Humboldt University Remote Sensing Laboratory

Research Projects of the Geomatics Lab

Modeling cropland dynamics in Romania – a comparison of logistic regressions and neural networks

(German: Modellierung von landwirtschaftlicher Nutzung in Rumänien – ein Vergleich von logistischer Regression und neuronalen Netzen)

Cropland change is the dominating land use change process in Romania, the second largest new member state of the European Union. This project investigates cropland dynamics in Argeş County, Romania, in cooperation IAMO and in continuation of a project of the junior research group “Postsocialist Land Reforms and Land Use”. Land cover change is monitored and analyzed using hybrid classification of Landsat data. We study cropland change by using two land use modelling techniques. We assess the underlying causes of cropland change using spatially explicit logistic regressions. Maps of likely cropland change are derived by neural network analysis (Land Transformation Model). We identify hot spots of change as those areas that are under most eminent threat of change as a possible tool for spatial decision-making.

Principal Investigators:
Tobia Lakes (Humboldt-Universität zu Berlin)
Daniel Müller (Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO))


			Projects
	overview Research Projects of the Geomatics Lab: Data integration and data mining DHAKA-INNOVATE DeSurvey EnMAP-Box EnMAP Core Science Team Environmental justice Graduate School on Urban Ecology Land changes in Albania and Kosovo Linking urban land use characteristics and mental illness Metrik Modeling cropland dynamics in Romania Modeling with domain-specific languages Risk model of Dengue Disease in Malaysia Social and health characteristics in urban areas Urban Environmental Monitoring Urban Environmental Monitoring II Urban growth in Greater Tirana Research Collaborations: ESF Exploratory Workshop: EuCaRe EARSeL workshop Post-USSR land cover Rapid urbanization Other Projects of the Geomatics Lab: Geodateninfrastruktur imageSVM		Research Projects of the Geomatics Lab Modeling cropland dynamics in Romania – a comparison of logistic regressions and neural networks (German: Modellierung von landwirtschaftlicher Nutzung in Rumänien – ein Vergleich von logistischer Regression und neuronalen Netzen) Cropland change is the dominating land use change process in Romania, the second largest new member state of the European Union. This project investigates cropland dynamics in Argeş County, Romania, in cooperation IAMO and in continuation of a project of the junior research group “Postsocialist Land Reforms and Land Use”. Land cover change is monitored and analyzed using hybrid classification of Landsat data. We study cropland change by using two land use modelling techniques. We assess the underlying causes of cropland change using spatially explicit logistic regressions. Maps of likely cropland change are derived by neural network analysis (Land Transformation Model). We identify hot spots of change as those areas that are under most eminent threat of change as a possible tool for spatial decision-making. Principal Investigators: Tobia Lakes (Humboldt-Universität zu Berlin) Daniel Müller (Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO))