SAR-Based Urban Extents Extraction: From ENVISAT to Sentinel-1

There are only a few examples in technical literature about the use of Synthetic Aperture Radar (SAR) dataset to extract human settlement extents. This paper shows how it is possible to extract a global urban layer from multiyear ENVISAT Advanced SAR (ASAR) backscatter measurements, overcoming some of the drawbacks of a preliminary release. Additionally, this research shows that the same technique can be applied with minor changes to SAR data from the new Sentinel-1A platform. The current ASAR urban layer shows improvements with respect to the preliminary version in the test sites of the 2011 Round Robin (RR) on urban mapping promoted by the European Space Agency (ESA). For Sentinel-1, results are similarly validated on the test sites of the 2015 edition of the RR on urban mapping. Results prove that UEXT can be used for SAR-based urban extent extraction using multiple sensors.

[1]  R. Nemani,et al.  Global Distribution and Density of Constructed Impervious Surfaces , 2007, Sensors.

[2]  A. Belward,et al.  GLC2000: a new approach to global land cover mapping from Earth observation data , 2005 .

[3]  Huadong Guo,et al.  A Global Human Settlement Layer From Optical HR/VHR RS Data: Concept and First Results , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4]  P. Levelt,et al.  ESA's sentinel missions in support of Earth system science , 2012 .

[5]  C. Woodcock,et al.  Mapping urban areas by fusing multiple sources of coarse resolution remotely sensed data , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[6]  Frédéric Bretar,et al.  Comparison of RADARSAT-1 and IKONOS satellite images for urban features detection , 2005, Inf. Fusion.

[7]  Thomas Esch,et al.  Urban Footprint Processor—Fully Automated Processing Chain Generating Settlement Masks From Global Data of the TanDEM-X Mission , 2013, IEEE Geoscience and Remote Sensing Letters.

[8]  Jin Chen,et al.  Global land cover mapping at 30 m resolution: A POK-based operational approach , 2015 .

[9]  Barry Haack,et al.  Radar spatial considerations for land cover extraction , 2005 .

[10]  Paolo Gamba,et al.  Semi-automatic choice of scale-dependent features for satellite SAR image classification , 2006, Pattern Recognit. Lett..

[11]  Zong-Guo Xia,et al.  SAR applications in human settlement detection, population estimation and urban land use pattern analysis: a status report , 1997, IEEE Trans. Geosci. Remote. Sens..

[12]  Urs Wegmüller,et al.  Strengths and weaknesses of multi-year Envisat ASAR backscatter measurements to map permanent open water bodies at global scale , 2015 .

[13]  D. Maktav,et al.  Remote sensing of urban areas , 2005 .

[14]  Achim Roth,et al.  Semi-automated classification of urban areas by means of high resolution radar data , 2004 .

[15]  Christelle Vancutsem,et al.  GlobCover: ESA service for global land cover from MERIS , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[16]  M. Friedl,et al.  A new map of global urban extent from MODIS satellite data , 2009 .

[17]  T. Strozzi,et al.  Potential and methodology of satellite based SAR for hazard mapping , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[18]  Lu Liang,et al.  China’s urban expansion from 1990 to 2010 determined with satellite remote sensing , 2012 .

[19]  Andrew Jarvis,et al.  Hole-filled SRTM for the globe Version 4 , 2008 .

[20]  F. Dell'Acqua,et al.  Unstructured Human Settlement Mapping with SAR Sensors , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[21]  Damien Sulla-Menashe,et al.  MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .

[22]  M. Herold,et al.  Global Mapping of Human Settlement : Experiences, Datasets, and Prospects , 2009 .

[23]  Thomas Esch,et al.  Pattern-Based Accuracy Assessment of an Urban Footprint Classification Using TerraSAR-X Data , 2011, IEEE Geoscience and Remote Sensing Letters.

[24]  Paolo Gamba,et al.  Fast and Efficient Urban Extent Extraction Using ASAR Wide Swath Mode Data , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.