{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T02:06:20Z","timestamp":1776737180790,"version":"3.51.2"},"reference-count":61,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2011,8,19]],"date-time":"2011-08-19T00:00:00Z","timestamp":1313712000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In order to better understand and exploit the rich information content of new remotely sensed datasets, there is a need for comparative land cover classification studies. In this study, the automatic classification of a suburban area was investigated by using (1) digital aerial image data; (2) digital aerial image data and laser scanner data; (3) a high-resolution optical QuickBird satellite image; (4) high-resolution airborne synthetic aperture radar (SAR) data; and (5) SAR data and laser scanner data. A segment-based approach was applied. The classification rules for distinguishing buildings, trees, vegetated ground, and non-vegetated ground were created automatically by using permanent test field points in a training area and the classification tree method. The accuracy of the results was evaluated by using test field points in validation areas. The highest overall accuracies were obtained when laser scanner data were used to separate high and low objects: 97% in Test 2, and 82% in Test 5. The overall accuracies in the other tests were 74% (Test 1), 67% (Test 3), and 68% (Test 4). An important contributing factor for the lower accuracy in Tests 3 and 4 was the lower spatial resolution of the datasets. The classification tree method and test field points provided a feasible and automated means of comparing the classifications. The approach is well suited for rapid analyses of new datasets to predict their quality and potential for land cover classification.<\/jats:p>","DOI":"10.3390\/rs3081777","type":"journal-article","created":{"date-parts":[[2011,8,19]],"date-time":"2011-08-19T10:35:15Z","timestamp":1313750115000},"page":"1777-1804","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":77,"title":["Segment-Based Land Cover Mapping of a Suburban Area\u2014Comparison of High-Resolution Remotely Sensed Datasets Using Classification Trees and Test Field Points"],"prefix":"10.3390","volume":"3","author":[{"given":"Leena","family":"Matikainen","sequence":"first","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kirsi","family":"Karila","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2011,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"963","DOI":"10.14358\/PERS.69.9.963","article-title":"A comparison of urban mapping methods using high-resolution digital imagery","volume":"69","author":"Thomas","year":"2003","journal-title":"Photogramm. Eng. Remote Sensing"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.isprsjprs.2003.09.007","article-title":"Object-based classification of remote sensing data for change detection","volume":"58","author":"Walter","year":"2004","journal-title":"ISPRS J. Photogramm."},{"key":"ref_3","unstructured":"Kressler, F.P., Franzen, M., and Steinnocher, K. (2005, January 17\u201320). Segmentation Based Classification of Aerial Images and Its Potential to Support the Update of Existing Land Use Data Bases. Proceedings of the ISPRS Hannover Workshop 2005: High-Resolution Earth Imaging for Geospatial Information, Hannover, Germany. Available online: http:\/\/www.isprs.org\/publications\/related\/hannover05\/paper\/papers.htm."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sanchez Hernandez, C., Gladstone, C., and Holland, D. (2007, January 11\u201313). Classification of Urban Features from Intergraph\u2019s Z\/I Imaging DMC High Resolution Images for Integration into a Change Detection Flowline within Ordnance Survey. Proceedings of the 2007 IEEE Urban Remote Sensing Joint Event, URBAN 2007-URS 2007, Paris, France.","DOI":"10.1109\/URS.2007.371798"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1109\/LGRS.2009.2035644","article-title":"Object classification of aerial images with bag-of-visual words","volume":"7","author":"Xu","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"162","DOI":"10.5589\/m06-015","article-title":"Object-oriented land cover classification of lidar-derived surfaces","volume":"32","author":"Brennan","year":"2006","journal-title":"Can. J. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"209","DOI":"10.2747\/1548-1603.45.2.209","article-title":"Object-based land cover classification using high-posting-density LiDAR data","volume":"45","author":"Im","year":"2008","journal-title":"GISci. Remote Sens."},{"key":"ref_8","unstructured":"Chehata, N., Guo, L., and Mallet, C. (2009, January 1\u20132). Airborne Lidar Feature Selection for Urban Classification Using Random Forests. Proceedings of the ISPRS Workshop: Laserscanning\u201909, Paris, France. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences."},{"key":"ref_9","unstructured":"Garcia-Gutierrez, J., Gon\u00e7alves-Seco, L., and Riquelme-Santos, J.C. (2009, January 1\u20132). Decision Trees on Lidar to Classify Land Uses and Covers. Proceedings of the ISPRS Workshop: Laserscanning\u201909, Paris, France. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5589\/m02-075","article-title":"A rule-based urban land use inferring method for fine-resolution multispectral imagery","volume":"29","author":"Zhang","year":"2003","journal-title":"Can. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Blaschke, T., Lang, S., and Hay, G.J. (2008). Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications, Springer.","DOI":"10.1007\/978-3-540-77058-9"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"77","DOI":"10.5589\/m08-016","article-title":"Determining land-use information from land cover through an object-oriented classification of IKONOS imagery","volume":"34","author":"Lackner","year":"2008","journal-title":"Can. