{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T17:11:05Z","timestamp":1778433065442,"version":"3.51.4"},"reference-count":57,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,3,18]],"date-time":"2019-03-18T00:00:00Z","timestamp":1552867200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Ministry of Business Innovation &amp; Employment (New Zealand)","award":["C09X1709"],"award-info":[{"award-number":["C09X1709"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Image classification and interpretation are greatly aided through the use of image segmentation. Within the field of environmental remote sensing, image segmentation aims to identify regions of unique or dominant ground cover from their attributes such as spectral signature, texture and context. However, many approaches are not scalable for national mapping programmes due to limits in the size of images that can be processed. Therefore, we present a scalable segmentation algorithm, which is seeded using k-means and provides support for a minimum mapping unit through an innovative iterative elimination process. The algorithm has also been demonstrated for the segmentation of time series datasets capturing both the intra-image variation and change regions. The quality of the segmentation results was assessed by comparison with reference segments along with statistics on the inter- and intra-segment spectral variation. The technique is computationally scalable and is being actively used within the national land cover mapping programme for New Zealand. Additionally, 30-m continental mosaics of Landsat and ALOS-PALSAR have been segmented for Australia in support of national forest height and cover mapping. The algorithm has also been made freely available within the open source Remote Sensing and GIS software Library (RSGISLib).<\/jats:p>","DOI":"10.3390\/rs11060658","type":"journal-article","created":{"date-parts":[[2019,3,18]],"date-time":"2019-03-18T12:18:53Z","timestamp":1552911533000},"page":"658","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["Operational Large-Scale Segmentation of Imagery Based on Iterative Elimination"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4809-0055","authenticated-orcid":false,"given":"James","family":"Shepherd","sequence":"first","affiliation":[{"name":"Landcare Research, Private Bag 11052, Palmerston North 4442, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7435-0148","authenticated-orcid":false,"given":"Pete","family":"Bunting","sequence":"additional","affiliation":[{"name":"Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Dymond","sequence":"additional","affiliation":[{"name":"Landcare Research, Private Bag 11052, Palmerston North 4442, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.isprsjprs.2007.03.003","article-title":"Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping","volume":"62","author":"Lucas","year":"2007","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.isprsjprs.2010.09.004","article-title":"Updating the Phase 1 habitat map of Wales, UK, using satellite sensor data","volume":"66","author":"Lucas","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_3","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. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1136","DOI":"10.1109\/36.628781","article-title":"Image segmentation and discriminant analysis for the identification of land cover units in ecology","volume":"35","author":"Lobo","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/S0034-4257(99)00083-8","article-title":"Integrating contextual information with per-pixel classification for improved land cover classification","volume":"71","author":"Stuckens","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1179\/caj.2002.39.1.15","article-title":"The UK Land Cover Map 2000: Construction of a parcel-based vector map from satellite images","volume":"39","author":"Fuller","year":"2002","journal-title":"Cartogr. J."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2973","DOI":"10.1109\/TGRS.2009.2016214","article-title":"Spectral-Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques","volume":"47","author":"Tarabalka","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","unstructured":"Definiens (2005). eCognition Version 5 Object Oriented Image Analysus User Guide, Definiens AG. Technical Report."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Carleer, A.P., Debeir, O., and Wolff, E. (2005). Assessment of Very High Spatial Resolution Satellite Image Segmentations. Photogramm. Eng. Remote Sens., 71.","DOI":"10.14358\/PERS.71.11.1285"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/0031-3203(81)90028-5","article-title":"A survey on image segmentation","volume":"13","author":"Fu","year":"1981","journal-title":"Pattern Recognit."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/S0734-189X(85)90153-7","article-title":"Image segmentation techniques","volume":"29","author":"Haralick","year":"1985","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.1016\/0031-3203(93)90135-J","article-title":"A review on image segmentation techniques","volume":"26","author":"Pal","year":"1993","journal-title":"Pattern Recognit."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2259","DOI":"10.1016\/S0031-3203(00)00149-7","article-title":"Color image segmentation: Advances and prospects","volume":"34","author":"Cheng","year":"2001","journal-title":"Pattern Recognit."},{"key":"ref_14","unstructured":"Dey, V., Zhang, Y., and Zhong, M. (2010, January 5\u20137). A review on image segmentation techniques with remote sensing perspective. Proceedings of the ISPRS TC VII Symposium\u2014100 Years ISPRS, Vienna, Austria."