A model-based approach for automatic building database updating from high-resolution space imagery

This article presents an approach for automatic building database updating from high-resolution space imagery based on the support vector machine (SVM) classification and building models. The developed approach relies on an idea that the buildings are similar in shape within an urban block or a neighbourhood unit. First, the building patches are detected through classification of the pan-sharpened high-resolution space imagery along with the normalized digital surface model (nDSM) and the normalized difference vegetation index (NDVI) using the binary SVM classifier. Then, the buildings that exist in the vector database but not seen in the image are detected through the analyses of the detected building patches. The buildings, which were constructed after the compilation date of the existing vector database, are extracted through the proposed model-based approach that utilizes the existing building database as a building model library. The approach was implemented in selected urban areas of the Batikent district of Ankara, the capital city of Turkey, using the IKONOS images and the existing building database. The results validated the success of the developed approach, with the building extraction accuracy computed to be higher than 80%.

[1]  Helmut Mayer,et al.  Automatic Object Extraction from Aerial Imagery - A Survey Focusing on Buildings , 1999, Comput. Vis. Image Underst..

[2]  Kensaku Fujii,et al.  Urban object reconstruction using airborne laser elevation image and aerial image , 2002, IEEE Trans. Geosci. Remote. Sens..

[3]  Ramakant Nevatia,et al.  Detecting changes in aerial views of man-made structures , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[4]  Vladimir Naumovich Vapni.  The Nature of Statistical Learning Theory , 1995 .

[5]  Paul M. Mather,et al.  Support vector machines for classification in remote sensing , 2005 .

[6]  J. Shan,et al.  CLASS-GUIDED BUILDING EXTRACTION FROM IKONOS IMAGERY , 2003 .

[7]  Jon Atli Benediktsson,et al.  Classification and feature extraction for remote sensing images from urban areas based on morphological transformations , 2003, IEEE Trans. Geosci. Remote. Sens..

[8]  Markus Niederöst,et al.  Detection and reconstruction of buildings for automated map updating , 2003 .

[9]  Giles M. Foody,et al.  Mapping a specific class for priority habitats monitoring from satellite sensor data , 2006 .

[10]  P. Varshney,et al.  Multisource Classification Using Support Vector Machines: An Empirical Comparison with Decision Tree and Neural Network Classifiers , 2008 .

[11]  Jiann-Yeou Rau,et al.  Robust Reconstruction of Building Models from Three-Dimensional Line Segments , 2003 .

[12]  Ansgar Brunn,et al.  3rd International Workshop: Automatic Extraction of Man-Made Objects from Aerial and Space Images , 2001, Künstliche Intell..

[13]  W. Tobler.  A Computer Movie Simulating Urban Growth in the Detroit Region , 1970 .

[14]  Giles M. Foody,et al.  Sanchez-Hernandez, Carolina and Boyd, Doreen S. and Foody, Giles M. (2007) One-class classification for monitoring a specific land cover class: SVDD classification of fenland. IEEE Transactions on , 2016 .

[15]  Giles M. Foody,et al.  Training set size requirements for the classification of a specific class , 2006 .

[16]  L. S. Davis,et al.  An assessment of support vector machines for land cover classi(cid:142) cation , 2002 .

[17]  Jefferey A. Shufelt,et al.  Fusion of monocular cues to detect man-made structures in aerial imagery , 1993 .

[18]  Yi-Hsing Tseng,et al.  SEMIAUTOMATED BUILDING EXTRACTION BASED ON CSG MODEL-IMAGE FITTING , 2003 .

[19]  Ruşen Keleş,et al.  Kooperatifçilik ilkeleri ve sosyal konut politikası açısından Türkiye'de konut kooperatifleri , 1967 .

[20]  Zhilin Li,et al.  A Split-and-Merge Technique for Automated Reconstruction of Roof Planes , 2005 .

[21]  A. Grün,et al.  Semi-automated approaches to site recording and modeling , 2000 .

