Andrew Crooks | SUNY: University at Buffalo (original) (raw)

Journal Articles by Andrew Crooks

Proceedings of the 7th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising , 2023

Generating synthetic social networks is an important task for many problems that study humans, th... more Generating synthetic social networks is an important task for many problems that study humans, their behavior, and their interactions. Geosocial networks enrich social networks with location information. Commonly used models to generate synthetic social networks include the classical Erdős-Rényi, Barabási-Albert, and Watts-Strogatz models. However, these classic social network models do not consider the location of individuals. Real-world geosocial networks do exhibit a strong spatial autocorrelation, thus having a higher likelihood of a social connection between agents that are spatially close. As such, recent variants of the three classical models have been proposed to consider location information. Yet, these existing solutions assume that individuals are located on a uniform lattice and exhibit certain limitations when applied to real-world data that exhibits clusters. In this work, we discuss these limitations and propose new approaches to extend the three classic social network generation models to geosocial networks. Our experiments show that our generated synthetic geosocial networks address the shortcomings of the state-of-the-art models and generate realistic geosocial networks that exhibit high similarity to real-world geosocial networks.

Environmental Research Letters, 2021

Flood risk is increasing in urban communities due to climate change and socioeconomic development... more Flood risk is increasing in urban communities due to climate change and socioeconomic development. Socioeconomic development is a major cause of urban expansion in flood-prone regions, as it places more physical, economic, and social infrastructure at risk. Moreover, in light of the 2030 Agenda for Sustainable Development by the United Nations, it has become an international imperative to move toward sustainable cities. Current approaches to quantify this risk use scenario-based methods involving arbitrary projections of city growth. These methods seldom incorporate geographical, social, and economic factors associated with urbanization and cannot mimic city growth under various urban development plans. In this paper, we introduce a framework for understanding the interactions between urbanization and flood risk as an essential ingredient for flood risk management. This framework integrates an urban growth model with a hazard model to explore flood risk under various urban development scenarios. We then investigate the effectiveness of coupling nonstructural flood mitigation measures-in terms of urban planning policies and socioeconomic incentives-with urban growth processes to achieve sustainable and resilient communities. Using this framework, we can not only simulate urban expansion dynamics through time and its effect on flood risk but also model the growth of a region under various urban planning policies and assess the effectiveness of these measures in reducing flood risk. Our analysis reveals that while current urban development plans may put more people and assets at flood risk, the nonstructural strategies considered in this study mitigated the consequences of floods. Such a framework could be used to assist city planners and stakeholders in examining tradeoffs between costs and benefits of future land development in achieving sustainable and resilient cities.

Scientific Reports, 2021

Floods are among the costliest natural hazards and their consequences are expected to increase fu... more Floods are among the costliest natural hazards and their consequences are expected to increase further in the future due to urbanization in flood-prone areas. It is essential that policymakers understand the factors governing the dynamics of urbanization to adopt proper disaster risk reduction techniques. Peoples' relocation preferences and their perception of flood risk (collectively called human behavior) are among the most important factors that influence urbanization in flood-prone areas. Current studies focusing on flood risk assessment do not consider the effect of human behavior on urbanization and how it may change the nature of the risk. Moreover, flood mitigation policies are implemented without considering the role of human behavior and how the community will cope with measures such as buyout, land acquisition, and relocation that are often adopted to minimize development in flood-prone regions. Therefore, such policies may either be resisted by the community or result in severe socioeconomic consequences. In this study, we present a new Agent-Based Model (ABM) to investigate the complex interaction between human behavior and urbanization and its role in creating future communities vulnerable to flood events. We identify critical factors in the decisions of households to locate or relocate and adopt policies compatible with human behavior. The results show that when people are informed about the flood risk and proper incentives are provided, the demand for housing within 500-year floodplain may be reduced as much as 15% by 2040 for the case study considered. On the contrary, if people are not informed of the risk, 29% of the housing choices will reside in floodplains. The analyses also demonstrate that neighborhood quality-influenced by accessibility to highways, education facilities, the city center, water bodies, and green spaces, respectively-is the most influential factor in peoples' decisions on where to locate. These results provide new insights that may be used to assist city planners and stakeholders in examining tradeoffs between costs and benefits of future land development in achieving sustainable and resilient cities.

Transactions in GIS, 2022

Calibration of agent-based models (ABMs) is a major challenge due to the complex nature of the sy... more Calibration of agent-based models (ABMs) is a major challenge due to the complex nature of the systems being modeled, the heterogeneous nature of geographical regions, the varying effects of model inputs on the outputs, and computational intensity. Nevertheless, ABMs need to be carefully tuned to achieve the desirable goal of simulating spatiotemporal phenomena of interest, and a well-calibrated model is expected to achieve an improved understanding of the phenomena. To address some of the above challenges, this article proposes an integrated framework of global sensitivity analysis (GSA) and calibration, called GSA-CAL. Specifically, variance-based GSA is applied to identify input parameters with less influence on differences between simulated outputs and observations. By dropping these less influential input parameters in the calibration process, this research reduces the computational intensity of calibration. Since GSA requires many simulation runs, due to ABMs' stochasticity, we leverage the high-performance computing power provided by the advanced cyberinfrastructure. A spatially explicit ABM of influenza transmission is used as the case study to demonstrate the utility of the framework. Leveraging GSA, we were able to exclude less influential parameters in the model calibration process and demonstrate the importance of revising local settings for an epidemic pattern in an outbreak.

Computational Urban Science, 2022

Geographically-explicit simulations have become crucial in understanding cities and are playing a... more Geographically-explicit simulations have become crucial in understanding cities and are playing an important role in Urban Science. One such approach is that of agent-based modeling which allows us to explore how agents interact with the environment and each other (e.g., social networks), and how through such interactions aggregate patterns emerge (e.g., disease outbreaks, traffic jams). While the use of agent-based modeling has grown, one challenge remains, that of creating realistic, geographically-explicit, synthetic populations which incorporate social networks. To address this challenge, this paper presents a novel method to create a synthetic population which incorporates social networks using the New York Metro Area as a test area. To demonstrate the generalizability of our synthetic population method and data to initialize models, three different types of agent-based models are introduced to explore a variety of urban problems: traffic, disaster response, and the spread of disease. These use cases not only demonstrate how our geographically-explicit synthetic population can be easily utilized for initializing agent populations which can explore a variety of urban problems, but also show how social networks can be integrated into such populations and large-scale simulations.

Socio-Environmental Systems Modelling, 2022

Agricultural water reuse is gaining momentum to address freshwater scarcity worldwide. The main o... more Agricultural water reuse is gaining momentum to address freshwater scarcity worldwide. The main objective of this paper was to investigate the micro-level dynamics of water reuse adoption by farmers at the watershed scale. An agent-based model was developed to simulate agricultural water consumption and socio-hydrological dynamics. Using a case study in California, the developed model was tested, and the results showed that agricultural water reuse adoption by farmers is a gradual and time-consuming process. In addition, results also showed that agricultural water reuse could significantly decrease the water shortage (by 57.7%) and groundwater withdrawal (by 74.1%). Furthermore, our results suggest that recycled water price was the most influential factor in total recycled water consumption by farmers. Results also showed how possible freshwater shortage or groundwater withdrawal regulations could increase recycled water use by farmers. The developed model can significantly help assess how the current water reuse management practices and strategies would affect the sustainability of agricultural water resources. Keywords Water reuse; agent-based modelling; agricultural water management; recycled water for irrigation Code availability The WRAF (water reuse adoption by farmers) model presented in this paper and its complete description following the Overview, Design concepts, Details, and Decision-making (ODD) (Grimm et al., 2006) protocol can be found at https://www.comses.net/codebase-release/cc6d551e-cf0f-472e-a54b-28591cd39b4d/.

Computational and Mathematical Organization Theory, 2023

The employment of drone strikes has been ongoing and the public continues to debate their perceiv... more The employment of drone strikes has been ongoing and the public continues to debate their perceived benefits. A question that persists is whether drone strikes contribute to an increase in radicalization. This paper presents a data-driven approach to explore the relationship between drone strikes conducted in Pakistan and subsequent responses, often in the form of terrorist attacks carried out by those in the communities targeted by these particular counterterrorism measures. Our exploration and analysis of news reports which discussed drone strikes and radicalization suggest that government-sanctioned drone strikes in Pakistan appear to drive terrorist events with a distributed lag that can be determined analytically. We leverage news reports to inform and calibrate an agent-based model grounded in radicalization and opinion dynamics theory. This enabled us to simulate terrorist attacks that approximated the rate and magnitude observed in Pakistan from 2007 through 2018. We argue that this research effort advances the field of radicalization and lays the foundation for further work in the area of data-driven modeling and drone strikes.

Computational and Mathematical Organization Theory, 2023

We introduce the Urban Life agent-based simulation used by the Ground Truth program to capture th... more We introduce the Urban Life agent-based simulation used by the Ground Truth program to capture the innate needs of a human-like population and explore how such needs shape social constructs such as friendship and wealth. Urban Life is a spatially explicit model to explore how urban form impacts agents' daily patterns of life. By meeting up at places agents form social networks, which in turn affect the places the agents visit. In our model, location and co-location affect all levels of decision making as agents prefer to visit nearby places. Co-location is necessary (but not sufficient) to connect agents in the social network. The Urban Life model was used in the Ground Truth program as a virtual world testbed to produce data in a setting in which the underlying ground truth was explicitly known. Data was provided to research teams to test and validate Human Domain research methods to an extent previously impossible. This paper summarizes our Urban Life model's design and simulation along with a description of how it was used to test the ability of Human Domain research teams to predict future states and to prescribe changes to the simulation to achieve desired outcomes in our simulated world.