},{"key":"ref_15","unstructured":"Chen, Q., Luo, J., Zhou, C., and Pei, T. (2003, January 21\u201325). A hybrid multi-scale segmentation approach for remotely sensed imagery. Proceedings of the 2003 IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Tilton, J.C. (1998, January 6\u201310). Image segmentation by region growing and spectral clustering with a natural convergence criterion. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium Proceedings (IGARSS), Seattle, WA, USA.","DOI":"10.1109\/IGARSS.1998.703645"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1132","DOI":"10.1109\/TPAMI.2007.70817","article-title":"Constrained connectivity for hierarchical image partitioning and simplification","volume":"30","author":"Soille","year":"2008","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_18","first-page":"7","article-title":"A Novel Method for Segmentation of Remote Sensing Images based on Hybrid GAPSO","volume":"29","author":"Ghamisi","year":"2011","journal-title":"Int. J. Comput. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1016\/j.envsoft.2010.03.019","article-title":"An automatic region-based image segmentation algorithm for remote sensing applications","volume":"25","author":"Wang","year":"2010","journal-title":"Environ. Model. Softw."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Yang, Y., Han, C., and Han, D. (2008, January 7\u201311). A Markov Random Field Model-based Fusion Approach to Segmentation of SAR and Optical Images. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Boston, MA, USA.","DOI":"10.1109\/IGARSS.2008.4779844"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1016\/j.dsp.2011.07.002","article-title":"Spectral clustering with fuzzy similarity measure","volume":"21","author":"Zhao","year":"2011","journal-title":"Digit. Signal Process."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Tasdemir, K. (2011, January 24\u201329). Neural network based approximate spectral clustering for remote sensing images. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, BC, Canada.","DOI":"10.1109\/IGARSS.2011.6049817"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2367","DOI":"10.1016\/j.patcog.2010.01.016","article-title":"Segmentation and classification of hyperspectral images using watershed transformation","volume":"43","author":"Tarabalka","year":"2010","journal-title":"Pattern Recognit."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1016\/S0031-3203(01)00070-X","article-title":"Segmentation of SAR images","volume":"35","author":"Ziou","year":"2002","journal-title":"Pattern Recognit."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.1016\/j.imavis.2006.09.002","article-title":"Iterative area filtering of multichannel images","volume":"25","author":"Brunner","year":"2007","journal-title":"Image Vis. Comput."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Weber, J., Petitjean, F., and Gan\u00e7arski, P. (2012, January 22\u201327). Towards Efficient Satellite Image Time Series Analysis: Combination of Dynamic Time Warping and Quasi-Flat Zones. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6350401"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/S0098-3004(00)00110-2","article-title":"TIDA: An algorithm for the delineation of tree crowns in high spatial resolution remotely sensed imagery","volume":"28","author":"Culvenor","year":"2002","journal-title":"Comput. Geosci."},{"key":"ref_28","first-page":"12","article-title":"Multiresolution segmentation: An optimization approach for high quality multi-scale image segmentation","volume":"58","author":"Baatz","year":"2000","journal-title":"J. Photogramm. Remote Sens."},{"key":"ref_29","unstructured":"Lucchese, L., and Mitra, S.K. (1999, January 22). Unsupervised segmentation of color images based on k-means clustering in the chromaticity plane. Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries (CBAIVL\u201999), Fort Collins, CO, USA."},{"key":"ref_30","unstructured":"Rouse, J., Haas, R., Schell, J., and Deering, D. (1974, January 1). Monitoring vegetation systems in the Great Plains with ERTS. Proceedings of the NASA Goddard Space Flight Center, 3d ERTS-1 Symposium (NASA SP-351 I), Greenbelt, MD, USA."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.cviu.2007.08.003","article-title":"Image segmentation evaluation: A survey of unsupervised methods","volume":"110","author":"Zhang","year":"2008","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/j.rse.2017.11.024","article-title":"Supervised methods of image segmentation accuracy assessment in land cover mapping","volume":"205","author":"Costa","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_33","unstructured":"Novack, T., Fonseca, L., and Kux, H. (2008, January 5\u20138). Quantitative comparison of segmentation results from ikonos images sharpened by different fusion and interpolation techniques. Proceedings of the GEOgraphic Object Based Image Analysis for the 21st Century (GEOBIA), Calgary, AB, Canada."},{"key":"ref_34","unstructured":"Neubert, M., and Herold, H. (2006, January 4\u20135). Evaluation of remote sensing image segmentation quality\u2014Further results and concepts. Proceedings of the Bridging Remote Sensing and GIS 1st International Conference on Object-Based Image Analysis (OBIA), Salzburg, Austria."},{"key":"ref_35","unstructured":"Neubert, M., and Herold, H. (2008, January 5\u20138). Assessment of remote sensing image segmentation quality. Proceedings of the GEOgraphic Object Based Image Analysis for the 21st Century (GEOBIA), Calgary, AB, Canada."