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
- Spatial Inequality and Public Policy in Global Cities
In the sections that follow, you will find some examples of our research:
Projects, models & metrics
- Addressing complexity in the role of green and blue spaces in achieving healthier cities
There is a growing body of evidence supporting the correlation between availability of natural spaces and population health improvement. However, more systematic evidence of how structural characteristics of natural spaces influence health, and how spatial scales, population groups, and urban contexts influence this process, are still lacking. In this context, this research explores associations between green-blue spaces characteristics and population mental health through the lens of complexity theory — using novel types of data (e.g. social media posts) — with the aim of achieving new holistic insights on how this complex system works. For this the research will start with a literature review of green-blue spaces spatial metrics used in health-related primary studies. And a meta-analysis of mental health impacts related to green-blue spaces exposure. The second part of the project will involve a spatial and dynamic analysis of remote sensing images, open mapping platforms, statistical year books, and twitter posts data in the case studies - London and Lisbon. This will generate maps of green–blue health metrics that capture baseline features important for population mental health. In the fourth chapter, we will develop an Agent Based Model (ABM), based on pattern-oriented modelling (POM) and ODD protocols, with a spatial-explicit visualization of agents' dynamic behavior within the urban natural environment; we will evaluate this ABM on the same case studies of chapter 3. This will help us explore the associations presented in the literature review and in the spatial analysis from a deductive perspective. This will also help us understand nonlinear associations, feedback loops, and emergent properties of the system, and allow us to test possible generalizations of model internal rules. We believe the combined results from these analysis will complement our understanding of how underlying mechanisms of this system work together in a mutually reinforcing way, better informing future planning and decision-making.
Work developed by Ana Paula Seraphim and Elisabete A. Silva
In order to know more about our work on this subject please see following papers
SERAPHIM, A.; ELISABETE, S. (2021). Literature review of Green–Blue Spaces and Health Research between 2000-2021: A Bibliometric Analysis. Paper presentation in the Healthy City Design 2021 International Congress. London, UK/ Online, October 11-14