Positional Accuracy Analysis of Satellite Imagery by Circular Statistics

The proposed method in this paper uses circular statistics for the analysis of errors in the positional accuracy of geometric corrections satellite images using Independent Check Lines (ICL) instead of Independent Check Points (ICP). Circular statistics has been preferred because of the vectorial nature of the spatial error. A study case has been presented and discussed in detail. From the TERRA-ASTER images of Extremadura area (Spain), the Ground Control Point (GCP), ICP, and ICL data were acquired using differential GPS through field survey, and the planimetric positional accuracy was analyzed by both the conventional method (using ICP) and the proposed method (using 1CL). Comparing conventional and proposed methods, the results indicated that modulus statistics are similar (e.g., RMSE of Geometric Correction 1 were 17.5 for the conventional method and 17.2 m for proposed method). But as additional results, azimuthal component statistics was calculated (e.g., mean direction: 247.2° in Geometric Correction 1), and several tests were made which showed the error distribution are not uniform and normal.

[1]  José A. Malpica,et al.  An automatic method for road extraction in rural and semi-urban areas starting from high resolution satellite imagery , 2005, Pattern Recognit. Lett..

[2]  Mehdi Mokhtarzade,et al.  Road Extraction from High Resolution Satellite Images Using Image Processing Algorithms and CAD-Based Environments Facilities , 2008 .

[3]  Curt H. Davis,et al.  An integrated system for automatic road mapping from high-resolution multi-spectral satellite imagery by information fusion , 2005, Inf. Fusion.

[4]  S. Kay,et al.  Geometric Quality Assessment of Orthorectified VHR Space Image Data. , 2003 .

[5]  Qiaoping Zhang,et al.  Benefit of the angular texture signature for the separation of parking lots and roads on high resolution multi-spectral imagery , 2006, Pattern Recognit. Lett..

[6]  Zhilin Li,et al.  Effects of check points on the reliability of DTM accuracy estimates obtained from experimental tests , 1991 .

[7]  Francisco Javier Ariza-López,et al.  Accuracy, reliability, and depuration of SPOT HRV and Terra ASTER digital elevation models , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Jun Zhou,et al.  Online Learning With Novelty Detection in Human-Guided Road Tracking , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Toni Schenk,et al.  From point-based to feature-based aerial triangulation , 2004 .

[10]  Emmanuel P. Baltsavias,et al.  Object extraction and revision by image analysis using existing geodata and knowledge: current status and steps towards operational systems☆ , 2004 .

[11]  Yasushi Yamaguchi,et al.  Overview of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) , 1998, IEEE Trans. Geosci. Remote. Sens..

[12]  A. C. Bird,et al.  GEOMETRIC CORRECTION OF SPOT AND LANDSAT IMAGERY: A COMPARISON OF MAP- AND GPS-DERIVED CONTROL POINTS , 1996 .

[13]  Peter Wonka,et al.  Road Network Extraction and Intersection Detection From Aerial Images by Tracking Road Footprints , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[14]  E. Batschelet.  Circular statistics in biology , 1981 .

[15]  Christian Heipke,et al.  Graph-supported verification of road databases , 2004 .

[16]  Nicholas I. Fisher,et al.  Statistical Analysis of Circular Data , 1993 .

[17]  Joachim Höhle.  Experiences with the Production of Digital Orthophotos , 1996 .

[18]  Peter Doucette,et al.  Automated Road Extraction from High Resolution Multispectral Imagery , 2004 .

[19]  B. Heller.  Circular Statistics in Biology, Edward Batschelet. Academic Press, London & New York (1981), 371, Price $69.50 , 1983 .

[20]  Alexandre Carleer,et al.  Assessment of Very High Spatial Resolution Satellite Image Segmentations , 2005 .