The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-7/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 1411–1418, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-1411-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 1411–1418, 2015
https://doi.org/10.5194/isprsarchives-XL-7-W3-1411-2015

  30 Apr 2015

30 Apr 2015

Analysis of urban development by means of multi-temporal fragmentation metrics from LULC data

M. Sapena and L. A. Ruiz M. Sapena and L. A. Ruiz
  • Geo-Environmental Cartography and Remote Sensing Group, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain

Keywords: Fragmentation Metrics, Urban Change, Growth Patterns, IndiFrag, LULC, Remote Sensing, Multi-temporal

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.