Journal of Environmental Management, 2023

Soil organic carbon (SOC) can be increased by cultivating bioenergy crops to produce low-carbon f... more Soil organic carbon (SOC) can be increased by cultivating bioenergy crops to produce low-carbon fuels, improving soil quality and agricultural productivity. This study evaluates the incentives for farmers to sequester SOC by adopting a bioenergy crop, carinata. Two agricultural management scenariosbusiness as usual (BaU) and a climate-smart (no-till) practicewere simulated using an agent-based modeling approach to account for farmers' carinata adoption rates within their context of traditional crop rotations, the associated profitability, influences of neighboring farmers, as well as their individual attitudes. Using the state of Georgia, US, as a case study, the results show that farmers allocated 1056 × 10 3 acres (23.8%; 2.47 acres is equivalent to 1 ha) of farmlands by 2050 at a contract price of 6.5perbushelofcarinataseedsandwithanincentiveof6.5 per bushel of carinata seeds and with an incentive of 6.5perbushelofcarinataseedsandwithanincentiveof50 Mg − 1 CO2e SOC sequestered under the BaU scenario. In contrast, at the same contract price and SOC incentive rate, farmers allocated 1152 × 10 3 acres (25.9%) of land under the no-till scenario, while the SOC sequestration was 483.83 × 10 3 Mg CO2e, which is nearly four times the amount under the BaU scenario. Thus, this study demonstrated combinations of seed prices and SOC incentives that encourage farmers to adopt carinata with climate-smart practices to attain higher SOC sequestration benefits.

Environment and Planning B, 2024

Today we are awash with data, especially when it comes to studying cities from a diverse data eco... more Today we are awash with data, especially when it comes to studying cities from a diverse data ecosystem ranging from demographic to remotely sensed imagery and social media. This has led to the growth of urban analytics providing new ways to conduct quantitative research within cities. One area that has seen significant growth is using natural language processing techniques on text data from social media to explore various issues relating to urban morphology. However, we would argue that social media only provides limited insights when dealing with longer-term urban phenomena, such as the growth and shrinkage of cities. This relates to the fact that social media is a relatively recent phenomenon compared to longer-term urban problems that take decades to emerge. Concerning longer-term coverage, newspapers, which are increasingly becoming digitized, provide the possibility to overcome the limitations of social media and provide insights over a timeframe that social media does not. To demonstrate the utility of newspapers for urban analytics and to study longer-term urban issues, we utilize an advanced topic modeling technique (i.e., BERTopic) on a large number of newspaper articles from 1975 to 2021 to explore urban shrinkage in Detroit. Our topic modeling results reveal insights related to how Detroit shrinks. For example, side effects of 2007 to 2009 economic recessions on Detroit's automobile industry, local employment status, and the housing market.

Computers, Environment and Urban Systems, 2024

Disasters have been a long-standing concern to societies at large. With growing attention being p... more Disasters have been a long-standing concern to societies at large. With growing attention being paid to resilient communities, such concern has been brought to the forefront of resilience studies. However, there is a wide variety of definitions with respect to resilience, and a precise definition has yet to emerge. Moreover, much work to date has often focused only on the immediate response to an event, thus investigating the resilience of an area over a prolonged period of time has remained largely unexplored. To overcome these issues, we propose a novel framework utilizing network analysis and concepts from disaster science (e.g., the resilience triangle) to quantify the long-term impacts of wildfires. Taking the Mendocino Complex and Camp wildfires-the largest and most deadly wildfires in California to date, respectively-as case studies, we capture the robustness and vulnerability of communities based on human mobility data from 2018 to 2019. The results show that demographic and socioeconomic characteristics alone only partially capture community resilience, however, by leveraging human mobility data and network analysis techniques, we can enhance our understanding of resilience over space and time, providing a new lens to study disasters and their long-term impacts on society.

International Journal of Geographical Information Science, 2024

This study addresses the challenge of equifinality in agent-based modeling (ABM) by introducing a... more This study addresses the challenge of equifinality in agent-based modeling (ABM) by introducing a novel sequential calibration approach. Equifinality arises when multiple models equally fit observed data, risking the selection of an inaccurate model. In the context of ABM, such a situation might arise due to limitations in data, such as aggregating observations into coarse spatial units. It can lead to situations where successfully calibrated model parameters may still result in reliability issues due to uncertainties in accurately calibrating the inner mechanisms. To tackle this, we propose a method that sequentially calibrates model parameters using diverse outcomes from multiple datasets. The method aims to identify optimal parameter combinations while mitigating computational intensity. We validate our approach through indoor pedestrian movement simulation, utilizing three distinct outcomes: (1) the count of grid cells crossed by individuals, (2) the number of people in each grid cell over time (fine grid) and (3) the number of people in each grid cell over time (coarse grid). As a result, the optimal calibrated parameter combinations were selected based on high test accuracy to avoid overfitting. This method addresses equifinality while reducing computational intensity of parameter calibration for spatially explicit models, as well as ABM in general.

International Journal of Geographical Information Science, 2024

The notion of physical space has long been central in geographical theories. However, the widespr... more The notion of physical space has long been central in geographical theories. However, the widespread adoption of information and communication technologies (ICTs) has freed human dynamics from purely physical to also relational and cyber spaces. While researchers increasingly recognize such shifts, rarely have studies examined how the information propagates in these hybrid spaces (ie physical, relational, and cyber). By exploring the vaccine opinion dynamics through agent-based modeling, this study is the first that combines all hybrid spaces and explores their distinct impacts on human dynamics from an individual's perspective. Our model captures the temporal dynamics of vaccination progress with small errors (MAE ¼ 2.45). Our results suggest that all hybrid spaces are indispensable in vaccination decision-making. However, in our model, most of the agents tend to give more emphasis to the information that is spread in the physical instead of other hybrid spaces. Our study not only sheds light on human dynamics research but also offers a new lens to identifying vaccinated individuals which has long been challenging in disease-spread models. Furthermore, our study also provides responses for practitioners to develop vaccination outreach policies and plan for future outbreaks.

PLoS ONE, 2024

The COVID-19 pandemic prompted governments worldwide to implement a range of containment measures... more The COVID-19 pandemic prompted governments worldwide to implement a range of containment measures, including mass gathering restrictions, social distancing, and school closures. Despite these efforts, vaccines continue to be the safest and most effective means of combating such viruses. Yet, vaccine hesitancy persists, posing a significant public health concern, particularly with the emergence of new COVID-19 variants. To

ACM Transactions on Spatial Algorithms and Systems, 2024

Human mobility data science using trajectories or check-ins of individuals has many applications.... more Human mobility data science using trajectories or check-ins of individuals has many applications. Recently, we have seen a plethora of research eforts that tackle these applications. However, research progress in this ield is limited by a lack of large and representative datasets. The largest and most commonly used dataset of individual human trajectories captures fewer than 200 individuals while data sets of individual human check-ins capture fewer than 100 check-ins per city per day. Thus, it is not clear if indings from the human mobility data science community would generalize to large populations. Since obtaining massive, representative, and individual-level human mobility data is hard to come by due to privacy considerations, the vision of this paper is to embrace the use of data generated by large-scale socially realistic microsimulations. Informed by both real data and leveraging social and behavioral theories, massive spatially explicit microsimulations may allow us to simulate entire megacities at the person level. The simulated worlds, which do not capture any identiiable personal information, allow us to perform łin silicož experiments using the simulated world as a sandbox in which we have perfect information and perfect control without jeopardizing the privacy of any actual individual. In silico experiments have become commonplace in other scientiic domains such as chemistry and biology, permitting experiments that foster the understanding of concepts without any harm to individuals. This work describes challenges and opportunities for leveraging massive and realistic simulated alternate worlds for in silico human mobility data science.

Frontiers in Microbiology, 2024

The COVID-19 pandemic has prompted an unprecedented global effort to understand and mitigate the ... more The COVID-19 pandemic has prompted an unprecedented global effort to understand and mitigate the spread of the SARS-CoV-2 virus. In this study, we present a comprehensive analysis of COVID-19 in Western New York (WNY), integrating individual patient-level genomic sequencing data with a spatially informed agent-based disease Susceptible-Exposed-Infectious-Recovered (SEIR) computational model. The integration of genomic and spatial data enables a multi-faceted exploration of the factors influencing the transmission patterns of COVID-19, including genetic variations in the viral genomes, population density, and movement dynamics in New York State (NYS). Our genomic analyses provide insights into the genetic heterogeneity of SARS-CoV-2 within a single lineage, at region-specific resolutions, while our population analyses provide models for SARS-CoV-2 lineage transmission. Together, our findings shed light on localized dynamics of the pandemic, revealing potential cross-county transmission networks. This interdisciplinary approach, bridging genomics and spatial modeling, contributes to a more comprehensive understanding of COVID-19 dynamics. The results of this study have implications for future public health strategies, including guiding targeted interventions and resource allocations to control the spread of similar viruses.

