{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T18:18:15Z","timestamp":1786040295527,"version":"3.56.0"},"reference-count":60,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2014,4,25]],"date-time":"2014-04-25T00:00:00Z","timestamp":1398384000000},"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>Remote sensing technologies have been commonly used to perform greenhouse detection and mapping. In this research, stereo pairs acquired by very high-resolution optical satellites GeoEye-1 (GE1) and WorldView-2 (WV2) have been utilized to carry out the land cover classification of an agricultural area through an object-based image analysis approach, paying special attention to greenhouses extraction. The main novelty of this work lies in the joint use of single-source stereo-photogrammetrically derived heights and multispectral information from both panchromatic and pan-sharpened orthoimages. The main features tested in this research can be grouped into different categories, such as basic spectral information, elevation data (normalized digital surface model; nDSM), band indexes and ratios, texture and shape geometry. Furthermore, spectral information was based on both single orthoimages and multiangle orthoimages. The overall accuracy attained by applying nearest neighbor and support vector machine classifiers to the four multispectral bands of GE1 were very similar to those computed from WV2, for either four or eight multispectral bands. Height data, in the form of nDSM, were the most important feature for greenhouse classification. The best overall accuracy values were close to 90%, and they were not improved by using multiangle orthoimages.<\/jats:p>","DOI":"10.3390\/rs6053554","type":"journal-article","created":{"date-parts":[[2014,4,28]],"date-time":"2014-04-28T05:15:00Z","timestamp":1398662100000},"page":"3554-3582","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":74,"title":["Object-Based Greenhouse Classification from GeoEye-1 and WorldView-2 Stereo Imagery"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0404-9875","authenticated-orcid":false,"given":"Manuel","family":"Aguilar","sequence":"first","affiliation":[{"name":"Department of Engineering, University of Almer\u00eda, Ctra. de Sacramento s\/n, La Ca\u00f1ada de San Urbano, E-04120 Almer\u00eda, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Bianconi","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5144-6411","authenticated-orcid":false,"given":"Fernando","family":"Aguilar","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Almer\u00eda, Ctra. de Sacramento s\/n, La Ca\u00f1ada de San Urbano, E-04120 Almer\u00eda, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ismael","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Almer\u00eda, Ctra. de Sacramento s\/n, La Ca\u00f1ada de San Urbano, E-04120 Almer\u00eda, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2014,4,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1177\/8756087906064220","article-title":"Plastic films for agricultural applications","volume":"22","author":"Espi","year":"2006","journal-title":"J. Plast. Film Sheeting"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1080\/01431160600658156","article-title":"Remote sensing as a tool for monitoring plasticulture in agricultural landscapes","volume":"28","author":"Levin","year":"2007","journal-title":"Int. J. Remote Sens"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.biosystemseng.2007.11.016","article-title":"Decision modelling for environmental protection: The contingent valuation method applied to greenhouse waste management","volume":"99","author":"Parra","year":"2008","journal-title":"Biosyst. Eng"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.biosystemseng.2010.07.007","article-title":"A model to manage crop-shelter spatial development by multi-temporal coverage analysis and spatial indicators","volume":"107","author":"Arcidiacono","year":"2010","journal-title":"Biosyst. Eng"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1016\/j.isprsjprs.2008.03.003","article-title":"Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses","volume":"63","author":"Aguilar","year":"2008","journal-title":"ISPRS J. Photogramm. Remote Sens"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.landurbplan.2010.11.008","article-title":"Analysis of plasticulture landscapes in Southern Italy through remote sensing and solid modelling techniques","volume":"100","author":"Picuno","year":"2011","journal-title":"Landsc. Urban Plan"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"4751","DOI":"10.1080\/01431160600702681","article-title":"Detecting greenhouse changes from QB imagery on the Mediterranean Coast","volume":"27","author":"Aguilar","year":"2006","journal-title":"Int. J. Remote Sens"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Liu, J.G., and Mason, P. (2009). Essential Image Processing and GIS for Remote Sensing, Wiley.","DOI":"10.1002\/9781118687963"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1913","DOI":"10.3390\/rs4071913","article-title":"Mapping rural areas with widespread plastic covered vineyards using true color aerial data","volume":"4","author":"Tarantino","year":"2012","journal-title":"Remote Sens"},{"key":"ref_10","unstructured":"Van der Wel, F.J.M. (2000). Assessment and Visualisation of Uncertainty in Remote Sensing Land Cover Classifications. Ph.D. Thesis."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Donnay, J.-P., Barnsley, M.J., and Longley, P.A. (2000). Remote Sensing and Urban Analysis, Taylor & Francis.","DOI":"10.1201\/9781482268119"},{"key":"ref_12","first-page":"363","article-title":"Utilizing landsat TM imagery to map greenhouses in Qingzhou, Shandong Province, China","volume":"14","author":"Zhao","year":"2004","journal-title":"Pedosphere"},{"key":"ref_13","unstructured":"Cuadrado, I.M. (2004). Estudio Multitemporal Sobre la Evoluci\u00f3n de la Superficie Invernada en la Provincia de Almer\u00eda por T\u00e9rminos Municipales Desde 1984 Hasta 2004: Mediante Teledetecci\u00f3n de Im\u00e1genes Thematic Mapper de los Sat\u00e9lites Landsat V y VII, Fundaci\u00f3n para la Investigaci\u00f3n Agraria de la Provincia de Almer\u00eda."