{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T04:13:01Z","timestamp":1784002381534,"version":"3.55.0"},"reference-count":56,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2016,6,18]],"date-time":"2016-06-18T00:00:00Z","timestamp":1466208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Economy and Competitiveness (Spain) and the European Union (European Regional Development Fund, ERDF) funds","award":["AGL2014-56017-R"],"award-info":[{"award-number":["AGL2014-56017-R"]}]},{"name":"Agrifood Campus of International Excellence","award":["ceiA3"],"award-info":[{"award-number":["ceiA3"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Greenhouse mapping through remote sensing has received extensive attention over the last decades. In this article, the innovative goal relies on mapping greenhouses through the combined use of very high resolution satellite data (WorldView-2) and Landsat 8 Operational Land Imager (OLI) time series within a context of an object-based image analysis (OBIA) and decision tree classification. Thus, WorldView-2 was mainly used to segment the study area focusing on individual greenhouses. Basic spectral information, spectral and vegetation indices, textural features, seasonal statistics and a spectral metric (Moment Distance Index, MDI) derived from Landsat 8 time series and\/or WorldView-2 imagery were computed on previously segmented image objects. In order to test its temporal stability, the same approach was applied for two different years, 2014 and 2015. In both years, MDI was pointed out as the most important feature to detect greenhouses. Moreover, the threshold value of this spectral metric turned to be extremely stable for both Landsat 8 and WorldView-2 imagery. A simple decision tree always using the same threshold values for features from Landsat 8 time series and WorldView-2 was finally proposed. Overall accuracies of 93.0% and 93.3% and kappa coefficients of 0.856 and 0.861 were attained for 2014 and 2015 datasets, respectively.<\/jats:p>","DOI":"10.3390\/rs8060513","type":"journal-article","created":{"date-parts":[[2016,6,20]],"date-time":"2016-06-20T12:51:28Z","timestamp":1466427088000},"page":"513","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":90,"title":["Object-Based Greenhouse Mapping Using Very High Resolution Satellite Data and Landsat 8 Time Series"],"prefix":"10.3390","volume":"8","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, Almer\u00eda 04120, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abderrahim","family":"Nemmaoui","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Almer\u00eda, Ctra. de Sacramento s\/n, La Ca\u00f1ada de San Urbano, Almer\u00eda 04120, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5671-9220","authenticated-orcid":false,"given":"Antonio","family":"Novelli","sequence":"additional","affiliation":[{"name":"Politecnico di Bari, via Orabona n. 4, I-70125 Bari, 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, Almer\u00eda 04120, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andr\u00e9s","family":"Garc\u00eda Lorca","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Almer\u00eda, Ctra Sacramento s\/n, La Ca\u00f1ada de San Urbano, Almer\u00eda 04120, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2016,6,18]]},"reference":[{"key":"ref_1","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. 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