Abstract
Abstract. The monitoring and modelling of the evolution of urban areas is increasingly attracting the attention of land managers and administration. New data, tools and methods are being developed and made available for a better understanding of these dynamic areas. We study and analyse the concept of landscape fragmentation by means of GIS and remote sensing techniques, particularly focused on urban areas. Using LULC data obtained from the European Urban Atlas dataset developed by the local component of Copernicus Land Monitoring Services (scale 1:10,000), the urban fragmentation of the province of Rome is studied at 2006 and 2012. A selection of indices that are able to measure the land cover fragmentation level in the landscape are obtained employing a tool called IndiFrag, using as input data LULC data in vector format. In order to monitor the urban morphological changes and growth patterns, a new module with additional multi-temporal metrics has been developed for this purpose. These urban fragmentation and multi-temporal indices have been applied to the municipalities and districts of Rome, analysed and interpreted to characterise quantity, spatial distribution and structure of the urban change. This methodology is applicable to different regions, affording a dynamic quantification of urban spatial patterns and urban sprawl. The results show that urban form monitoring with multi-temporal data using these techniques highlights urbanization trends, having a great potential to quantify and model geographic development of metropolitan areas and to analyse its relationship with socioeconomic factors through the time.
Highlights
Monitoring, assessing the influences of land use land cover (LULC) change, and measuring landscape patterns and their change processes have become a priority for researchers, land managers and policy makers (Liu et al, 2010; Malaviya et al, 2010)
The main objectives of this study are: (1) To introduce a software tool (IndiFrag) for the extraction of urban LULC metrics at different levels and using multi-temporal data; (2) to assess the capabilities of these metrics in the analysis of urban sprawl dynamics based on preliminary data from the Urban Atlas; and (3) to preview and discuss their use for comparison of the expansion patterns of different cities, their relation with socio-economic variables, and for the definition of models of urban growing based on these data that are becoming available in a regular basis
The remainder land uses were grouped as follows: housing represents urban fabric, independently of the soil sealing degree; commercial, industrial and landmark class includes public buildings; roads and rail network was reclassified as roads; barren land includes mine, dump and construction sites; leisure areas represents green urban areas, sport and leisure facilities; and water bodies remains as water
Summary
Monitoring, assessing the influences of LULC change, and measuring landscape patterns and their change processes have become a priority for researchers, land managers and policy makers (Liu et al, 2010; Malaviya et al, 2010). The evolution of spatial structure in a city is a result of natural, social, economic and technology factors (Tian et al, 2011). The population increase in urban areas demands more natural resources, including land for building housings and industrial, commercial and transport infrastructures. The trend to move out of city centres to the suburbs often drives the development of urban sprawl (European Commission, 2012). This urban expansion usually grows in a scattered way throughout countryside. Drivers of urban sprawl can be grouped into economic factors, demographic factors, housing preferences, social aspects, transportation, and regulatory frameworks (EEA, 2011)
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