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"397","DOI":"10.14358\/PERS.75.4.397","article-title":"An assessment of geometric activity features for per-pixel classification of urban man-made objects using very high resolution satellite imagery","volume":"75","author":"Chan","year":"2009","journal-title":"Photogramm. Eng. Remote Sensing"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3198","DOI":"10.1109\/TGRS.2010.2044508","article-title":"Rule-based classification of a very high resolution image in an urban environment using multispectral segmentation guided by cartographic data","volume":"48","author":"Bouziani","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"248","DOI":"10.5589\/m10-042","article-title":"Urban land cover classification from very high resolution imagery using spectral and invariant moment shape information","volume":"36","author":"Xu","year":"2010","journal-title":"Can. J. Remote Sens."},{"key":"ref_16","unstructured":"Corr, D.G., Walker, A., Benz, U., Lingenfelder, I., and Rodrigues, A. (2003, January 21\u201325). Classification of Urban SAR Imagery Using Object Oriented Techniques. Proceedings of IGARSS \u201903, Toulouse, France."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1109\/LGRS.2009.2020070","article-title":"Coarse-to-fine approach for urban area interpretation using TerraSAR-X data","volume":"7","author":"Datcu","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"236","DOI":"10.5589\/m10-046","article-title":"Urban land cover classification with high-resolution polarimetric SAR interferometric data","volume":"36","author":"Li","year":"2010","journal-title":"Can. J. Remote Sens."},{"key":"ref_19","unstructured":"Niu, X., and Ban, Y. (2010, January 5\u20137). Multitemporal RADARSAT-2 Polarimetric SAR Data for Urban Land-Cover Mapping. Proceedings of the ISPRS Technical Commission VII Symposium: 100 Years ISPRS Advancing Remote Sensing Science, Vienna, Austria. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences."},{"key":"ref_20","unstructured":"Qi, Z., Yeh, A.G., Li, X., and Lin, Z. (2010, January 5\u20137). Land Use and Land Cover Classification Using RADARSAT-2 Polarimetric SAR Image. Proceedings of the ISPRS Technical Commission VII Symposium: 100 Years ISPRS Advancing Remote Sensing Science, Vienna, Austria. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4439","DOI":"10.1080\/01431160110114952","article-title":"Joint analysis of SAR, LIDAR and aerial imagery for simultaneous extraction of land cover, DTM and 3D shape of buildings","volume":"23","author":"Gamba","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1473","DOI":"10.14358\/PERS.74.12.1473","article-title":"A knowledge-based approach to urban feature classification using aerial imagery with lidar data","volume":"74","author":"Huang","year":"2008","journal-title":"Photogramm. Eng. Remote Sensing"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1016\/j.asr.2008.11.008","article-title":"Hierarchical object oriented classification using very high resolution imagery and LIDAR data over urban areas","volume":"43","author":"Chen","year":"2009","journal-title":"Adv. Space Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1080\/01431160903475415","article-title":"Fusion of Quickbird MS and RADARSAT SAR data for urban land-cover mapping: Object-based and knowledge-based approach","volume":"31","author":"Ban","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","unstructured":"Bellmann, A., and Hellwich, O. (2006). EuroSDR Official Publication No 50, EuroSDR."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1109\/36.298006","article-title":"Multisource classification of remotely sensed data: Fusion of Landsat TM and SAR images","volume":"32","author":"Jain","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2101","DOI":"10.1080\/01431160050021321","article-title":"The study of ERS-1 SAR and Landsat TM synergism for land use classification","volume":"21","author":"Kuplich","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1080\/01431160600784267","article-title":"The integrated use of optical and InSAR data for urban land-cover mapping","volume":"28","author":"Amarsaikhan","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1109\/LGRS.2008.915939","article-title":"Urban mapping using coarse SAR and optical data: Outcome of the 2007 GRSS data fusion contest","volume":"5","author":"Pacifici","year":"2008","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Blaschke, T., Lang, S., and Hay, G.J. (2008). Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications, Springer.","DOI":"10.1007\/978-3-540-77058-9"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1515\/FREQ.2001.55.3-4.129","article-title":"Fusion of SAR\/INSAR data and optical imagery for landuse classification","volume":"55","author":"Hellwich","year":"2001","journal-title":"Frequenz"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1080\/19479830903562041","article-title":"Fusing high-resolution SAR and optical imagery for improved urban land cover study and classification","volume":"1","author":"Amarsaikhan","year":"2010","journal-title":"Int. J. Image Data Fusion"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/S0924-2716(99)00010-6","article-title":"Extraction of buildings and trees in urban environments","volume":"54","author":"Haala","year":"1999","journal-title":"ISPRS J. Photogramm."