Using agent based models to look at ecosystem-based or integrated management of oceans and coastal zones
The goal of my research program is to improve our understanding about highly integrated natural and human processes. Within the context of Land-System Science, I seek to understand how natural and human systems interact through feedback mechanisms and affect land management choices among humans and ecosystem (e.g., carbon storage) and biophysical processes (e.g., erosion) in natural systems. One component of this program involves finding novel methods for data collection (e.g., unmanned aerial vehicles) that can be used to calibrate and validate models of natural systems at the resolution of decision makers. Another component of this program involves the design and construction of agent-based models to formalize our understanding of human decisions and their interaction with their environment in computer code. The most exciting, and remaining part, is coupling these two components together so that we may not only quantify the impact of representing their coupling, but more importantly to assess the impacts of changing climate, technology, and policy on human well-being, patterns of land use and land management, and ecological and biophysical aspects of our environment.
To achieve this overarching goal, my students and I conduct fieldwork that involves the use of state-of-the-art unmanned aerial vehicles (UAVs) in combination with ground-based light detection and ranging (LiDAR) equipment, RTK global positioning system (GPS) receivers, weather and soil sensors, and a host of different types of manual measurements. We bring these data together to make methodological advancements and benchmark novel equipment to justify its use in the calibration and validation of models of natural and human processes. By conducting fieldwork at high spatial resolutions (e.g., parcel level) we are able to couple our representation of natural system processes at the scale at which human actors make decisions and improve our understanding about how they react to changes and affect our environment.
land use; land management; agricultural systems; ecosystem function; carbon; remote sensing; field measurements; unmanned aerial vehicle; human decision-making; erosion, hydrological, and agent-based modelling
My initial training was in cadastre and geodesy (B.Eng from the Distrital University, UD, Colombia). After earning my Master’s degree in Geography (UPTC, Colombia) in 2003, I worked for the “José Benito Vives de Andreis” marine and coastal research institute (INVEMAR) and for the International Center for Tropical Agriculture (CIAT). Three years later, in 2006, I left Colombia to come to Canada, where I began a PhD in Geography with a specialization in modelling complex systems at Simon Fraser University (SFU), under the direction of Dr. Suzana Dragicevic (SAMLab). In my dissertation I examined the topic of spatial and temporal modelling of insect epidemics and their complex behaviours. After obtaining my PhD in 2011, I began postdoctoral studies at the University of British Columbia (2011) and the University of Victoria (2011-2013), where I worked on issues concerning the spatial and temporal relationships between changes in indirect indicators of biodiversity and climate change.
I am an Associate Professor in the Department of Geography at the University of Montreal. My research interests center around the incorporation of artificial intelligence and machine learning techniques into the development Agent-Based Models to solve complex socio-ecological problems in different kind of systems, such as urban, forest and wetland ecosystems.
The core of my research projects aim to learn more about spatial and temporal interactions and relationships driving changes in our world, by focusing on the multidisciplinary nature of geographical information science (GIScience) to investigate the relationships between ecological processes and resulting spatial patterns. I integrate spatial analysis and modeling approaches from geographic information science (GIScience) together with computational intelligence methods and complex systems approaches to provide insights into complex problems such as climate change, landscape ecology and forestry by explicitly representing phenomena in their geographic context.
Specialties: Agent-based modeling, GIScience, Complex socio-environmental systems, Forestry, Ecology
Mazaher Kianpour is a PhD candidate at NTNU. He holds a Bachelor’s degree in Computer Engineering (Software) from the Payame Noor University. He obtained his Master’s degree in Architecture of Computer Systems from Shahid Beheshti University, Tehran, Iran. He started his PhD in Information Security at NTNU in May 2018. His PhD research lies at the intersection of economics and information security with a socio-technical perspective. He has several years of work experience at Tehran University of Medical Sciences, and his professional training includes Computer Networks, Cybersecurity and Risk Management.
My main research interest is modelling of information security, business operations and deterrents in complex ICT ecosystem. I will in particular focus on the complex interaction between various stakeholders and actors in the information security business domain. In order to model and better understand the information security ecosystem, I rely on agent-based simulation and quantitative modelling techniques such as stochastic modelling, discrete event simulations and game theory. Of particular interest is to gain increased understanding on how various security threats and measures influence business operations in the digital ecosystem.
are related to interoperability and conflation models in geospatial analysis and integrated modelling applications, particularly in the context of spatial data infrastructures such as GEOSS. This translates to a focus on geospatial statistics, geospatial patterns, outbreak detection and geospatial data mining in general, but also to data quality and uncertainty propagation principles in relation to geoworkflows connected to/using web services. Didier’s research centres on environmental agro-ecological geospatial models, and public health and spatial epidemiology applications. (see website)
My experience is diverse, with research in spatial analyses and GIS, ecosystem modeling, landscape ecology, database management, biogeographical relationships of birds and plants, species/habitat relationships, wildlife and pastoral livestock mobility, spectroscopy, cluster analysis, and telemetry techniques. Research projects are ongoing in Colorado, the contiguous US, Kenya, Mali, and Tibet.
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My general research interest is on modeling of complex natural and human systems systems. Specifically, I am interested in modeling agricultural production systems, that blends the complexity, multiplicity of scales and feedbacks of biophysical interactions in natural ecosystems with the additional intricacies of human decision-making. During last years I have coordinated the development and evaluation of an agent-based of agricultural production systems in the Argentinean Pampas.