Scientific Data, 2024

Within the geo-simulation research domain, micro-simulation and agent-based modeling often requir... more Within the geo-simulation research domain, micro-simulation and agent-based modeling often require the creation of synthetic populations. Creating such data is a time-consuming task and often lacks social networks, which are crucial for studying human interactions (e.g., disease spread, disaster response) while at the same time impacting decision-making. We address these challenges by introducing a Python based method that uses the open data including that from 2020 U.S. Census data to generate a large-scale realistic geographically explicit synthetic population for America's 50 states and Washington D.C. along with the stylized social networks (e.g., home, work and schools). the resulting synthetic population can be utilized within various geo-simulation approaches (e.g., agent-based modeling), exploring the emergence of complex phenomena through human interactions and further fostering the study of urban digital twins.

Environment and Planning B, 2023

DIGITAL HEALTH, 2023

The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of publi... more The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of public discussion. In this discussion, various social media platforms have a key role. While this has long been recognized, the way by which the public assigns attention to such topics remains largely unknown. Furthermore, the question of whether there is a discrepancy between people's opinions as expressed online and their actual decision to vaccinate remains open. To shed light on this issue, in this paper we examine the dynamics of online debates among four prominent vaccines (i.e., COVID-19, Influenza, MMR, and HPV) through the lens of public attention as captured on Twitter in the United States from 2015 to 2021. We then compare this to actual vaccination rates from governmental reports, which we argue serve as a proxy for real-world vaccination behaviors. Our results demonstrate that since the outbreak of COVID-19, it has come to dominate the vaccination discussion, which has led to a redistribution of attention from the other three vaccination themes. The results also show an apparent discrepancy between the online debates and the actual vaccination rates. These findings are in line with existing theories, that of agenda-setting and zero-sum theory. Furthermore, our approach could be extended to assess the public's attention toward other health-related issues, and provide a basis for quantifying the effectiveness of health promotion policies.

Socio-Environmental Systems Modelling, 2022

Proceedings of the 7th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising , 2023

Environmental Research Letters, 2021

Scientific Reports, 2021

Transactions in GIS, 2022

Computational Urban Science, 2022

Socio-Environmental Systems Modelling, 2022

Computational and Mathematical Organization Theory, 2023

Journal of Environmental Management, 2023

Environment and Planning B, 2024

Computers, Environment and Urban Systems, 2024

International Journal of Geographical Information Science, 2024

PLoS ONE, 2024

ACM Transactions on Spatial Algorithms and Systems, 2024

Frontiers in Microbiology, 2024

Scientific Data, 2024

Environment and Planning B, 2023

DIGITAL HEALTH, 2023

Socio-Environmental Systems Modelling, 2022

Introduction The beginning of the twenty-fi rst century marked a milestone in human history. For ... more Introduction The beginning of the twenty-fi rst century marked a milestone in human history. For the fi rst time, more than half of the world's population (3.9 billion people) lived in urban areas. This trend is expected to continue into the foreseeable future with 6.3 billion people projected to live in cities by 2050 (United Nations, 2014). This rapid urbanization will place unprecedented pressures on cities and their ability to provide the most basic of services such as health care and transportation. To plan for this future, we need to better understand the inherent complexity of cities from social, economic and environmental perspectives. Cities are complex dynamic organisms, composed of many discrete parts interacting with each other over space. As such it has been argued that understanding cities represents one of the major scientifi c challenges of our time (Batty, 2013b ; Wilson, 2000). Over the last few decades the focus has shifted from studying urban systems from a top-down perspective to a bottom-up one, specifi cally researching the reasoning on which individual decisions are made and their consequences (Heppen-stall et al ., 2012). With this shift in focus, modelers have started to explore such cites and their dynamics, through the lens of agent-based modeling (ABM). In the remainder of this chapter, we fi rst introduce readers to ABM, outlining their basic properties, provide a simple example to illustrate how through individual interactions more macro phenomena can emerge and discuss how they can be used to study different aspects of cities and regions. We then discuss the potential that big data offer for ABM before moving onto example applications of using big data within agent-based models. We conclude the chapter with a summary and outlook.

Agent-based modeling (ABM) is a technique that allows us to explore how the interactions of hete... more Agent-based modeling (ABM) is a technique that allows us to explore how the interactions of heterogeneous individuals impact on the wider behavior of social/spatial systems. In this article, we introduce ABM and its utility for studying geographical systems. We discuss how agent-based models have evolved over the last 20 years and situate the discipline within the broader arena of geographical modeling. The main properties of ABM are introduced and we discuss how models are capable of capturing and incorporating human behavior. We then discuss the steps taken in building an agent-based model and the issues of verification and validation of such models. As the focus of the article is on ABM of geographical systems, we then discuss the need for integrating geographical information into models and techniques and toolkits that allow for such integration. Once the core concepts and techniques of creating agent-based models have been introduced, we then discuss a wide range of applications of agent-based models for exploring various aspects of geographical systems. We conclude the article by outlining challenges and opportunities of ABM in understanding geographical systems and human behavior.

More than 900 million people or one third of the world’s urban population lives in either slum or... more More than 900 million people or one third of the world’s urban population lives in either slum or squatter settlements. Urbanization rates in developing countries are often so rapid that formal housing development cannot meet the demand. In the past decades, international, national and local development communities have taken several policy actions in an attempt to improve the living conditions of people within slums or to eradicate them completely. However, such policies have largely failed and slum-free cities have remained a distant goal for many developing countries. This chapter argues that for informed policymaking, it is important to investigate questions related to slum formation such as: (1) How do slums form and expand? (2) Where and when are they formed? (3) What types of structural changes and/or policy interventions could improve housing conditions for the urban poor? In order to address these questions, this chapter develops a geosimulation model that is capable of exploring the spatio-temporal dynamics of slum formation and simulating future formation and expansion of slums within cities of the developing world. Our geosimulation model integrates agent-based modeling (ABM) and Geographic Information System (GIS), methods that are often applied separately to explore slums. In our model, ABM simulates human behavior and GIS provides a spatial environment for the housing market. GIS is also used to analyze empirical data using spatial analyses techniques, which is in turn used to validate the model outputs. The core of this framework is a linked dynamic model operating at both micro and macro geographic and demographic scales. The model explores the collective effect of many interacting inhabitants of slums as well as non-slum actors (e.g. local government) and how their interactions within the spatial environment of the city generate the emergent structure of slums at the macro scale. We argue that when empirical data is absent, geosimulation provides useful insights to study implications of various policies. The goal of this framework is to develop a decision support tool that could allow urban planners and policymakers to experiment with new policy ideas ex-ante in a simulated environment. We calibrate and validate the model using data from Ahmedabad, the sixth largest city of India, where 41% of its population lives in slums. This is one of the first attempts to develop an integrated and multi-scalar analytical framework to tackle slum issues in the developing world at multiple spatial scales.

As the urban population rapidly increases to the point where most of us will be living in cities ... more As the urban population rapidly increases to the point where most of us will be living in cities by the end of this century, the need to better understand urban areas grows ever more urgent. Urban simulation modelling as a field has developed in response to this need, util-ising developing technologies to explore the complex interdependencies, feedbacks, and heterogeneities which characterise and drive processes that link the functions of urban areas to their form. As these models grow more nuanced and powerful, it is important to consider the role of transportation within them. Transportation joins, divides, and structures urban areas, providing a functional definition of the geometry and the economic costs that determine urban processes accordingly. However, it has proved challenging to factor transportation into agent-based models (ABM); past approaches to such modelling have struggled to incorporate information about accessibility, demographics, or time costs in a significant way. ABM have not yet embraced alternative traditions such as that in land use transportation modelling that build on spatial interaction in terms of transport directly, nor have these alternate approaches been disaggregated to the level at which populations are represented as relatively autonomous agents. Where disaggregation of aggregate transport has taken place, it has led to econometric models of individual choice or microsimulaton models of household activity patterns which only superficially embody the key principles of ABM. But the explosion in the availability of movement data in recent years, combined with improvements in modelling technology, is easing this process dramatically. In particular, agent-based modelling as a methodology has grown ever more promising and is now capable of emulating the interplay of urban systems and transportation. Here, we explore the importance of this approach, review how transportation has been factored into or omitted from agent-based models of urban areas, and suggest how it might be handled in future applications. Our approach is to take snapshots of different applications and use these to illustrate how transportation is handled in such models.

In the early 1990s, Sierra Leone entered into nearly 10 years of civil war. The ease of accessibi... more In the early 1990s, Sierra Leone entered into nearly 10 years of civil war. The ease of accessibility to the country's diamonds is said to have provided the funding needed to sustain the insurgency over the years. According to Le Billon, the spatial dispersion of a resource is a major defining feature of a war. Using geographic information systems to create a realistic landscape and theory to ground agent behavior, an agent-based model is developed to explore Le Billon's claim. Different scenarios are explored as the diamond mines are made secure and the mining areas are moved from rural areas to the capital. It is found that unexpected consequences can come from minimally increasing security when the mining sites are in rural regions, potentially displacing conflict rather than removing it. On the other hand, minimal security may be sufficient to prevent conflict when resources are found in the city.

