing and simulating Spatial-Temporal Dynamics using big data? confirmatory analysis of existent data from sensors and big data from mobile devises (i.e. mobile-phone) on: 1 Population spatial distribution in Shanghai (Heat map, static metric and dynamic metric), 2 Urban Spatial Structure of Shanghai (residential areas, employment areas and leisure areas), 3. O-D distribution (real 4-step transportation, from big data to generalize human behavior patterns), 5. valuate the telationship between the spatial population flow pattern and land use\road\underground\planning policy\space syntax

How to incorporate human behavior patterns with ABM model to simulate the future population spatial distribution and future O-D distribution

Work developed by Chaowei Xiao and Elisabete A. Silva

Case study: Shanghai

Shanghai Multi-day Average Population Density Map Obtained from Big Data


7.  BM4SIS model - Business models for sustainability

---- What is the impact of sustainable business model innovation on the industrial system? This research aims to conduct ‘experiments’, combining SBMs, and other agent behaviours, in a ABM to understand the implications for system level outcomes (energy use, resource depletion, wealth). Configurations (describing what gets made where and how including the physical network and value network configuration) that emerge for a given experiment will be captured. These configurations will be assessed for their ability to deliver sustainability at the system level. 

Model developed jointly by Elisabete A. Silva (at Dep. Land Economy) and Steve Evans, Doroteya Vladimirova, Maria Holgado Granados, Miying Yang, Kirsten van Fossen (Dep. of Engineering - Institute for Manufacturing)


 6. CID-USST model - Dynamic models for creative cities/firms/industries 

----What factors determine the location of creative industries? ; Is the strategy of creative industries’ parks effective in promoting creative industries/firms?; In the development of creative industries what are the land market and urban spatial structure consequences? And what are the policy implications? How can we sustain the development of the creative industries? Is tax reduction, land rent reduction and trade promotion enough?; How can we observe the evolution of offer/demand dynamics in available office/industry space, residential space, and propose sustainable policies? ; What are the location determinants for both the firms and the workers

Work developed by: Helin Liu and Elisabete Silva (2011-2013) and expanded further by Helin Liu, Qian Wang, Elisabete Silva, Yalan Li and Yan Qin  (2013 - 2015)

Model applied to Nanjing, Yangpu District - Shanghai, Jiading - Shanghai.

In order do download the initial demo version please click here 

In order to download the Nanjing model please click here

In order to download the Jiading model please click here



5. 4CMR' s Agent-based model of global carbon mitigation through bilateral negotiation under economic constraints

----What set of conditions would be effective in moving nations, regions and the global economy onto the energy transformation and emissions reduction pathways  necessary for significant emissions reductions in the aggregate? The current paper explores this question through the use of an agent-based model. It seeks through this modelling, to examine if global carbon mitigation is achievable with no global unitary framework but through bilateral negotiation; and to explore what mitigation level can be reached in three different mitigation schemes

Model developed by Doug Crawford-Brown, Helin Liu and Elisabete A. Silva

Model applied to world - Annex I and non-Annex I countries

Download/click here


4 . IUBEA model - Energy efficient cities, urban form and decision making 

----What is the energy consumption locally and globally and EC reduction policies?; Whatare the techniques for extending building level models to quantify energy consumption of a neighbourhood, district, or city region; What are the targets of energy consumption? Are they achievable and where? (Identify areas that will comply, level of compliance, etc.)? ; How to track energy change globally and per local authority/building.? Wow to estimated and analysis energy use intensities of sub-categories of buildings?; How to understand how the distribution of Land Use influences energy consumption in London’s local authorities?, What is the percentage of mix use that optimizes Energy?

Model developed jointly by Yu Sun, Elisabete Silva (at Dep. Land Economy), Ruchi Choudhary and Wei Tian (Dep. of Engineering). 

Model applied to London

Download here: 


3. DG-ABC model - ABM and CA integrated model of land transaction

----DG-ABC is an integrated model that incorporates ABM (Agent Base
Model), CA (Cellular Automaton) and Genetic Algorithm (GA) to include both spatial and a-spatial dynamics in an urban system in order to supply a new solution for urban studies. In our model (DG-ABC stands for ‘Developing Genetic-Agent Based Cells’), the social economic behaviours of heterogeneous agents (resident, property developer and government) will be regulated by GA and Theory of Planning Behaviour (TpB). With a pilot study conducted with the model we analyzed how the macro level of the spatial pattern change (the emergence phenomena) is produced from the interactions of actors at the micro level (the heterogeneous behaviours and interactions between agents, and the discrete
spatial dynamics represented by CA).

Model developed by Ning Wu and Elisabete A. Silva

Model applied to 

Download here:

In order to know more about our work on this model please see following papers: 

Wu, N. and E. A. Silva (2013) DG-ABC: An Integrated multi-agent and cellular automata urban growth model. Technologies in Urban and Spatial Planning: Virtual Cities and Territories? (Eds. Nuno Norte Pinto, José António Tenedório, António Pais Antunes and Josep Roca ), Springer

Wu, N. and E. A. Silva (2010) Integration of genetic agents and cellular automata for dynamic urban growth modelling: pilot studies. (With N. Wu) WCTR-World Congress of Transportation Research, July, Lisbon, Portugal. Conference program: page 61; Book of Abstracts: (digital format paper 1858 (page 119) ; PowerPoint: 15 slides, Paper:  10 pages.

Wu, N. and E. A. Silva (2009) Integration of genetic agents and cellular automata for dynamic urban growth modelling. (With N. Wu) Geocomputation, November, Australia. Paper 5 pages.


2. CVCA model - countervailing CA of landscape strategies

-----The CVCA model was conceived to provide answers to questions such as: What is the state of the landscape? Which landscape strategies are predominant? How can one create a different image of the metropolitan area?What is the dominant pattern (corridor, patch)? Are the strategies promoting connectivity? Which landscape metrics increase the dominant strategy?

Model developed by Elisabete A. Silva

Model applied to Lisbon and Porto Metropolitan Areas

Download here: 

In order to know more about our work on this model please see following papers: 

Silva, E. A. J. Wileden, J. and J. Ahern (2008) Strategies for Landscape Ecology in Metropolitan Planning: Applications Using Cellular Automata Models., Progress in Planning, 70(4):133-177 - ISSN: 0305-9006


1. SLEUTH model - CA model of urban and land use change

SLEUTH is a tightly coupled, modified cellular automaton model of urban and other land class change. Its main component is the Clarke Urban Growth Model (UGM) which drives a second component, the Deltatron land cover model. 

** All C language code and libraries, and a sample data set, demo_city, is contained within the compressed SLEUTH3.0beta file. Information on file structure, decompression and how to run SLEUTH may be found on theImplement pages. The Implement page instructions for SLEUTH3.0beta may be used for SLEUTH3.0beta_p01. To post questions or information on the download process please refer to the project discussion board.

Download here:


In order to know more about our work on this model please see following papers: 

Silva, E. A. and K. Clarke (2005) Complexity, Emergence and Cellular Urban Models: Lessons Learned from Appling SLEUTH to two Portuguese Cities. European Planning Studies, 13 (1): 93-115 – ISSN: 0965-4313

Silva, E. A. and K. Clarke (2002) Calibration of the SLEUTH Urban Growth Model for Lisbon and Porto, Portugal. Computers, Environment and Urban Systems, 26 (6): 525-552  - ISSN: 0198-9715


Friday 2 November 2018

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