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)
Agent Based Modelling for spatial systems
Isaac IT Ullah, PhD, (Arizona State University 2013) Dr. Ullah is a computational archaeologist who employs GIS and simulation modeling to understand the long-term dynamics of humans and the Earth System. Dr. Ullah is particularly interested in the social and environmental changes surrounding the advent of farming and animal husbandry. His focus is on Mediterranean and other semi-arid landscapes, and he conducts fieldwork in Jordan, Italy, and Kazakhstan. His field work includes survey for and excavation of early agricultural sites as well as geoarchaeological analyses of anthropogenic landscapes. His specialties include landscape evolution, complex adaptive systems science, computational methods, geospatial analysis, and imagery analysis.
Computational Archaeology, Food Production, Forager-Farmer transition, Neolithic, Agro-pastoralism, Erosion Modeling, Anthropogenic Landscapes, Geoarchaeology, Modeling and Simulation, GIS, Imagery Analysis, ABM, Mediterranean
I am a lowly civil servant moonlighting as a PhD student interested in urban informatics, Smart Cities, artificial intelligence/machine learning, all-things geospatial and temporal, advanced technologies, agent-based modeling, and social complexity… and enthusiastically trying to find a combination thereof to form a disseration. Oh… and I would like to win the lottery.
Eric has graduate degrees in urban planning and policy and sociology and an undergraduate degree in biology. He has worked on multiple collaborative and interdisciplinary projects and is skilled at engaging communities and other stakeholders. He is adept at qualitative research and has earned a Certificate in Geospatial Analysis and Visualization, demonstrating proficiency in Adobe Suite, ArcGIS, agent-based modeling and system dynamics modeling. He is currently writing manuscripts for publication based on his work on motivating energy retrofit decisions, energy-related urban planning, municipal decision-making on infrastructure investments, and other work on resilience and sustainability.
Conducts urban planning and policy research on energy efficiency, environmental, and infrastructure decision making.
My interests center around long-term human ecology and landscape dynamics with ongoing projects in the Mediterranean (late Pleistocene through mid-Holocene) and recent work in the American Southwest (Holocene-Archaic). I’ve done fieldwork in Spain, Bosnia, and various locales in North America and have expertise in hunter/gatherer and early farming societies, geoarchaeology, lithic technology, and evolutionary theory, with an emphasis on human/environmental interaction, landscape dynamics, and techno-economic change.
Quantitative methods are critical to archaeological research, and socioecological sciences in general. They are an important focus of my research, especially emphasizing dynamic modeling, spatial technologies (including GIS and remote sensing), statistical analysis, and visualization. I am a member of the open source GRASS GIS international development team that is making cutting edge spatial technologies available to researchers and students around the world.
My research examines the most effective and efficient policies for renewable energy development using an approach that integrates input-output analysis, life cycle analysis, econometric, and agent-based modelling to estimate the impacts of the policies to economic, emission, extracted materials, renewable energy capacity and social acceptance.