Monitoring Urban Dynamics Change - MURBANDY: Development of Land Use Change Databases for the Vienna Area Using Remote Sensing Data

Project Leader: Dr. Klaus Steinnocher

The European Union is the most urbanized part of the world and future urban development will be confronted with the finite availability of land. For this reason, the European Commission has initiated a number of studies such as Monitoring Urban Dynamics (MURBANDY) that promote a homogeneous and equilibrated development of Europe’s landscapes. MURBANDY identifies Earth Observation (EO) as a measurement procedure that can provide a synoptic view of European cities. Spatial analysis and modeling activity are conducted to understand urban cities in their relationship with the environment and the availability of renewable resources. MURBANDY in its current pilot phase focuses on 15 European cities.
MURBANDY is subdivided into three components, CHANGE, UNDERSTAND and FORECAST. CHANGE aims at implementing an EO based procedure for monitoring land cover/- use changes in urban and peri-urban areas using very-high resolution satellite imagery. Land use databases covering 40 years and the changes occurred in between are currently established. The data-sets developed are structured within a geographic information system framework that will also include non-EO data. UNDERSTAND aims at computing static and dynamic EO based urban indicators as well as EO/non-space data environmental indicators to help understand urban and peri-urban landscapes and their dynamics. FORECAST aims at developing scenarios of urban growth under current and/or future policies and economic systems to assess the sustainability of Europe’s landscapes.
This project focuses on the CHANGE part of MURBANDY for the metropolitan area of Vienna. Objective is the establishment of four land use data bases from the 1950s, 1960s, 1980s and 1990s. For each date a polygon and a vector coverage will be derived representing land use units and linear features such as street or railway networks respectively. The interpretation key is based on the CORINE land cover nomenclature, but extended by a fourth level for the urban land use categories. The data sets used in this project are EO data, including air- and space-borne imagery, and ancillary information such as city maps, land use inventories or master plans.

Results

The outcome of the project are digital spatial data bases representing the land use of the metropolitan area of Vienna for 1958, 1971, 1986 and 1997. For each date a vector layer – representing linear features such as roads and railways – and a polygon layer – representing land use areas – were derived from computer-assisted visual interpretation of the EO data. The accuracy of the data bases refers to a map scale of 1:25.000. The geographic projection of the data bases refers to the Austrian National Projection System (Gauß-Krüger M34).
In addition to the establishment of the data bases some statistical analysis was performed on the time series. The general increase of residential, industrial, commercial and service areas is significant. This is particularly valid for the north-eastern part of the city, across the Danube, and for the southern outskirts of the city. As a consequence of a strict environmental policy since 1872 the Vienna Woods have been successfully protected from urbanisation. An obvious change occurred along the Danube where the “Donauinsel” was build in the early eighties as a leisure island for the Viennese people.
The increase of artificial surfaces can be directly related to a decrease of agricultural areas. The decrease of forest and semi-natural areas is mostly related to the construction of the “Donauinsel”, when the former flooding areas (semi-natural areas) were divided into the new arm of the Danube (waterbody) and the artificial island (artificial non-agricultural vegetated area). This change is also responsible for the significant increase of water bodies between 1971 and 1986.
The data bases - in combination with e.g. socio-economic data sets - will be used to identify urban and environmental indicators that will help in providing a synthetic assessment of urban and peri-urban landscapes. Developing scenarios of growth for urban and peri-urban areas might be another application based on the combination of EO and non-space data. The scenarios could serve as major input to formulate and evaluate long term strategy for sustainable urban development.