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2977","DOI":"10.1080\/01431160902946580","article-title":"Relationship between atmospheric correction and training site strategy with respect to accuracy of greenhouse detection process from very high resolution imagery","volume":"31","author":"Carvajal","year":"2010","journal-title":"Int. J. Remote Sens"},{"key":"ref_15","first-page":"9","article-title":"Improving per-pixel classification of crop-shelter coverage by texture analyses of high-resolution satellite panchromatic images","volume":"4","author":"Arcidiacono","year":"2011","journal-title":"J. Agric. Eng"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.17660\/ActaHortic.2012.937.124","article-title":"Pixel-based classification of high-resolution satellite images for crop-shelter coverage recognition","volume":"937","author":"Arcidiacono","year":"2012","journal-title":"Acta Hortic"},{"key":"ref_17","first-page":"1071","article-title":"Accuracy of crop-shelter thematic maps: A case study of maps obtained by spectral and textural classification of high-resolution satellite images","volume":"10","author":"Arcidiacono","year":"2012","journal-title":"J. Food Agric. Environ"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.14358\/PERS.77.10.1011","article-title":"Building extraction and rubble mapping for city port-au-prince post-2010 earthquake with GeoEye-1 imagery and lidar data","volume":"77","author":"Hussain","year":"2011","journal-title":"Photogramm. Eng. Remote Sens"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1155","DOI":"10.1109\/TGRS.2011.2165548","article-title":"Very high resolution multiangle urban classification analysis","volume":"50","author":"Longbotham","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2583","DOI":"10.1080\/01431161.2012.747018","article-title":"GeoEye-1 and WorldView-2 pansharpened imagery for object-based classification in urban environments","volume":"34","author":"Aguilar","year":"2013","journal-title":"Int. J. Remote Sens"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.cageo.2012.12.007","article-title":"Object oriented image analysis based on multi-agent recognition system","volume":"54","author":"Mahmoudi","year":"2013","journal-title":"Comput. Geosci"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Koc-San, D. (2013). Evaluation of different classification techniques for the detection of glass and plastic greenhouses from WorldView-2 satellite imagery. J. Appl. Remote Sens, 7.","DOI":"10.1117\/1.JRS.7.073553"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1080\/014311698215748","article-title":"Review article Multisensor image fusion in remote sensing: Concepts, methods and applications","volume":"19","author":"Pohl","year":"1998","journal-title":"Int. J. Remote Sens"},{"key":"ref_24","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_25","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.14358\/PERS.76.10.1159","article-title":"Land cover classification in a complex urban-rural landscape with QuickBird imagery","volume":"76","author":"Lu","year":"2010","journal-title":"Photogramm. Eng. Remote Sens"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/j.rse.2010.12.017","article-title":"Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery","volume":"115","author":"Myint","year":"2011","journal-title":"Remote Sens. Environ"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.rse.2011.02.030","article-title":"Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends","volume":"117","author":"Weng","year":"2012","journal-title":"Remote Sens. Environ"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4081\/jae.2010.3.1","article-title":"Classification of crop-shelter coverage by RGB aerial images: A compendium of experiences and findings","volume":"3","author":"Arcidiacono","year":"2010","journal-title":"J. Agric. Eng"},{"key":"ref_29","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. Remote Sens"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.3390\/rs3061188","article-title":"Evaluation of automatic building detection approaches combining high resolution images and LiDAR data","volume":"3","author":"Hermosilla","year":"2011","journal-title":"Remote Sens"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.isprsjprs.2010.06.001","article-title":"Automatic detection of residential buildings using LiDAR data and multispectral imagery","volume":"65","author":"Awrangjeb","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens"},{"key":"ref_32","first-page":"6347","article-title":"Accuracy assessment of digital surface models based on WorldView-2 and ADS80 stereo remote sensing data","volume":"4","author":"Hobi","year":"2012","journal-title":"Remote Sens"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1007\/s11069-013-0583-4","article-title":"3D modeling of large urban areas with stereo VHR satellite imagery: Lessons learned","volume":"68","author":"Poli","year":"2013","journal-title":"Nat. Hazards"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1259","DOI":"10.1109\/TGRS.2013.2249521","article-title":"Generation and quality assessment of stereo-extracted DSM from GeoEye-1 and WorldView-2 imagery","volume":"52","author":"Aguilar","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"4193","DOI":"10.1080\/01431161.2011.640963","article-title":"A model-based approach for automatic building database updating from high-resolution space imagery","volume":"33","author":"Turker","year":"2012","journal-title":"Int. J. Remote Sens"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1109\/TGRS.2013.2240692","article-title":"Building