Modeling of impervious surface in Germany using Landsat images and topographic vector data

The constant expansion of urban agglomerations in most countries is closely associated with a significant increase of impervious surface (IS). In Europe, robust and cost-effective methods for detection and quantification of IS on a continental or national scale are still rare. Thus, our study focuses on determining the percentage of impervious surface (PIS) for whole Germany based on a combined analysis of Landsat images and vector data on roads and railway networks, using Support Vector Machines (SVM) and GIS functionalities. We developed a procedure which provides functionalities for 1) the modeling of IS for built-up areas (PISB) based on optical earth observation data, 2) the combination of PISB with vector data providing additional information on small-scale infrastructure (PIST) and 3) the spatial aggregation of the combined product (PISBT) to the administrative units of municipalities. Compared to reference data sets of four cities, the results showed a mean absolute error of 19.4 % and a mean standard deviation of 17.3 %. The mean PIS of the total of residential, industrial and transportation-related areas in Germany comes up to 43.0 %, with a minimum in the federal state of Brandenburg (39.3 %) and a maximum in Hessen (46.1 %).

[1]  M. Bauer,et al.  Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery , 2007 .

[2]  Limin Yang,et al.  An approach for mapping large-area impervious surfaces: synergistic use of Landsat-7 ETM+ and high spatial resolution imagery , 2003 .

[3]  Qihao Weng,et al.  Mapping Urban Impervious Surfaces from Medium and High Spatial Resolution Multispectral Imagery , 2007 .

[4]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[5]  Stefan Coe,et al.  Operational Remote Sensing Solutions for Estimating Total Impervious Surface Areas , 2006 .

[6]  Michael P. Johnson Environmental Impacts of Urban Sprawl: A Survey of the Literature and Proposed Research Agenda , 2001 .

[7]  J. R. Jensen,et al.  Effectiveness of Subpixel Analysis in Detecting and Quantifying Urban Imperviousness from Landsat Thematic Mapper Imagery , 1999 .

[8]  D J Cieslewicz,et al.  THE ENVIRONMENTAL IMPACTS OF SPRAWL. IN: URBAN SPRAWL: CAUSES, CONSEQUENCES AND POLICY RESPONSES , 2002 .

[9]  M. Bauer,et al.  Estimating and Mapping Impervious Surface Area by Regression Analysis of Landsat Imagery , 2007 .

[10]  Stefan Dech,et al.  Potential of hyperspectral remote sensing for characterisation of urban structure in Munich , 2008 .

[11]  T. Esch,et al.  Large-area assessment of impervious surface based on integrated analysis of single-date Landsat-7 images and geospatial vector data , 2009 .

[12]  D. Lu,et al.  Spectral mixture analysis of ASTER images for examining the relationship between urban thermal features and biophysical descriptors in Indianapolis, Indiana, USA , 2006 .

[13]  Martin Herold,et al.  Mapping imperviousness using NDVI and linear spectral unmixing of ASTER data in the Cologne-Bonn region (Germany) , 2004, SPIE Remote Sensing.

[14]  Gavin A. Wood,et al.  THE APPLICATION OF REMOTE SENSING TO IDENTIFY AND MEASURE SEALED AREAS IN URBAN ENVIRONMENTS , 2006 .