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Faculty of Mathematics and Natural Sciences - Applied Geoinformation Science

Welcome to the Geoinformation science lab

Our vision

 

In the Geoinformation science lab we focus on the development an d application of spatio-temporal techniques to study the human environment system. In our research projects we address spatio-temporal modeling of regional land use change and the human-environment interface in urban areas.

 

 

I Spatio-temporal modeling of land use and land cover change

 

We study land change processes on a regional scale using multitemporal remote-sensing derived land-cover data and an integrated dataset of socio-economic as well as environmental data. Our overall aim within the projects is to test and develop different state-of-the-art techniques of spatio-temporal modeling in land system science including cellular automata, Bayesian Belief networks, agent-based modeling, machine learning and advanced regression analysis.

 

Working environment

We provide a working environment in which everybody contributes an important role to the mission of the lab. We strive for valuing social, cultural and individual diversity in an interdisciplinary and international team.

In our work we aim for transparent and well-documented workflows using open source software besides well-established proprietary products whenever possible. To assess geodata means for us to share and document geodata as far as possible in agreement with data privacy

 

 

II Exploring spatial patterns and processes in the human environment system

 

Urban areas represent the living environment of more than half of the world’s population and are characterized by a heterogeneous set of socio-demographic, economical, and environmental factors. We hence study urban areas as human-environment systems following the concepts of vulnerability and risk, environmental justice, spatial epidemiology and ecosystem services provision. In order to gain new insights on spatial patterns and underlying processes in urban areas we investigate spatial data analysis techniques in the fields of data integration and data mining, geostatistics, remote-sensing, and time-series analysis.

 

We contribute to the current research activities on a national and international level and, wherever adequate, identify the transfer to society and politics. Due to our holistic approaches to Geographic problems we aim for collaborations with national and international researchers in interdisciplinary and transdisciplinary settings.

Teaching

We teach different classes on Bachelor and Master level on fundamental and specialist knowledge in both, concepts and hand’s on knowledge, of applied GIScience. We transfer methods and research topics knowledge into lectures, exercises, seminars and internships and offer close linkages between research and teaching. We enable our students to gain a direct insight into the exciting field of applied GIScience and joining at an early stage as student collaborator or in pursuing final theses. Our students are well prepared for using  GIScience in their future professional career.

 

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