[22]  Giles M. Foody,et al.  A relative evaluation of multiclass image classification by support vector machines , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[23]  Jeffrey Shufelt.  Geometric Constraints for Object Detection and Delineation , 1999 .

[24]  Dong-Chen He,et al.  Automatic change detection of buildings in urban environment from very high spatial resolution images using existing geodatabase and prior knowledge , 2010 .

[25]  John A. Richards,et al.  Remote Sensing Digital Image Analysis , 1986 .

[26]  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 .

[27]  Brian Pilemann Olsen,et al.  Automated Change Detection for Updates of Digital Map Databases , 2003 .

[28]  C. Brenner.  Building reconstruction from images and laser scanning , 2005 .

[29]  Kim L. Boyer,et al.  A system to detect houses and residential street networks in multispectral satellite images , 2005, Comput. Vis. Image Underst..

[30]  Yerach Doytsher,et al.  MONOCULAR RIGHT-ANGLE BUILDING HYPOTHESIS GENERATION IN REGULARIZED URBAN AREAS BY POSE CLUSTERING , 2003 .

[31]  Claus Brenner,et al.  Extraction of buildings and trees in urban environments , 1999 .

[32]  Curt H. Davis,et al.  Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information , 2005, EURASIP J. Adv. Signal Process..

[33]  Franck Jung.  Detecting building changes from multitemporal aerial stereopairs , 2004 .

[34]  P. Zingaretti,et al.  Performance evaluation of automated approaches to building detection in multi-source aerial data , 2010 .

[35]  I. Dowman,et al.  Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction * , 2007 .

[36]  Cem Ünsalan,et al.  Urban-Area and Building Detection Using SIFT Keypoints and Graph Theory , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[37]  John Trinder,et al.  Building detection by fusion of airborne laser scanner data and multi-spectral images : Performance evaluation and sensitivity analysis , 2007 .

[38]  Kim L. Boyer,et al.  A system to detect houses and residential street networks in multispectral satellite images , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[39]  You Hongjian,et al.  3D building reconstruction from aerial CCD image and sparse laser sample data , 2006 .

[40]  H. Murakami,et al.  Change detection of buildings using an airborne laser scanner , 1999 .

[41]  C. Song,et al.  Urban 3D GIS From LiDAR and digital aerial images , 2004, Comput. Geosci..

[42]  Arcot Sowmya,et al.  Modelling and representation issues in automated feature extraction from aerial and satellite images , 2000 .

[43]  J. Peng,et al.  Model and context‐driven building extraction in dense urban aerial images , 2005 .

[44]  Guobin Zhu,et al.  Classification using ASTER data and SVM algorithms;: The case study of Beer Sheva, Israel , 2002 .

[45]  Kyoung Mu Lee,et al.  Fusion of Lidar and Imagery for Reliable Building Extraction , 2008 .

[46]  Kourosh Khoshelham,et al.  A Model‐Based Approach to Semi‐Automated Reconstruction of Buildings from Aerial Images , 2004 .

[47]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[48]  Curt H. Davis,et al.  A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas , 2003, IEEE Trans. Geosci. Remote. Sens..

[49]  P. Gamba,et al.  Joint analysis of SAR, LIDAR and aerial imagery for simultaneous extraction of land cover, DTM and 3D shape of buildings , 2002 .

[50]  George Vosselman,et al.  Reconstruction of 3D building models from aerial images and maps , 2003 .

[51]  Yerach Doytsher,et al.  Right‐Angle Rooftop Polygon Extraction in Regularised Urban Areas: Cutting the Corners , 2004 .

[52]  D. Fairbairn,et al.  Comparing expert systems and neural fuzzy systems for object recognition in map dataset revision , 2002 .

[53]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[54]  D. Boyd,et al.  Updating topographic mapping in Great Britain using imagery from high-resolution satellite sensors , 2006 .