Web 2.0, specifically The Cloud, GeoWeb and Wikitecture are revolutionising the way in which we p... more Web 2.0, specifically The Cloud, GeoWeb and Wikitecture are revolutionising the way in which we present, share and analyse geographic data. In this paper we outline and provide working examples a suite of tools which are detailed below, aimed at developing new applications of GIS and related technologies. GeoVUE is one of seven nodes in the National Centre for e-Social Science whose mission it is to develop web-based technologies for the social and geographical sciences. The Node, based at the Centre for Advanced Spatial Analysis, University College London has developed a suite of free software allowing quick and easy visualisation of geographic data in systems such as Google Maps, Google Earth, Crysis and Second Life. These tools address two issues, firstly that spatial data is still inherently difficult to share and visualise for the non-GIS trained academic or professional and secondly that a geographic data social network has the potential to dramatically open up data sources for both the public and professional geographer. With our applications of GMap Creator, and MapTube to name but two, we detail ways to intelligently visualise and share spatial data. This paper concludes with detailing usage and outreach as well as an insight into how such tools are already providing a significant impact to the outreach of geographic information.

The agent-based modeling (ABM) paradigm provides a mechanism for understanding the effects of int... more The agent-based modeling (ABM) paradigm provides a mechanism for understanding the effects of interactions of individuals and through such interactions emergent structures develop, both in the social and physical environment of cities. This chapter explores how through the use of ABM, and its linkage with complexity theory, allows one to create agent-based models for the studying cities from the bottom-up. Specifically the chapter focuses on segregation and land-use change. Furthermore, it will highlight the growing interest between geographical information systems (GIS) and ABM. This linkage is allowing modellers to create spatially explicit agent-based models, thus relating agents to actual geographical places. This approach allows one to explore the link between socio-economic geography of the city and its built physical form, and can support decision-making regarding
interventions within the social and physical environment.

The massive proliferation of traditional geospatial datasets like remote sensing imagery is prese... more The massive proliferation of traditional geospatial datasets like remote sensing imagery is presenting substantial computational challenges associated with the management, processing, and analysis of massive volumes of datasets. While these challenges are indeed substantial, they reflect an evolution rather than a breakpoint for the geoinformatics community: we are trying to apply established analysis techniques onto massive data. The emergence of social media however is posing a different type of Big Data challenge to the geoinformatics community: not only are the datasets large, but their analysis is also novel, and calls for a hybrid mix of spatial and social analysis. The geographical content of social media comprises coordinates from which the contributions originate, or of references to specific locations. At the same time, information on the underlying social structure of the user community can be derived by studying the interactions between users (e.g. formed as they respond to, or follow, other users), and this information can provide additional context to the data. The analysis of both the geographical and social content of social media feeds is referred to as geosocial analysis. It is emerging as a new research frontier for the geoinformatics and social sciences communities, and through its volume and richness opens new avenues and research challenges for understanding dynamic events and situations around the world.

Cities provide homes for over half of the world’s population, and this proportion is expected to ... more Cities provide homes for over half of the world’s population, and this proportion is expected to increase throughout the next century. The growth of cities raises many questions and challenges for urban planning including which cities and regions are most likely to grow, what the pattern of urban growth will be, and how the existing infrastructure will cope with such growth. One way to explore these types of questions is through the use of multi-agent systems (MAS) that are capable of modeling how individuals interact and how structures emerge through such interactions, in terms of both the social and physical environment of cities. Within this chapter, the authors focus on how MAS can lead to insights into urban problems and aid urban planning from the bottom up. They review MAS models that explore the growth of cities and regions, models that explore land-use patterns resulting from such growth along with the rise of slums. Furthermore, the authors demonstrate how MAS models can be used to model transportation and the changing demographics of cities. Through these examples the authors also demonstrate how this style of modeling can give insights into such issues that cannot be gleamed from other modeling methodologies. The chapter concludes with challenges and future research directions of MAS models with respect to capturing the dynamics of human behavior in urban planning.

The emergence of social media has provided the public with an effective and irrepressible real-ti... more The emergence of social media has provided the public with an effective and irrepressible real-time mechanism to broadcast information. The great popularity of platforms such as twitter and YouTube, and the substantial amount of content that is communicated through them are making social media an essential component of open-source intelligence. The information communicated through such feeds conveys the interests and opinions of individuals, and reveals links and the complex structure of social networks. However, this information is only partially exploited if one does not consider its geographical aspect. Indeed, social media feeds more often than not have some sort of geographic content, as they may communicate the location from where a particular report is contributed, the geolocation of an image, or they may refer to a specific sociocultural hotspot. By harvesting this geographic content from social media feeds we can transfer the extracted knowledge from the amorphous cyberspace to the geographic space, and gain a unique understanding of the human lansdscape, its structure and organization, and its evolution over time. This newfound opportunity signals the emergence of open-source geospatial intelligence, whereby social media contributions can be analyzed and mined to gain unparalleled situational awareness. In this paper we showcase a number of sample applications that highlight the capabilities of harvesting geospatial intelligence from social media feeds, focusing particularly on twitter as a representative data source.

The Internet and its World Wide Web (WWW) have revolutionised many aspects of our daily lives fro... more The Internet and its World Wide Web (WWW) have revolutionised many aspects of our daily lives from how we access and retrieve information to how we communicate with friends and peers. Over the past two decades, the Web has evolved from a system aimed primarily towards data access to a medium that fosters information contribution and interaction within large, globally distributed communities. Just as the Web evolved, so too did Web-based GeoComputation (GC), which we refer to here as the Geographic World Wide Web or the GeoWeb for short. Whereas the generation and viewing of geographical information was initially limited to the purview of specialists and dedicated workstations, it has now become of interest to the general public and is accessed using a variety of devices such as GPS-enabled smartphones and tablets. Accordingly, in order to meet the needs of this expanded constituency, the GeoWeb has evolved from displaying static maps to a dynamic environment where diverse datasets can be accessed, exchanged and mashed together. Within this chapter, we trace this evolution and corresponding paradigm shifts within the GeoWeb with a particular focus on Web 2.0 technologies. Furthermore, we explore the role of the crowd in consuming and producing geographical information and how this is influencing GeoWeb developments. Specifically, we are interested in how location provides a means to index and access information over the Internet. Next, we discuss the role of Digital Earth and virtual world paradigms for storing, manipulating and displaying geographical information in an immersive environment. We then discuss how GIS software is changing towards GIS services and the rise in location-based services (LBS) and lightweight software applications (so-called apps). Finally, we conclude with a summary of this chapter and discuss how the GeoWeb might evolve with the rise in massive amounts of locational data being generated through social media and the growth of augmented reality (AR) applications tied to specific locations.

The application of agent-based modelling (ABM) to simulating dynamics within geographical systems... more The application of agent-based modelling (ABM) to simulating dynamics within geographical systems has seen a considerable increase over the last decade. ABM allows the disaggregation of systems into individual components that can potentially have their own characteristics and rule sets. This is a powerful paradigm that can be exploited through simulation to further our knowledge of the workings of geographical systems.

Within this chapter we focus on the integration of Geographical Information System (GIS) and Agen... more Within this chapter we focus on the integration of Geographical Information System (GIS) and Agent-based modelling (ABM) and review a selection of toolkits which allow for such integration. Moreover, we identify current capabilities of modelling within a GIS and methods of coupling and integrating GIS with agent-based models.

This chapter guides the reader to the material in this book. It begins by outlining the meaning a... more This chapter guides the reader to the material in this book. It begins by outlining the meaning and rationale for agent-based models/modelling (ABM), focusing on their history, how they evolved and how they sit within the broader context of modelling and simulation for geographical systems.

Advanced Geosimulation Models, 2011

Abstract: There is a growing interest in relating agent-based models to real-world locations by c... more Abstract: There is a growing interest in relating agent-based models to real-world locations by combining them with geographical information systems (GIS) which can be seen with the increase of geosimulation models in recent years. This coincides with the proliferation of digital data both in the two and three dimensions allowing one to construct detailed and extensive feature-rich and highly visual 3D city models.

This chapter provides some general reflections on the development of ABM in terms of the applicat... more This chapter provides some general reflections on the development of ABM in terms of the applications presented in this book. We focus on the dilemma of building rich models that tend to move the field from strong to weaker styles of prediction, raising issues of validation in environments of high diversity and variability. We argue that we need to make progress on these issues while at the same time extending our models to deal with cross-cutting issues that define societal grand challenges such as climate change, energy depletion, aging, migration, security, and a host of other global issues. We pick up various pointers to how we might best use models in a policy context that have been introduced in many of the applications presented within this book and we argue that in the future, we need to develop a more robust approach to how we might use such models in policy making and planning.

Cities play a crucial role in our lives, providing habitats for over half of the world's populati... more Cities play a crucial role in our lives, providing habitats for over half of the world's population. However, understanding such systems is extremely complex as they are composed of many parts, with many dynamically changing parameters and large numbers of discrete actors interacting within space.