change detection based on satellite stereo imagery and digital surface models","volume":"52","author":"Tian","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2857","DOI":"10.1109\/TGRS.2008.2000741","article-title":"Hyperspectral and multiangle CHRIS-PROBA images for the generation of land cover maps","volume":"46","author":"Duca","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_38","first-page":"427","article-title":"Assessing geometric accuracy of the orthorectification process from GeoEye-1 and WorldView-2 panchromatic images","volume":"21","author":"Aguilar","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1080\/01431160500297956","article-title":"Urban land cover multi-level region-based classification of VHR data by selecting relevant features","volume":"27","author":"Carleer","year":"2006","journal-title":"Int. J. Remote Sens"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"4981","DOI":"10.1080\/01431160500213912","article-title":"A competitive pixel-object approach for land cover classification","volume":"26","author":"Song","year":"2005","journal-title":"Int. J. Remote Sens"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1080\/01431161003743173","article-title":"Assessing object-based classification: advantages and limitations","volume":"1","author":"Liu","year":"2010","journal-title":"Remote Sens. Lett"},{"key":"ref_42","unstructured":"Definiens eCognition (2009). Definiens eCognition Developer 8 Reference Book, Definiens AG."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2236","DOI":"10.1080\/01431161.2012.743694","article-title":"Using WorldView-2 bands and indices to predict bronze bug (Thaumastocoris peregrinus) damage in plantation forests","volume":"34","author":"Oumar","year":"2013","journal-title":"Int. J. Remote Sens"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","volume":"3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1109\/TGRS.1995.8746010","article-title":"An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters","volume":"33","author":"Baraldi","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2564","DOI":"10.1016\/j.rse.2011.05.013","article-title":"Object-oriented mapping of landslides using random forests","volume":"115","author":"Stumpf","year":"2011","journal-title":"Remote Sens. Environ"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1016\/j.rse.2012.06.011","article-title":"A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species","volume":"124","author":"Pu","year":"2012","journal-title":"Remote Sens. Environ"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1109\/TGRS.2004.827257","article-title":"A relative evaluation of multiclass image classification by support vector machines","volume":"42","author":"Foody","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1778","DOI":"10.1109\/TGRS.2004.831865","article-title":"Classification of hyperspectral remote sensing images with support vector machines","volume":"42","author":"Melgani","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2058","DOI":"10.1109\/JSTARS.2013.2240265","article-title":"Non-parametric object-based approaches to carry out ISA classification from archival aerial orthoimages","volume":"6","author":"Aguilar","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.rse.2006.04.001","article-title":"The use of small training sets containing mixed pixels for accurate hard image classification: Training on mixed spectral responses for classification by a SVM","volume":"103","author":"Foody","year":"2006","journal-title":"Remote Sens. Environ"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2731","DOI":"10.1016\/j.patcog.2008.04.013","article-title":"Statistical pattern recognition in remote sensing","volume":"41","author":"Chen","year":"2008","journal-title":"Pattern Recognit"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Vapnik, V.N. (1995). The Nature of Statistical Learning Theory, Springer-Verlag.","DOI":"10.1007\/978-1-4757-2440-0"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A review of assessing the accuracy of classifications of remotely sensed data","volume":"37","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1109\/TGRS.2009.2027702","article-title":"Automatic mapping of linear woody vegetation features in agricultural landscapes using very high-resolution imagery","volume":"48","author":"Aksoy","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_57","first-page":"1","article-title":"Stereo processing by semiglobal matching and mutual information","volume":"30","year":"2008","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"309","DOI":"10.17660\/ActaHortic.2008.801.31","article-title":"Image processing for the classification of crop shelters","volume":"801","author":"Arcidiacono","year":"2008","journal-title":"Acta Hortic"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Marchisio, G., Pacifici, F., and Padwick, C. (2010, January 25\u201330). On the Relative Predictive Value of the New Spectral Bands in the WorldView-2 Sensor. Honolulu, HI, USA.","DOI":"10.1109\/IGARSS.2010.5649771"},{"key":"ref_60","unstructured":"Marshall, V., Lewis, M., and Ostendorf, B. (September, January 25). Do Additional Bands (Coastal, Nir-2, Red-Edge and Yellow) in WorldView-2 Multispectral Imagery Improve Discrimination of an Invasive Tussock, Buffel Grass (Cenchrus Ciliaris)?. Melbourne, Australia."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/5\/3554\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:10:43Z","timestamp":1760217043000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/5\/3554"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,4,25]]},"references-count":60,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2014,5]]}},"alternative-id":["rs6053554"],"URL":"https:\/\/doi.org\/10.3390\/rs6053554","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,4,25]]}}}