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.isprsjprs.2015.01.009","article-title":"Segmentation quality evaluation using region-based precision and recall measures for remote sensing images","volume":"102","author":"Zhang","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_37","unstructured":"Marcal, A.R.S., and Rodrigues, S.A. (2008, January 5\u20138). A framework for the evalulation of multi-spectral image segmentation. Proceedings of the GEOgraphic Object Based Image Analysis for the 21st Century (GEOBIA), Calgary, AB, Canada."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1016\/j.isprsjprs.2011.02.006","article-title":"Unsupervised image segmentation evaluation and refinement using a multi-scale approach","volume":"66","author":"Johnson","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3503","DOI":"10.1080\/01431160210154029","article-title":"Correcting satellite imagery for the variance of reflectance and illumination with topography","volume":"24","author":"Shepherd","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_40","first-page":"281","article-title":"Some methods for classification and analysis of multivariate observations","volume":"Volume 1","author":"MacQueen","year":"1967","journal-title":"Fifth Berkeley Symposium on Mathematical Statistics and Probability"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1002\/bs.3830120210","article-title":"A clustering technique for summarizing multivariate data","volume":"12","author":"Ball","year":"1967","journal-title":"Behav. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1109\/34.1000236","article-title":"Mean shift: A robust approach toward feature space analysis","volume":"24","author":"Comaniciu","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1080\/01621459.1963.10500845","article-title":"Hierarchical Grouping to Optimize an Objective Function","volume":"58","author":"Ward","year":"1963","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_44","unstructured":"Bezdek, J.C. (1963). Fuzzy Mathematics in Pattern Classification. [Ph.D. Thesis, Cornell University]."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.envsci.2011.11.011","article-title":"Remote sensing of land-use change for Kyoto Protocol reporting: The New Zealand case","volume":"16","author":"Dymond","year":"2012","journal-title":"Environ. Sci. Policy"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2013.11.025","article-title":"Mapping forest growth stage in the Brigalow Belt Bioregion of Australia through integration of ALOS PALSAR and Landsat-derived Foliage Projected Cover (FPC) data","volume":"155","author":"Lucas","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Michel, J., Feuvrier, T., and Inglada, J. (2009). Reference algorithm implementations in OTB: Textbook cases. IEEE Int. Geosci. Remote Sens. Symp.","DOI":"10.1109\/IGARSS.2009.5417483"},{"key":"ref_48","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. Soc. Newsl."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"4758","DOI":"10.1080\/01431161.2014.930199","article-title":"Object-based change detection in wind storm-damaged forest using high-resolution multispectral images","volume":"35","author":"Chehata","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Bellakanji, A.C., Zribi, M., Lili-Chabaane, Z., and Mougenot, B. (2018). Forecasting of Cereal Yields in a Semi-arid Area Using the Simple Algorithm for Yield Estimation (SAFY) Agro-Meteorological Model Combined with Optical SPOT\/HRV Images. Sensors, 18.","DOI":"10.3390\/s18072138"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2240","DOI":"10.1109\/JSTARS.2015.2416656","article-title":"Benchmarking of remote sensing segmentation methods","volume":"8","author":"Mikes","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Vedaldi, A., and Soatto, S. (2008). Quick shift and kernel methods for mode seeking. European Conference on Computer Vision, Springer.","DOI":"10.1007\/978-3-540-88693-8_52"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1023\/B:VISI.0000022288.19776.77","article-title":"Efficient graph-based image segmentation","volume":"59","author":"Felzenszwalb","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.cageo.2013.08.007","article-title":"The Remote Sensing and GIS Software Library (RSGISLib)","volume":"62","author":"Bunting","year":"2014","journal-title":"Comput. Geosci."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Scarth, P., Armston, J., Lucas, R., and Bunting, P. (2019). A Structural Classification of Australian Vegetation Using ICESat\/GLAS, ALOS PALSAR, and Landsat Sensor Data. Remote Sens., 11.","DOI":"10.3390\/rs11020147"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"6111","DOI":"10.3390\/rs6076111","article-title":"A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA) Utilizing Raster Attribute Tables","volume":"6","author":"Clewley","year":"2014","journal-title":"Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.cageo.2013.03.025","article-title":"The KEA image file format","volume":"57","author":"Bunting","year":"2013","journal-title":"Comput. Geosci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/6\/658\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:38:46Z","timestamp":1760186326000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/6\/658"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,18]]},"references-count":57,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2019,3]]}},"alternative-id":["rs11060658"],"URL":"https:\/\/doi.org\/10.3390\/rs11060658","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,18]]}}}