{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T14:51:07Z","timestamp":1770907867043,"version":"3.50.1"},"reference-count":65,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,10,8]],"date-time":"2024-10-08T00:00:00Z","timestamp":1728345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Recovery and Resilience Plan (NRRP)","award":["CN_00000033"],"award-info":[{"award-number":["CN_00000033"]}]},{"name":"National Recovery and Resilience Plan (NRRP)","award":["CUP J83C20001990005"],"award-info":[{"award-number":["CUP J83C20001990005"]}]},{"name":"Project PRIN 2020, Sector ERC LS9 Call 2020 Prot. 2020 EMLWTN","award":["CN_00000033"],"award-info":[{"award-number":["CN_00000033"]}]},{"name":"Project PRIN 2020, Sector ERC LS9 Call 2020 Prot. 2020 EMLWTN","award":["CUP J83C20001990005"],"award-info":[{"award-number":["CUP J83C20001990005"]}]},{"name":"Ministry of University and Research (MUR)","award":["CN_00000033"],"award-info":[{"award-number":["CN_00000033"]}]},{"name":"Ministry of University and Research (MUR)","award":["CUP J83C20001990005"],"award-info":[{"award-number":["CUP J83C20001990005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urban trees support vital ecological functions and help with the mitigation of and adaption to climate change. Yet, their monitoring and management require significant public resources. remote sensing could facilitate these tasks. Recent hyperspectral satellite programs such as PRISMA have enabled more advanced remote sensing applications, such as species classification. However, PRISMA data\u2019s spatial resolution (30 m) could limit its utility in urban areas. Improving hyperspectral data resolution with pansharpening using the PRISMA coregistered panchromatic band (spatial resolution of 5 m) could solve this problem. This study addresses the need to improve hyperspectral data resolution and tests the pansharpening method by classifying exemplative urban tree species in Naples (Italy) using a convolutional neural network and a ground truths dataset, with the aim of comparing results from the original 30 m data to data refined to a 5 m resolution. An evaluation of accuracy metrics shows that pansharpening improves classification quality in dense urban areas with complex topography. In fact, pansharpened data led to significantly higher accuracy for all the examined species. Specifically, the Pinus pinea and Tilia x europaea classes showed an increase of 10% to 20% in their F1 scores. Pansharpening is seen as a practical solution to enhance PRISMA data usability in urban environments.<\/jats:p>","DOI":"10.3390\/rs16193730","type":"journal-article","created":{"date-parts":[[2024,10,8]],"date-time":"2024-10-08T12:03:49Z","timestamp":1728389029000},"page":"3730","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Testing the Impact of Pansharpening Using PRISMA Hyperspectral Data: A Case Study Classifying Urban Trees in Naples, Italy"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7671-9904","authenticated-orcid":false,"given":"Miriam","family":"Perretta","sequence":"first","affiliation":[{"name":"Department of Architecture, University of Naples Federico II, Via Forno Vecchio, 36, 80134 Naples, Italy"},{"name":"NBFC, National Biodiversity Future Center, 90133 Palermo, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8642-9468","authenticated-orcid":false,"given":"Gabriele","family":"Delogu","sequence":"additional","affiliation":[{"name":"Department of Economics, Engineering, Society and Business Organization (DEIM), Tuscia University, Via del Paradiso, 47, 01100 Viterbo, Italy"},{"name":"Department of Agricultural and Forestry Sciences (DAFNE), Tuscia University, Via S. Camillo de Lellis, 01100 Viterbo, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4443-8322","authenticated-orcid":false,"given":"Cassandra","family":"Funsten","sequence":"additional","affiliation":[{"name":"Department of Architecture, University of Naples Federico II, Via Forno Vecchio, 36, 80134 Naples, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3387-5877","authenticated-orcid":false,"given":"Alessio","family":"Patriarca","sequence":"additional","affiliation":[{"name":"Department of Agricultural and Forestry Sciences (DAFNE), Tuscia University, Via S. Camillo de Lellis, 01100 Viterbo, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5995-7374","authenticated-orcid":false,"given":"Eros","family":"Caputi","sequence":"additional","affiliation":[{"name":"Department of Economics, Engineering, Society and Business Organization (DEIM), Tuscia University, Via del Paradiso, 47, 01100 Viterbo, Italy"},{"name":"Department of Agricultural and Forestry Sciences (DAFNE), Tuscia University, Via S. Camillo de Lellis, 01100 Viterbo, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7993-9480","authenticated-orcid":false,"given":"Lorenzo","family":"Boccia","sequence":"additional","affiliation":[{"name":"Department of Architecture, University of Naples Federico II, Via Forno Vecchio, 36, 80134 Naples, Italy"},{"name":"NBFC, National Biodiversity Future Center, 90133 Palermo, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,8]]},"reference":[{"key":"ref_1","unstructured":"(2019). 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