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"973","DOI":"10.14358\/PERS.69.9.973","article-title":"Synergistic use of lidar and color aerial photography for mapping urban parcel imperviousness","volume":"69","author":"Hodgson","year":"2003","journal-title":"Photogramm. Eng. Remote Sensing"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.inffus.2004.06.004","article-title":"Using the Dempster-Shafer method for the fusion of LIDAR data and multi-spectral images for building detection","volume":"6","author":"Rottensteiner","year":"2005","journal-title":"Inf. Fusion"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3119","DOI":"10.1080\/01431160701469065","article-title":"An object-oriented approach for analysing and characterizing urban landscape at the parcel level","volume":"29","author":"Zhou","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_37","first-page":"28","article-title":"Detecting buildings and roads from IKONOS data using additional elevation information","volume":"6","author":"Hofmann","year":"2001","journal-title":"GeoBITGIS"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1109\/TGE.1976.294460","article-title":"Classification of multispectral image data by extraction and classification of homogeneous objects","volume":"GE-14","author":"Kettig","year":"1976","journal-title":"IEEE Trans. Geosci. Electron."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Blaschke, T., Lang, S., and Hay, G.J. (2008). Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications, Springer.","DOI":"10.1007\/978-3-540-77058-9"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm."},{"key":"ref_41","unstructured":"Addink, E.A., and Van Coillie, F.M.B. (July, January 29). Geographic Object-Based Image Analysis. Proceedings of GEOBIA 2010, Ghent, Belgium. Available online: http:\/\/geobia.ugent.be\/proceedings\/."},{"key":"ref_42","unstructured":"Breiman, L., Friedman, J.H., Olshen, R.A., and Stone, C.J. (1984). Classification and Regression Trees, Wadsworth, Inc."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/S0034-4257(97)00049-7","article-title":"Decision tree classification of land cover from remotely sensed data","volume":"61","author":"Friedl","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_44","first-page":"1137","article-title":"Rule-based classification systems using classification and regression tree (CART) analysis","volume":"67","author":"Lawrence","year":"2001","journal-title":"Photogramm. Eng. Remote Sensing"},{"key":"ref_45","unstructured":"Mancini, A., Frontoni, E., and Zingaretti, P. (2009, January 3\u20134). Automatic Extraction of Urban Objects from Multi-Source Aerial Data. Proceedings of CMRT09: Object Extraction for 3D City Models, Road Databases and Traffic Monitoring\u2014Concepts, Algorithms and Evaluation, Paris, France. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences."},{"key":"ref_46","first-page":"5","article-title":"Improving automation in rule-based interpretation of remotely sensed data by using classification trees","volume":"20","author":"Matikainen","year":"2006","journal-title":"Photogramm. J. Fin."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1217","DOI":"10.3390\/rs2051217","article-title":"Automatic detection of buildings and changes in buildings for updating of maps","volume":"2","author":"Matikainen","year":"2010","journal-title":"Remote Sens."},{"key":"ref_48","first-page":"47","article-title":"Rule-based interpretation of high-resolution SAR images for map updating","volume":"19","author":"Matikainen","year":"2004","journal-title":"Photogramm. J. Fin."},{"key":"ref_49","unstructured":"Available online: http:\/\/www.terrasolid.fi\/."},{"key":"ref_50","unstructured":"Strobl, J., Blaschke, T., and Griesebner, G. (2000). Angewandte Geographische Informationsverarbeitung XII: Beitr\u00e4ge zum AGIT-Symposium Salzburg 2000, Wichmann."},{"key":"ref_51","unstructured":"Available online: http:\/\/www.ecognition.com\/."},{"key":"ref_52","unstructured":"Available online: http:\/\/www.mathworks.com\/."},{"key":"ref_53","unstructured":"The MathWorks (2007). Online Documentation for Statistics Toolbox, The MathWorks, Inc.. Version 6.1."},{"key":"ref_54","unstructured":"Definiens (2010). Definiens eCognition 8.0.1 Reference Book, Definiens AG."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Congalton, R.G., and Green, K. (1999). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Lewis Publishers.","DOI":"10.1201\/9781420048568"},{"key":"ref_56","unstructured":"Helld\u00e9n, U. (1980). A Test of Landsat-2 Imagery and Digital Data for Thematic Mapping, Illustrated by an Environmental Study in Northern Kenya, University of Lund. Rapporter och Notiser 47."},{"key":"ref_57","unstructured":"Schreier, G. (1993). SAR Geocoding: Data and Systems, Wichmann."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.rse.2004.01.007","article-title":"Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis","volume":"90","author":"Lawrence","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"3317","DOI":"10.1109\/TGRS.2007.900693","article-title":"TanDEM-X: A satellite formation for high-resolution SAR interferometry","volume":"45","author":"Krieger","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Matikainen, L., Hyypp\u00e4, J., Ahokas, E., Markelin, L., and Kaartinen, H. (2009, January 1\u20132). An Improved Approach for Automatic Detection of Changes in Buildings. Proceedings of the ISPRS Workshop: Laserscanning\u201909, Paris, France. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences.","DOI":"10.3390\/rs2051217"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/3\/8\/1777\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:57:08Z","timestamp":1760219828000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/3\/8\/1777"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,8,19]]},"references-count":61,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2011,8]]}},"alternative-id":["rs3081777"],"URL":"https:\/\/doi.org\/10.3390\/rs3081777","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,8,19]]}}}