M Mo od de el li in ng g a an nd d S Si im mu ul la at ti in ng g U Ur rb ba an n P Pr ro oc ce e... more M Mo od de el li in ng g a an nd d S Si im mu ul la at ti in ng g U Ur rb ba an n P Pr ro oc ce es ss se es s K Ko oc ch h, , A An nd dr re ea as s a an nd d M Ma an nd dl l, , P Pe et te er r ( (e ed ds s. .) ) L Li it t V Ve er rl la ag g: : W Wi ie en n, , 2 20 01 11 1 I IS SB BN N 9 97 78 83 36 64 43 35 50 00 03 36 66 6 ( (p pb b) ) Reviewed by A An nd dr re ew w C Cr ro oo ok ks s George Mason University Urban systems are constantly evolving and examining how they are affected by climate change or social restructuring is a non-trivial task. The responses can be manifested in land Review of Koch, Andreas and Mandl, Peter (eds.): Modeling an...

A framework for geodesign: changing geography by design by C Steinitz; ESRI Press, Redlands, CA, ... more A framework for geodesign: changing geography by design by C Steinitz; ESRI Press, Redlands, CA, 2012, 224 pages, $79.95 paper (£66.50), ISBN 987 1589483330

Proceedings of the Annual Modeling and Simulation Conference, 2023

As the level of complexity of agent-based models grows, so does the complexity of their developme... more As the level of complexity of agent-based models grows, so does the complexity of their development. At the time of writing, the discipline of agent-based modeling does not have an established standard for the software development process to support this increasing complexity. We hope to address this need by introducing our variation of the Spiral model of software development and demonstrating an application of this process through a simple use case. We argue that the Spiral model of software development is a flexible approach that can be tailored to fit the needs of almost any project type. Further, our agent-based modeling variation of the Spiral model is an effective approach that is capable of guiding and supporting large interdisciplinary teams participating in a project, while providing sufficient flexibility to account for the uncertainty in the requirements that may arise during the development period.

Proceedings of the Annual Modeling and Simulation Conference , 2023

The COVID-19 pandemic has clearly highlighted the importance of supply chains to the function of ... more The COVID-19 pandemic has clearly highlighted the importance of supply chains to the function of the world economy. Moreover, the global nature of most modern supply chains along with their complexity has left them vulnerable to a wide-ranging set of disruptive scenarios. This increase in complexity has also led to a corresponding increase in disruptions to supply chains from criminal networks. In this paper, we demonstrate how a generic pharmaceutical supply chain network can be successfully modeled using discrete event simulation. We outline how disruptions by criminal networks and mitigation strategies to counter them can be effectively incorporated into the same model. Finally, we show how optimization techniques, such as evolutionary computation, can be used to not only identify worst-case disruptions and find mitigations for them, but also be used to identify mitigation strategies that are effective against a diverse set of damaging disruption scenarios.

roceedings of the 12th International Conference on Geographic Information Science, 2023

People's opinions are one of the defining factors that turn spaces into meaningful places. Online... more People's opinions are one of the defining factors that turn spaces into meaningful places. Online platforms such as Yelp allow users to publish their reviews on businesses. To understand reviewers' opinion formation processes and the emergent patterns of published opinions, we utilize natural language processing (NLP) techniques especially that of aspect-based sentiment analysis methods (a deep learning approach) on a geographically explicit Yelp dataset to extract and categorize reviewers' opinion aspects on places within urban areas. Such data is then used as a basis to inform an agent-based model, where consumers' (i.e., agents') choices are based on their characteristics and preferences. The results show the emergent patterns of reviewers' opinions and the influence of these opinions on others. As such this work demonstrates how using deep learning techniques on geospatial data can help advance our understanding of place and cities more generally. 2012 ACM Subject Classification Computing methodologies → Natural language processing; Computing methodologies → Agent / discrete models; Social and professional topics → Geographic characteristics Keywords and phrases aspect-category sentiment analysis, consumer choice, agent-based modeling, online restaurant reviews

Proceedings of the 2023 International Conference of The Computational Social Science Society of the Americas, 2023

Over the last two decades, there has been a growth in the applications of geographically-explicit... more Over the last two decades, there has been a growth in the applications of geographically-explicit agent-based models. One thing such models have in common is the creation of synthetic populations to initialize the artificial worlds in which the agents inhabit. One challenge such models face is that it is often difficult to create reusable geographically-explicit synthetic populations with social networks. In this paper, we introduce a Python based method that generates a reusable geographically-explicit synthetic population dataset along with its social networks. In addition, we present a pipeline for using the population datasets for model initialization. With this pipeline, multiple spatial and temporal scales of geographically-explicit agent-based models are presented focusing on Western New York. Such models not only demonstrate the utility of our synthetic population on commuting patterns but also how social networks can impact the simulation of disease spread and vaccination uptake. By doing so, this pipeline could benefit any modeler wishing to reuse synthetic populations with realistic geographic locations and social networks.

Proceedings of the 2023 ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems,, 2023

Individual human location trajectory and check-in data have been the driving force for human mobi... more Individual human location trajectory and check-in data have been the driving force for human mobility research in recent years. However, existing human mobility datasets are very limited in size and representativeness. For example, one of the largest and most commonly used datasets of individual human location trajectories, GeoLife, captures fewer than two hundred individuals. To help fill this gap, this Data and Resources paper leverages an existing data generator based on fine-grained simulation of individual human patterns of life to produce large-scale trajectory, check-in, and social network data. In this simulation, individual human agents commute between their home and work locations, visit restaurants to eat, and visit recreational sites to meet friends. We provide large datasets of months of simulated trajectories for two example regions in the United States: San Francisco and New Orleans. In addition to making the datasets available, we also provide instructions on how the simulation can be used to regenerate data, thus allowing researchers to generate the data locally without downloading prohibitively large files.

Proceedings of the 2024 International Conference of the Computational Social Science Society of the Americas, 2024

In the United States, educational attainment and student retention in higher education are two of... more In the United States, educational attainment and student retention in higher education are two of the main focuses of higher education research. Institutions are constantly looking for ways to identify areas of improvement across different aspects of the student experience on university campuses. This paper combines Department of Education data over a 10 year period, U.S. Census data, and higher education theory on student retention, to build an agent-based model of student behavior. Furthermore we model student social interactions with their peers along with considering environmental components (e.g., urban vs. rural campuses) and institution personnel to explore the elements that increase the likelihood of student retention. Results suggest that both social interactions and environmental components make a difference in student retention. Suggesting that higher education institutions should consider new ways to accommodate learning needs that promote better student outcomes.

Proceedings of the 7th ACM SIGSPATIAL International Workshop on Geospatial Simulation, 2024

During the COVID-19 pandemic, social media become an important hub for public discussions on vacc... more During the COVID-19 pandemic, social media become an important hub for public discussions on vaccination. However, it is unclear how the rise of cyber space (i.e., social media) combined with traditional relational spaces (i.e., social circles), and physical space (i.e., spatial proximity) together affect the diffusion of vaccination opinions and produce different impacts on urban and rural population's vaccination uptake. This research builds an agent-based model utilizing the Mesa framework to simulate individuals' opinion dynamics towards COVID-19 vaccines, their vaccination uptake and the emergent vaccination rates at a macro level for New York State (NYS). By using a spatially explicit synthetic population, our model can accurately simulate the vaccination rates for NYS (mean absolute error=6.93) and for the majority of counties within it (81%). This research contributes to the modeling literature by simulating individuals vaccination behaviors which are important for disease spread and transmission studies. Our study extends geo-simulations into hybrid-space settings (i.e., physical, relational, and cyber spaces). CCS Concepts • Applied computing → Health informatics; • Information systems → Geographic information systems; • Computing methodologies → Agent / discrete models.

Proceedings of the 7th ACM SIGSPATIAL International Workshop on Geospatial Simulation, 2024

The COVID-19 pandemic has reshaped societies and brought to the forefront simulation as a tool to... more The COVID-19 pandemic has reshaped societies and brought to the forefront simulation as a tool to explore the spread of the diseases including that of agent-based modeling. Efforts have been made to ground these models on the world around us using synthetic populations that attempt to mimic the population at large. However, we would argue that many of these synthetic populations and therefore the models using them, miss the social connections which were paramount to the spread of the pandemic. Our argument being is that contagious diseases mainly spread through people interacting with each other and therefore the social connections need to be captured. To address this, we create a geographically-explicit synthetic population along with its social network for the Western New York (WNY) Area. This synthetic population is then used to build a framework to explore a hypothetical contagious disease inspired by various of COVID-19. We show simulation results from two scenarios utilizing this framework, which demonstrates the utility of our approach capturing the disease dynamics. As such we show how basic patterns of life along with interactions driven by social networks can lead to the emergence of disease outbreaks and pave the way for researchers to explore the next pandemic utilizing agent-based modeling with geographically explicit social networks.

ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2024

We demonstrate the Patterns of Life Simulation to create realistic simulations of human mobility ... more We demonstrate the Patterns of Life Simulation to create realistic simulations of human mobility in a city. This simulation has recently been used to generate massive amounts of trajectory and check-in data. Our demonstration focuses on using the simulation twofold: (1) using the graphical user interface (GUI), and (2) running the simulation headless by disabling the GUI for faster data generation. We further demonstrate how the Patterns of Life simulation can be used to simulate any region on Earth by using publicly available data from OpenStreetMap. Finally, we also demonstrate recent improvements to the scalability of the simulation allows simulating up to 100,000 individual agents for years of simulation time. During our demonstration, as well as offline using our guides on GitHub, participants will learn: (1) The theories of human behavior driving the Patters of Life simulation, (2) how to simulate to generate massive amounts of synthetic yet realistic trajectory data, (3) running the simulation for a region of interest chosen by participants using OSM data, (4) learn the scalability of the simulation and understand the properties of generated data, and (5) manage thousands of parallel simulation instances running concurrently.

