{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:49:30Z","timestamp":1760240970774,"version":"build-2065373602"},"reference-count":73,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2019,10,31]],"date-time":"2019-10-31T00:00:00Z","timestamp":1572480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Universidad de Almer\u00eda and the Universidad de La Laguna","award":["2019\/006 and 2018\/0001440"],"award-info":[{"award-number":["2019\/006 and 2018\/0001440"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study analyzes the potential of very high resolution (VHR) remote sensing images and extended morphological profiles for mapping Chestnut stands on Tenerife Island (Canary Islands, Spain). Regarding their relevance for ecosystem services in the region (cultural and provisioning services) the public sector demand up-to-date information on chestnut and a simple straight-forward approach is presented in this study. We used two VHR WorldView images (March and May 2015) to cover different phenological phases. Moreover, we included spatial information in the classification process by extended morphological profiles (EMPs). Random forest is used for the classification process and we analyzed the impact of the bi-temporal information as well as of the spatial information on the classification accuracies. The detailed accuracy assessment clearly reveals the benefit of bi-temporal VHR WorldView images and spatial information, derived by EMPs, in terms of the mapping accuracy. The bi-temporal classification outperforms or at least performs equally well when compared to the classification accuracies achieved by the mono-temporal data. The inclusion of spatial information by EMPs further increases the classification accuracy by 5% and reduces the quantity and allocation disagreements on the final map. Overall the new proposed classification strategy proves useful for mapping chestnut stands in a heterogeneous and complex landscape, such as the municipality of La Orotava, Tenerife.<\/jats:p>","DOI":"10.3390\/rs11212560","type":"journal-article","created":{"date-parts":[[2019,10,31]],"date-time":"2019-10-31T06:33:29Z","timestamp":1572503609000},"page":"2560","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Mapping Chestnut Stands Using Bi-Temporal VHR Data"],"prefix":"10.3390","volume":"11","author":[{"given":"Francesca","family":"Marchetti","sequence":"first","affiliation":[{"name":"Departamento de F\u00edsica, Universidad de La Laguna, 38200 San Crist\u00f3bal de La Laguna, Spain"}]},{"given":"Bj\u00f6rn","family":"Waske","sequence":"additional","affiliation":[{"name":"Remote Sensing Working Group, Institute of Computer Science, University of Osnabr\u00fcck, 49090 Osnabr\u00fcck, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6853-4442","authenticated-orcid":false,"given":"Manuel","family":"Arbelo","sequence":"additional","affiliation":[{"name":"Departamento de F\u00edsica, Universidad de La Laguna, 38200 San Crist\u00f3bal de La Laguna, Spain"}]},{"given":"Jose","family":"Moreno-Ru\u00edz","sequence":"additional","affiliation":[{"name":"Departamento de Inform\u00e1tica, Universidad of Almer\u00eda, 04120 Almer\u00eda, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2204-2936","authenticated-orcid":false,"given":"Alfonso","family":"Alonso-Benito","sequence":"additional","affiliation":[{"name":"Departamento de F\u00edsica, Universidad de La Laguna, 38200 San Crist\u00f3bal de La Laguna, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,31]]},"reference":[{"key":"ref_1","unstructured":"European Environment Agency (2018, September 23). 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