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Measuring and modeling urban dynamics: impact on quality of life and hydrology (MAMUD)

Projet de recherche SR/00/105 (Action de recherche SR)

Personnes :

  • Prof. dr.  CANTERS Frank - Vrije Universiteit Brussel (VUB)
    Coordinateur du projet
    Partenaire financé belge
    Durée: 1/12/2006-31/12/2010
  • Prof. dr.  GOOSSENS Rudi - Universiteit Gent (UGent)
    Partenaire financé belge
    Durée: 1/12/2006-31/12/2010
  • Dr.  CORNET Yves - Université de Liège (ULG)
    Partenaire financé belge
    Durée: 1/12/2006-31/12/2010
  • Dr.  ENGELEN Guy - Vlaamse Instelling voor Technologisch Onderzoek (VITO)
    Partenaire financé belge
    Durée: 1/12/2006-31/12/2010
  • Dr.  BATELAAN Okke - Vrije Universiteit Brussel (VUB)
    Partenaire financé belge
    Durée: 1/12/2006-31/12/2010
  • Dr.  LAVALLE Carlo - European Commission (EU)
    Partenaire financé étranger
    Durée: 1/12/2006-31/12/2010

Description :

Context and objectives

The goal of MAMUD is to investigate how EO can contribute to a better monitoring, modeling and understanding of urban dynamics, and its impacts on the urban and suburban environment. Research will focus on two urban areas in Europe (Dublin, Istanbul), which are part of the MOLAND project. Both high-resolution (HR) satellite data, as well as medium-resolution (MR) imagery will be used, separately and in combination, to improve the monitoring and modeling of urban change processes and their environmental impact, based on innovative land-use/land-cover mapping approaches, spatial metrics and spatial dynamic modeling.

Major objectives of the project are:

- to improve the extraction of urban land-use/land-cover (LULC) information and elevation data from high- and medium-resolution satellite imagery;
- to investigate how spatial metrics may contribute to a more detailed, more objective, and more generic representation of urban form and function;
- to examine how spatial metrics derived from remotely sensed imagery may complement existing, detailed land-use maps in the calibration and validation of the MOLAND urban growth model;
- to study the impact of urban dynamics on population distribution, landscape characteristics and hydrological run-off in the urban/rural interface.


A first research module (M1) will deal with the extraction of LULC information from HR and MR remotely sensed data. Work on HR data will focus on exploiting the potential of multi-angle image acquisition for reducing the impact of shadow and occluded areas, and for improving the labelling of urban objects. Work on MR data will focus on the production of accurate time series of gradient information (sub-pixel proportion of impervious surfaces and vegetation). Historic information on the 3D-structure of urban areas will be extracted from HR stereoscopic archive imagery, and will be used to complement the land-cover gradient information with information on the vertical dimension of urban structures. A second module (M2) will be devoted to the definition of spatially explicit urban metrics, readily obtainable from RS data and capable of describing urban morphological and structural dynamics in a coherent way. The development of urban metrics will be closely linked to the work on land-use change modelling planned in the third module (M3), where the metrics will be used to complement existing, detailed land-use maps in the calibration of the MOLAND model. The fourth module (M4) will focus on the use of RS-derived urban metrics in population distribution modelling, on quantifying the impact of urban growth on landscape structure, and on modelling rainfall-runoff processes using spatially distributed parameter information derived from RS data (M1) and urban growth modelling (M3).

Results expected

To understand changes in urban form, and how these changes relate to urban development processes that drive these changes or are affected by it, increasing use is made of computer-based urban growth models. The performance of these models strongly depends on the availability of different types of data, needed for calibration and validation. Next to socio-economic data, most of these models require data on topography, road infrastructure, as well as detailed information on LULC change. The latter is usually obtained from visual interpretation of historic time series of aerial photographs or satellite imagery, complemented with ancillary information. In the EU-MOLAND project, aerial photography and satellite imagery have been used to produce detailed land-use datasets for an extensive network of cities and regions for four dates of the last fifty years (early 1950s, late 1960s, 1980s, late 1990s) or for two dates (mid 1980s, late 1990s) in case of larger areas. Calibration and validation of the MOLAND urban growth model based on these data, however, proves to be difficult. The major goal of this project is to develop new approaches to extract information on urban form from time series of RS data, using state-of-the-art information extraction procedures and spatial metrics, and to use that information to improve the calibration and validation of the MOLAND model without significantly increasing the cost of the calibration. The research should also lead to an improvement of current approaches for modelling and forecasting impacts of urban development on population distribution, landscape characteristics and rainfall-runoff processes in the urban fringe.

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