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Currently Associate Professor of Anthropology, University of Colorado Colorado Springs. I took my first modelling class in Repast with Dr. Mark Lake as part of my M. Sc. at UCL. After a workshop with Dr. Luke Premo and Dr. Anne Kandler, I moved to NetLogo and haven’t looked back.
Find our recent textbook, Agent-based modeling for Archaeology: Simulating the Complexity of Societies here: https://santafeinstitute.github.io/ABMA/
General Question:
Without Central Control is self organization possible?
Specific Case:
Considering the seemingly preplanned, densely aggregated communities of the prehistoric Puebloan Southwest, is it possible that without centralized authority (control), that patches of low-density communities dispersed in a bounded landscape could quickly self-organize and construct preplanned, highly organized, prehistoric villages/towns?
I am strongly interested in ecological modeling and complex system and truly enjoyed working with a variety of tools to uncover patterns in empirical data and explore their ecological and evolutionary consequences. My primary research is to conduct research in the field of ‘ecological complexity’, including the development of appropriate descriptive measure to quantify the structural, spatial and temporal complexity of ecosystem and the identification of the mechanism that generate this complexity, through modeling and field studies.
Currently investigated is how biological characteristics of invasive species (dispersal strategies and demographic processes) interact with abiotic variables and resource distribution to determine establishment success and spread in a complex heterogeneous environment (Individual based modelling integrated with GIS technologies).
My broad research interests are in human-environmental interactions and land-use change. Specifically, I am interested in how people make land-use decisions, how those decisions modify the functioning of natural systems, and how those modifications feedback on human well-being, livelihoods, and subsequent land-use decisions. All of my research begins with a complex systems background with the aim of understanding the dynamics of human-environment interactions and their consequences for environmental and economic sustainability. Agent-based modeling is my primary tool of choice to understand human-environment interactions, but I also frequently use other land change modeling approaches (e.g., cellular automata, system dynamics, econometrics), spatial statistics, and GIS. I also have expertise in synthesis methods (e.g., meta-analysis) for bringing together leveraging disparate forms of social and environmental data to understand how specific cases (i.e., local) of land-use change contribute to and/or differ from broader-scale (i.e. regional or global) patterns of human-environment interactions and land change outcomes.
Muhammad Mobeen is doing his PhD from the University of Hamburg, Hamburg, Germany. Previously. he has earned his M.Phil. in Geography from Department of Earth Sciences, University of Sargodha. He received M.Sc Geography (Distinction) & MS.Ed. from the University of the Punjab Lahore. He is an MA in Political Science and PGD in International Affairs as a Private candidate from Punjab University. He started his professional career in Aug-2007 as an Assistant Meteorologist (BS-16), Pakistan Meteorological Department, and then in Aug- 2008 he moved as a lecturer in Geography (BS-17) at Islamabad College for Boys G-6/3 Islamabad. He has been working as Lecturer in Geography (BS-18) at the Department of Earth Sciences, the University of Sargodha since 2010 and now he is on study leave for his PhD on the HEC cum the DAAD funding. His research interests are Climate Change, and water conflicts.
Climate Change, Water conflict modeling, ABM, Netlogo, GIS, Remote Sensing,
I am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).
Modeling land use change from smallholder agricultural intensification
Agricultural expansion in the rural tropics brings much needed economic and social development in developing countries. On the other hand, agricultural development can result in the clearing of biologically-diverse and carbon-rich forests. To achieve both development and conservation objectives, many government policies and initiatives support agricultural intensification, especially in smallholdings, as a way to increase crop production without expanding farmlands. However, little is understood regarding how different smallholders might respond to such investments for yield intensification. It is also unclear what factors might influence a smallholder’s land-use decision making process. In this proposed research, I will use a bottom-up approach to evaluate whether investments in yield intensification for smallholder farmers would really translate to sustainable land use in Indonesia. I will do so by combining socioeconomic and GIS data in an agent-based model (Land-Use Dynamic Simulator multi-agent simulation model). The outputs of my research will provide decision makers with new and contextualized information to assist them in designing agricultural policies to suit varying socioeconomic, geographic and environmental contexts.
I am a geographer interested in exploring tourism system dynamics and assessing tourism’s role in environmental sustainability using agent-based modelling (ABM). My current work focus is on human complex systems interactions with the environment and on the application of tools (such as scenario analysis, network analysis and ABM) to explore topics systems adaptation, vulnerability and resilience to global change. I am also interested in looking into my PhD future research directions which pointed the potential of Big Data, social media and Volunteer Geographical Information to increase destination awareness.
I have extensive experience in GIS, quantitative and qualitative methods of research. My master thesis assessed the potential for automatic feature extraction from QuickBird imagery for municipal management purposes. During my PhD I have published and submitted several scientific papers in ISI indexed journals. I have a good research network in Portugal and I integrate an international research network on the topic “ABM meets tourism”. I am a collaborator in a recently awarded USA NCRCRD grant project “Using Agent Based Modelling to Understand and Enhance Rural Tourism Industry Collaboration” and applied for NSF funding with the project “Understanding and Enhancing the Resilience of Recreation and Tourism Dependent Communities in the Gulf”.
As a data scientist, I employ a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I also apply Science and Technology Studies lenses to my modeling processes in order to see potential ways to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling: teaching mapping and modeling skills, collaboratively building data representations and models, and analyzing and synthesizing community-held data as appropriate. At the same time, I look for ways to create space for qualitative and other forms of knowledge to reside alongside quantitative analysis, using mixed and integrative methods.
Recent projects include: 1) Studying Californian forest dynamics using Bayesian statistical models and object-based image analysis (datasets included forest inventories and historical aerial photographs); 2) Indigenous mapping and community-based modeling of agro-pastoral systems in rural Zimbabwe (methods included GPS/GIS, agent-based modeling and social network analysis); 3) Supporting Tribal science and environmental management on the Klamath River in California using historical aerial image analysis of land use/land cover change and social networks analysis of water quality management processes; 4) Bayesian statistical modeling of community-collected data on human uses of Marine Protected Areas in California.
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