Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

被引:32
作者
Freire, S. [1 ]
Santos, T. [1 ]
Navarro, A. [2 ]
Soares, F. [2 ]
Silva, J. D. [2 ]
Afonso, N. [3 ]
Fonseca, A. [3 ]
Tenedorio, J. [1 ]
机构
[1] Univ Nova Lisboa, Fac Ciencias Sociais & Humanas, E GEO, P-1069061 Lisbon, Portugal
[2] Univ Lisbon, Inst Dom Luiz, P-1699 Lisbon, Portugal
[3] Natl Lab Civil Engn LNEC, P-1700066 Lisbon, Portugal
关键词
QuickBird; Feature extraction; Buildings; Urban; Accuracy; Lisbon;
D O I
10.1016/j.isprsjprs.2013.12.009
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened Quick-Bird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000. (C) 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 9
页数:9
相关论文
共 28 条
[1]  
[Anonymous], 2008, OBJECT BASED IMAGE A
[2]  
[Anonymous], 2009, ASSESSING ACCURACY R
[3]   Automatic detection of residential buildings using LIDAR data and multispectral imagery [J].
Awrangjeb, Mohammad ;
Ravanbakhsh, Mehdi ;
Fraser, Clive S. .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2010, 65 (05) :457-467
[4]   Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information [J].
Benz, UC ;
Hofmann, P ;
Willhauck, G ;
Lingenfelder, I ;
Heynen, M .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2004, 58 (3-4) :239-258
[5]   Object based image analysis for remote sensing [J].
Blaschke, T. .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2010, 65 (01) :2-16
[6]   Focusing on feature-based differences in map comparison [J].
Dungan J.L. .
Journal of Geographical Systems, 2006, 8 (2) :131-143
[7]  
Freire S., 2010, P 30 EARSEL S REM SE
[8]  
Freire S., 2010, P GEOBIA2010 GHENT 2
[9]  
Gianinetto M., 2008, INT J NAVIGATION OBS, V9
[10]  
Hay G.J., 2008, Remote Sensing Applications, P75, DOI DOI 10.1007/978-3-540-77058-9_4