Proceedings of the Annual Modeling and Simulation Conference , 2023

Forced migration of populations is a topic of increasingly national and international importance ... more Forced migration of populations is a topic of increasingly national and international importance due to security, international relations, and humanitarian considerations. Despite its importance, there has been a dearth of quantitative research to support modeling and simulation of this topic, thus hindering our ability to better understand this phenomenon. Motivated by this gap, this research leverages the recent availability of diverse set of data related to forced migration, including regime legitimacy, violence, human rights violations, conflict, socio-political mobilization, intervening opportunities, and social media. The purpose of this article is to explore the applicability and utility of open-source data in a system dynamics model to forecast population displacement, and to illustrate the benefits of using a system dynamics approach to modeling displaced population on a national and international scale. Our results suggest that this proposed approach can be used to understand such migration processes and simulate possible scenarios.

Proceedings of the Annual Modeling and Simulation Conference , 2023

2022 Computational Social Science Society of the Americas (CSS 2022) Annual Conference. , 2022

The use of fossil fuels is the primary source of greenhouse gas emissions but there are alternati... more The use of fossil fuels is the primary source of greenhouse gas emissions but there are alternatives to these especially in the form of biofuels, fuels derived from bioenergy crops. This paper aims to determine farmers' potential adoption rates of newly introduced bioenergy crops with a specific example of carinata in the state of Georgia. The determination is done using an agent-based modeling technique with two principal assumptions-farmers are profit maximizer and they are influenced by neighboring farmers. Two diffusion parameters (traditional and expansion) are followed along with two willingness (high and low) scenarios to switch at varying production economics to carinata and other prominent traditional field crops (cotton, peanuts, corn) in the study region. The paper finds that a contract prices around 9,9, 9,8 and $7 can be a viable option for encouraging farmers to adopt carinata in low, average, and high profit conditions, respectively. Expansion diffusion (that diffuses all over the geographical area), rather than centered to the few places like traditional diffusion at the early stage of adoption in conjunction with higher willingness conditions influences higher adoption rates in the short-term. As such, the model can be used to understand the behavioral economics of carinata in Georgia and beyond, as well as offering a potential tool to study similar bioenergy crops.

GeoSim '22: Proceedings of the 5th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, 2022

Mesa is an open-source agent-based modeling (ABM) framework implemented in the Python programming... more Mesa is an open-source agent-based modeling (ABM) framework implemented in the Python programming language, allowing users to build and visualize agent-based models. It has been used in a diverse range of application areas over the years ranging from biology to workforce dynamics. However, there has been no direct support for integrating geographical data from geographical information systems (GIS) into models created with Mesa. Users have had to rely on their own implementations to meet such needs. In this paper we present Mesa-Geo, a GIS extension for Mesa, which allows users to import, manipulate, visualise and export geographical data for ABM. We introduce the main components and functionalities of Mesa-Geo, followed by example applications utilizing geographical data which demonstrates Mesa-Geo's core functionalities and features common to agent-based models. Finally, we conclude with a discussion and outlook on future directions for Mesa-Geo. CCS CONCEPTS • Computing methodologies → Simulation tools; • Software and its engineering → Software libraries and repositories; • Information systems → Geographic information systems.

Proceedings of the 2022 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation, 2022

Disruption to supply chains can significantly influence the operation of the world economy and th... more Disruption to supply chains can significantly influence the operation of the world economy and this has been shown to permeate and affect a large majority of countries and their citizens. We present initial results from a model that explores the disruptions to supply chains by a criminal agent and possible mitigation strategies. We construct a model of a typical pharmaceutical manufacturing supply chain, which is implemented via discrete event simulation. The criminal agent optimizes its resource allocation to maximize disruption to the supply chain. Our findings show criminal agents can cause cascading damage and exploit vulnerabilities, which inherently exist within the supply chain itself. We also demonstrate how basic mitigation strategies can efficaciously alleviate this potential damage.

ICOSSAR 2022: 13th International Conference on Structural Safety and Reliability, 2022

The risk of flooding to urban communities is increasing significantly due to the effects of clima... more The risk of flooding to urban communities is increasing significantly due to the effects of climate change and socioeconomic development. Thus, a comprehensive understanding of the impact of urban growth on flood risk is an essential ingredient for adequate flood risk management. In addition, a life-cycle perspective may offer advantages to policymakers, developers, and homeowners in making future community development more resilient and attractive from both financial and social stances. In this study, we employ a Cellular Automata model to simulate urban expansion dynamics resulting from socioeconomic changes to a community. The urban growth projections are then coupled with floodplains for a set of flood hazard scenarios, using the City of Boulder, CO, USA as a testbed. The results from the urban growth simulations are subsequently used in a life-cycle analysis to show that estimates of flood risk to urban communities can be greatly improved by including drivers of city expansion, including socioeconomic incentives.

GeoSim'21: 4th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, 2021

With progressively increased people living in cities, and lately the global COVID-19 outbreak, hu... more With progressively increased people living in cities, and lately the global COVID-19 outbreak, human mobility within cities has changed. Coinciding with this change, is the recent uptake of the '15-Minute City' idea in urban planning around the world. One of the hallmarks of this idea is to create a high quality of life within a city via an acceptable travel distance (i.e., 15 minutes). However, a definitive benchmark for defining a '15-Minute City' has yet to be agreed upon due to the heterogeneous character of urban morphologies worldwide. To shed light on this issue, we develop an agent-based model named 'D-FMCities' utilizing realistic street networks and points-of-interest, in this instance the borough of Queens in New York City as a test case. Through our modeling we grow diverse communities from the bottom up and estimate the size of such local communities to delineate 15-minute cities. Our findings suggest that the model could be helpful to detect the flexibility of defining the extent of a '15-minute city' and consequently support uncovering the underlying factors that may affect its various definitions and diverse sizes throughout the world.

Proceedings of 2021 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation, 2021

Drone strikes have been ongoing and there is a debate about their benefits. One major question is... more Drone strikes have been ongoing and there is a debate about their benefits. One major question is what is their role with respect to radicalization. This paper presents a data-driven approach to explore the relationship between drone strikes in Pakistan and subsequent responses, often in the form of terrorist attacks carried out by those in the communities targeted by these counterterrorism measures. Our analysis of news reports which discussed drone strikes and radicalization suggests that government-sanctioned drone strikes in Pakistan appear to drive terrorist events with a distributed lag that can be determined analytically. We then utilize these news reports to inform and calibrate an agent-based model which is grounded in radicalization and opinion dynamics theory. In doing so, we were able to simulate terrorist attacks that approximated the rate and magnitude observed in Pakistan from 2007 through 2018. We argue that this research effort advances the field of radicalization and lays the foundation for further work in the area of data-driven modeling and kinetic actions.

International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, 2021

Agent-based geospatial simulations have become very popular and widely used in examining the soci... more Agent-based geospatial simulations have become very popular and widely used in examining the social and cultural characteristics of populations. Well-known toolkits such as NetLogo or MASON generally have scalability limitations, especially when the model and underlying spatial infrastructure become complex. This paper presents a framework for simulating large-scale agent-based geospatial systems by integrating the multi-agent systems toolkit JADE with the MASON agent-based modeling framework and its GIS extension, GeoMASON. The proposed Java-based framework can simulate large areas with hundreds of thousands of agents. It allows for the studying the evolution of a population and its environment over time. Such a framework provides the essential first steps for scalable model execution without sacrificing the model generality.

Geosim ’20: 3rd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, 2020

Social connections between people influence how they behave and where they go; however, such netw... more Social connections between people influence how they behave and where they go; however, such networks are rarely incorporated in agent-based models of disaster. To address this, we introduce a novel synthetic population method which specifically creates social relationships. This synthetic population is then used to instantiate a geographically explicit agent-based model for the New York megacity region which captures pre-and post-disaster behaviors. We demonstrate not only how social networks can be incorporated into models of disaster but also how such networks can impact decision making, opening up a variety of new application areas where network structures matter in urban settings. CCS CONCEPTS • Computing methodologies → Modeling and simulation; Agent /discrete models.

SIGSPATIAL Special, 2020

Human mobility and social networks have received considerable attention from researchers in recen... more Human mobility and social networks have received considerable attention from researchers in recent years. What has been sorely missing is a comprehensive data set that not only addresses geometric movement patterns derived from trajectories, but also provides social networks and causal links as to why movement happens in the first place. To some extent, this challenge is addressed by studying location-based social networks (LBSNs). However, the scope of real-world LBSN data sets is constrained by privacy concerns, a lack of authoritative ground-truth, their sparsity, and small size. To overcome these issues we have infused a novel geographically explicit agent-based simulation framework to simulate human behavior and to create synthetic but realistic LBSN data based on human patterns-of-life (i.e., a geo-social simulation). Such data not only captures the location of users over time, but also their motivation, and interactions via temporal social networks. We have open sourced our framework and released a set of large data sets for the SIGSPATIAL community. In order to showcase the versatility of our simulation framework, we added disease a model that simulates an outbreak and allows us to test different policy measures such as implementing mandatory mask use and various social distancing measures. The produced data sets are massive and allow us to capture 100% of the (simulated) population over time without any data uncertainty, privacy-related concerns, or incompleteness. It allows researchers to see the (simulated) world through the lens of an omniscient entity having perfect data.

