Remote Sensing Data Assimilation in Modelling of Urban Dynamics

Introduction

Urban change processes are increasingly affecting the environment. The problem analysis, planning and monitoring phases of sustainable urban management policies require reliable and sufficiently detailed information on the urban environment and its dynamics. Geospatial and socio-economic data supplemented with knowledge on dynamic urban processes are incorporated in the land-use change models currently available to planners and policy makers. They enable them to assess the impacts of decisions on the spatial systems that they are to manage. To be usefully applicable to this effect, land-use change models need extensive calibration. Current calibration methods, however, do not take into account uncertainties in the parametrisation of these models and in land-use data used as a reference. This leads to uncertainties in the prediction of future land use, which need to be quantified and reduced.

Objective

The ASIMUD project aims to provide a solution to this issue by applying a data assimilation framework to the calibration of land-use change models. The framework will use land-use maps and remote sensing derived land-use data at time steps that they are available in order to optimize the parameters of the land-use change model.

Approach

Coupling of an existing land use change model with the PCRaster data assimilation framework.

Consortium partners

Additional information

Detailed project information is available here.

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