SIGSPATIAL Special, 11(3): 20-22, 2019

Space has long been acknowledged by researchers as a fundamental constraint which shapes our worl... more Space has long been acknowledged by researchers as a fundamental constraint which shapes our world. As technological changes have transformed the very concept of distance, the relative location and connectivity of geospatial phenomena have remained stubbornly significant in how systems function. At the same time, however, technology has allowed us to begin to bring tools like geospatial simulation to bear on our understanding of how such systems work. While previous generations of scientists and practitioners were unable to gather spatial data or to incorporate it into models at any meaningful scale, new methodologies and data sources are becoming increasingly available to researchers, developers, users, and practitioners. This flourishing of different approaches is occurring simultaneously across many fields, and at every point in the research process allowing for new opportunities for geospatial simulation.

Centre for Advanced Spatial Analysis (University College London): Working Paper 214, 2019

This paper charts the progress made since agent-based models (ABMs) of geographical systems emerg... more This paper charts the progress made since agent-based models (ABMs) of geographical systems emerged from more aggregative approaches to spatial modeling in the early 1990s. We first set the context by noting that ABM explicitly represent the spatial system by individual objects, usually people in the social science domain, with behaviors that we simulate here mainly as decisions about location and movement. Key issues pertaining to the way in which temporal dynamics characterize these models are noted and we then pick up the challenges from the review of this field conducted by Crooks, et al. (2008) some 12 years ago which was also published as a CASA working paper. We then define key issues from this past review as pertaining to a series of questions involving: the rationale for modeling; the way in which theory guides models and vice versa; how models can be compared; questions of model replication, experiment, verification and validation; how dynamics are incorporated in models; how agent behaviors can be simulated; how such ABMs are communicated and disseminated; and finally the data challenges that still dominate the field. This takes us to the current challenges emerging from this discussion. Big data, the way it is generated, and its relevance for ABM is explored with some important caveats as to the relevance of such data for these models, the way these models might be integrated with one another and with different genera of models are noted, while new ways of testing such models through ensemble forecasting and data assimilation are described. The notion about how we model human behaviors through agents learning in complex environment is presented and this then suggests that ABM still have enormous promise for effective simulations of how spatial systems evolve and change.

In this paper we analyse the street network of London both in its primary and dual representation... more In this paper we analyse the street network of London both in its primary and dual representation. To understand its properties, we consider three idealised models based on a grid, a static random planar graph and a growing random planar graph. Comparing the models and the street network, we find that the streets of London form a self-organising system whose growth is characterised by a strict interaction between the metrical and informational space. In particular, a principle of least effort appears to create a balance between the physical and the mental effort required to navigate the city.

The agent-based modelling (ABM) paradigm provides a mechanism for understanding the effects of in... more The agent-based modelling (ABM) paradigm provides a mechanism for understanding the effects of interactions of individuals and through such interactions emergent structures develop, both in the social and physical environment of cities. This paper explores how through the use of ABM, and its linkage with complexity theory, allows one to create agent-based models for the studying cities from the bottom-up. Specifically the paper focuses on segregation and land-use change. Furthermore, it will highlight the growing interest between geographical information systems (GIS) and ABM. This linkage is allowing modellers to create spatially explicit agent-based models, thus relating agents to actual geographical places. This approach allows one to explore the link between socio-economic geography of the city and its built physical form, and can support decision-making regarding interventions within the social and physical environment.

There is a growing interest in relating agent-based models to realworld locations by combining th... more There is a growing interest in relating agent-based models to realworld locations by combining them with geographical information systems (GIS) which can be seen with the proliferation of geosimulation models in recent years. This coincides with the proliferation of digital data both in the two and three dimensions allowing one to construct detailed and extensive feature rich and highly visual 3D city models. This paper explores some of these developments in relation to our own initial work on building 3D geospatial agent-based models of urban systems and the technologies that allow for such models to be created. Furthermore, we highlight some techniques for the creation of 3D agent-based models and stress that such models are not a substitute to good models.

Scholars and urban planners have suggested that the key characteristic of leading world cities is... more Scholars and urban planners have suggested that the key characteristic of leading world cities is that they attract the best and brightest minds. As home to the creative classes, which consist of professionals working in knowledge-based industries, they are the bedrocks of prosperity and drivers of innovation. They not only provide unrivaled educational and professional opportunities, but also the best entertainment facilities such as art galleries, theaters and restaurants. Both through hard and soft infrastructure, residents of these cities enjoy seamless connectivity which fosters human creativity. When combined with population density, socio-economic diversity and societal tolerance, the elevated interaction intensity diffuses creativity and boosts economic productivity. However, rapidly urbanizing cities in the developing world are struggling to maintain adequate service delivery standards. The form and function of many cities are increasingly marred by congestion, sprawl and socioeconomic segregation, preventing them from experiencing expected productivity gains associated with urbanization. We operationalize these insights by creating a stylized agent-based model of a theoretical city, inspired by social complexity theory and the new urban literature. A virtual environment is designed where heterogeneous and independent decision-making agents interact under various policy scenarios, such as greater urban transportation investments and altered land-use regulations. By creating typical urban conditions, we conclude that the combination of mixed land-use, improved access to urban mobility and high societal tolerance levels foster creativity led urban economic growth.

The built environment is a significant factor in many urban processes, yet direct measures of bui... more The built environment is a significant factor in many urban processes, yet direct measures of built form are seldom used in geographical studies. Representation and analysis of urban form and function could provide new insights and improve the evidence base for research. So far progress has been slow due to limited data availability, computational demands, and a lack of methods to integrate built environment data with aggregate geographical analysis.

Agent-based modelling (ABM) is becoming the dominant paradigm in social simulation due primarily ... more Agent-based modelling (ABM) is becoming the dominant paradigm in social simulation due primarily to a worldview that suggests that complex systems emerge from the bottom-up, are highly decentralised, and are composed of a multitude of heterogeneous objects called agents. These agents act with some purpose and their interaction, usually through time and space, generates emergent order, often at higher levels than those at which such agents operate. ABM however raises as many challenges as it seeks to resolve. It is the purpose of this paper to catalogue these challenges and to illustrate them using three somewhat different agent-based models applied to city systems. The seven challenges we pose involve: the purpose for which the model is built, the extent to which the model is rooted in independent theory, the extent to which the model can be replicated, the ways the model might be verified, calibrated and validated, the way model dynamics are represented in terms of agent interactions, the extent to which the model is operational, and the way the model can be communicated and shared with others. Once catalogued, we then illustrate these challenges with a pedestrian model for emergency evacuation in central London, a hypothetical model of residential segregation model tuned to London data, and an agent-based residential location model, for Greater London. The ambiguities posed by this new style of modelling are drawn out as conclusions, and the relative arbitrariness of such modelling highlighted.

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modell... more The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.

Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded.

Cities are faced with many problems such as urban sprawl, congestion, and segregation. They are a... more Cities are faced with many problems such as urban sprawl, congestion, and segregation. They are also constantly changing. Computer modelling is becoming an increasingly important tool when examining how cities operate. Agent based models (ABM) allow for the testing of different hypotheses and theories for urban change, thus leading to a greater understanding of how cities work. This paper presents how ABMs can be developed by their integration with Geographical Information System (GIS).

Executive Summary The term'mash-up'refers to websites that weave data from different sources into... more Executive Summary The term'mash-up'refers to websites that weave data from different sources into new Web services. The key to a successful Web service is to gather and use large datasets and harness the scale of the Internet through what is known as network effects. This means that data sources are just as important as the software that'mashes' them, and one of the most profound pieces of data that a user has at any one time is his or her location.

Centre for Advanced Spatial Analysis (University College London): Working Paper 123, 2007

The use of simulation/modelling systems can simplify the implementation of agent-based models. Re... more The use of simulation/modelling systems can simplify the implementation of agent-based models. Repast is one of the few simulation/modelling software systems that supports the integration of geospatial data especially that of vector-based geometries. This paper provides details about Repast specifically an overview, including its different development languages available to develop agent-based models.

GIM International, 2018

Over one billion people currently live in slums (informal settlements) with populations worldwide... more Over one billion people currently live in slums (informal settlements) with populations worldwide increasing; this number is only expected to grow in the coming decades. These communities are often recognized as the most vulnerable groups in society. In an effort to better address the plight of slum dwellers (e.g. the provision of better infrastructure and services) and to develop more effective and efficient policies, better information on slums needs to be collected and slum populations monitored. Five-step process for addressing the problem of slums We propose a five-step process for addressing this problem (Define, Data, Map, Analyze and Model).

Abstract. This paper describes a stylized model of internally displaced person (IDP) dynamics in ... more Abstract. This paper describes a stylized model of internally displaced person (IDP) dynamics in East Africa. Displaced people often require support from national governments, international agencies or major non-governmental organizations. Anticipating the timing and magnitude of displacement events, as well as the likely locations to which displaced people will move would be of great interest to the various organizations tasked with managing such events. The paper examines three alternative modeling frameworks based on a pruned ...

The Computational Social Science Society of America Conference, 2011

Abstract. This paper describes a preliminary, lightweight and robust method for simulating vegeta... more Abstract. This paper describes a preliminary, lightweight and robust method for simulating vegetation growth that has basic validity in the face of remotely sensed vegetation data while being simple enough to retain conceptual and computational tractability when it is incorporated into a large agent-based model of human subsistence, conflict, and displacement in East Africa. The sub-model predicts daily vegetation values for 2.5 million 1km2 land grid cells using remotely sensed monthly rainfall data. It has been informally ...

This paper describes a stylized model of internally displaced person (IDP) dynamics in East Afric... more This paper describes a stylized model of internally displaced person (IDP) dynamics in East Africa. Displaced people often require support from national governments, international agencies or major non-governmental organizations. Anticipating the timing and magnitude of displacement events, as well as the likely locations to which displaced people will move would be of great interest to the various organizations tasked with managing such events. The paper examines three alternative modeling frameworks based on a pruned spatial interaction model, a local interaction model, and a hybrid of these two approaches. Each of the pure approaches is found to have limitations that can be overcome by adopting the hybrid approach.

The study of slums as social and physical constructs: challenges and emerging research opportunities

over 1 billion people currently live in slums, with the number of slum dwellers only expected to ... more over 1 billion people currently live in slums, with the number of slum dwellers only expected to grow in the coming decades. the vast majority of slums are located in and around urban centres in the less economically developed countries, which are also experiencing greater rates of urbanization compared with more developed countries. this rapid rate of urbanization is cause for significant concern given that many of these countries often lack the ability to provide the infrastructure (e.g., roads and affordable housing) and basic services (e.g., water and sanitation) to provide adequately for the increasing influx of people into cities. While research on slums has been ongoing, such work has mainly focused on one of three constructs: exploring the socio-economic and policy issues; exploring the physical characteristics; and, lastly, those modelling slums. this paper reviews these lines of research and argues that while each is valuable, there is a need for a more holistic approach for studying slums to truly understand them. By synthesizing the social and physical constructs, this paper provides a more holistic synthesis of the problem, which can potentially lead to a deeper understanding and, consequently, better approaches for tackling the challenge of slums at the local, national and regional scales.

Socio-Cultural Dynamics and Global Security (C. Tucker and R. Tomes, editors), 2013

GIScience 2012 (short paper), 2012

In this paper we focus on the spatiotemporal content of twitter feeds in order to assess their us... more In this paper we focus on the spatiotemporal content of twitter feeds in order to assess their use as a hybrid form of a sensor network to monitor evolving events. Our objective is to investigate how social media contributions can be utilized to study the spatiotemporal evolution of dynamic sociocultural events. Towards this goal we use as a representative case the events of the Occupy Wall Street (OWS) movement in New York City, NY, on the International Day of Action of November 17th, 2011. We use twitter as a representative example to harvest social media for our study. We collected geolocated tweets during that day, making reference to the Occupy Wall Street movement (e.g. through its associated hashtags and usernames, such as #ows) and analyze them to investigate how well they capture that day’s activities.

Environment and Planning B: Planning and Design, 2009

Journal of Artificial Societies and Social Simulation, 2015

ABSTRACT

Social media contributions are manifestations of humans acting as sensors, participating in activ... more Social media contributions are manifestations of humans acting as sensors, participating in activities, reacting to events, and reporting issues that are considered important. Harvesting this information offers a unique opportunity to monitor the human landscape, and gain unparalleled situational awareness, especially as it relates to sociocultural dynamics. However, this requires the emergence of a novel GeoSocial analysis paradigm. Towards this goal, in this paper we present a framework for collaborative GeoSocial analysis, which is designed around data harvesting from social media feeds (starting with twitter and flickr) and the concept of a collaborative GeoSocial Analysis Workbench (G- SAW). We present key concepts of this framework, and early test implementation results in order to demonstrate the potential of the G-SAW framework for enhanced situational awareness.

This unique book brings together a comprehensive set of papers on the background, theory, technic... more This unique book brings together a comprehensive set of papers on the background, theory, technical issues and applications of agent-based modelling (ABM) within geographical systems. This collection of papers is an invaluable reference point for the experienced agent-based modeller as well those new to the area. Specific geographical issues such as handling scale and space are dealt with as well as practical advice from leading experts about designing and creating ABMs, handling complexity, visualising and validating ...

2013 Winter Simulations Conference (WSC), 2013

The displacement of people in times of crisis represents a challenge for humanitarian assistance ... more The displacement of people in times of crisis represents a challenge for humanitarian assistance and disaster relief and stakeholder agencies. Major challenges include providing adequate security and medical facilities to displaced people. Within this paper, we develop a spatially explicit multi-agent system model that explores the spread of cholera in the Dadaab refugee camps, Kenya. A common characteristic of these camps is poor sanitation and housing conditions which contribute to frequent outbreaks of cholera. We model the spread of cholera by explicitly representing the interaction between humans (host) and their environment, and the spread of the epidemic. The results from the model show that the spread of cholera grows radially from contaminated water sources and can have an impact on service provision. Agents' social behavior and movements contribute to the spread of cholera to other camps where water sources were relatively safe.

Social Science Computer Review, 2009

We first develop the network paradigm that is currently dominating the way we think about the int... more We first develop the network paradigm that is currently dominating the way we think about the internet and introduce varieties of social networking that are being fashioned in interactive web environments. This serves to ground our arguments about Web 2.0 technologies. These constitute ways in which users of web-based services can take on the role of producers as well as consumers of information that derive from such services with sharing becoming a dominant mode of adding value to such data. These developments are growing Web 2.0 from the ground up, enabling users to derive hitherto unknown, hidden and even new patterns and correlations in data that imply various kinds of social networking. We define crowdsourcing and crowdcasting as essential ways in which large groups of users come together to create data and to add value by sharing. This is highly applicable to new forms of mapping. We begin by noting that maps have become important services on the internet with nonproprietary services such as Google Maps being ways in which users can fashion their own functionality. We review various top-down and bottom-up strategies and then present our own contributions in the form of GMapCreator that lets users fashion new maps using Google Maps as a base. We have extended this into an archive of pointers to maps created by this software, which is called MapTube, and we demonstrate how it can be used in a variety of contexts to share map information, to put existing maps into a form that can be shared, and to create new maps from the bottom up using a combination of crowdcasting, crowdsourcing and traditional broadcasting. We conclude by arguing that these developments define a neogeography which is essentially 'mapping for the masses'.

In this article, we explore the concepts and applications of Web 2.0 through the new media of Neo... more In this article, we explore the concepts and applications of Web 2.0 through the new media of NeoGeography and its impact on how we collect, interact and search for spatial information. We argue that location and space are becoming increasingly important in the information technology revolution. To this end, we present a series of software tools which we have designed to facilitate the non-expert user to develop online visualisations which are essentially map-based. These are based on Google Map Creator, which can produce any number of thematic maps which can be overlaid on Google Maps. We then introduce MapTube, a technology to generate an archive of shared maps, before introducing Google Earth Creator, Image Cutter and PhotoOverlay Creator. All these tools allow users to display and share information over the web. Finally, we present how Second Life has the potential to combine all aspects of Web 2.0, visualisation and NeoGeography in a single multi-user three-dimensional collaborative environment.

Abstract. The displacement of people in times of crises represents a challenge for humanitarian a... more Abstract. The displacement of people in times of crises represents a challenge for humanitarian agencies. This challenge is especially acute within developing countries, which home the majority of displaced people. Within this paper, we will demonstrate a spatially explicit agent based model that explores the spread of cholera in the Dadaab refugee camps. Poor sanitation and housing conditions contribute to frequent incidents of cholera outbreaks. We model the spread of cholera by explicitly representing the ...

Journal of the American Planning Association, 2009

Ever since computers were first developed in the mid 20 th century, planners saw an immediate use... more Ever since computers were first developed in the mid 20 th century, planners saw an immediate use for them in not only organizing large quantities of data about the city but also in the analysis of that data, the construction of simulation models of how cities functioned, and in forecasting the future form of cities. All these ideas were put in place in the 1950s and 1960s mainly in North America and there were even moves to automate the city planning process itself by formulating models that could generate idealised plans based on data ...

casa.ucl.ac.uk, 2008

EcoHealth, 2016

As the Ebola outbreak in West Africa wanes, it is time for the international scientific community... more As the Ebola outbreak in West Africa wanes, it is time for the international scientific community to reflect on how to improve the detection of and coordinated response to future epidemics. Our interdisciplinary team identified key lessons learned from the Ebola outbreak that can be clustered into three areas: environmental conditions related to early warning systems, host characteristics related to public health, and agent issues that can be addressed through the laboratory sciences. In particular, we need to increase zoonotic surveillance activities, implement more effective ecological health interventions, expand prediction modeling, support medical and public health systems in order to improve local and international responses to epidemics, improve risk communication, better understand the role of social media in outbreak awareness and response, produce better diagnostic tools, create better therapeutic medications, and design better vaccines. This list highlights research priorities and policy actions the global community can take now to be better prepared for future emerging infectious disease outbreaks that threaten global public health and security. Paul L. Delamater, Jhumka Gupta, , Mariaelena Pierobon, Katherine E. Rowan, J. Reid Schwebach, Padmanabhan Seshaiyer ... ; ; ; ; ; >