{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T11:20:14Z","timestamp":1764588014374,"version":"build-2065373602"},"reference-count":47,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,3,6]],"date-time":"2019-03-06T00:00:00Z","timestamp":1551830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the China Scholarship Counsil program","award":["201706960055"],"award-info":[{"award-number":["201706960055"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871177","61801357","61571345","91538101","61501346","61502367","61701360"],"award-info":[{"award-number":["61871177","61801357","61571345","91538101","61501346","61502367","61701360"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the 111 project","award":["B08038"],"award-info":[{"award-number":["B08038"]}]},{"name":"the Natural Science Basic Research Plan in Shaanxi Province of China","award":["2016JQ6023"],"award-info":[{"award-number":["2016JQ6023"]}]},{"name":"the Yangtze River Scholar Bonus Schemes of China","award":["CJT160102"],"award-info":[{"award-number":["CJT160102"]}]},{"name":"the Fundamental Research Funds for the Central Universities","award":["JB180104"],"award-info":[{"award-number":["JB180104"]}]},{"name":"General Financial Grant from the China Postdoctoral Science Foundation","award":["2017M620440"],"award-info":[{"award-number":["2017M620440"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A new method of superpixel segmentation-based local pixel neighborhood preserving embedding (SSLPNPE) is proposed for the fusion of hyperspectral and light detection and ranging (LiDAR) data based on the extinction profiles (EPs), superpixel segmentation and local pixel neighborhood preserving embedding (LPNPE). A new workflow is proposed to calibrate the Goddard\u2019s LiDAR, hyperspectral and thermal (G-LiHT) data, which allows our method to be applied to actual data. Specifically, EP features are extracted from both sources. Then, the derived features of each source are fused by the SSLPNPE. Using the labeled samples, the final label assignment is produced by a classifier. For the open standard experimental data and the actual data, experimental results prove that the proposed method is fast and effective in hyperspectral and LiDAR data fusion.<\/jats:p>","DOI":"10.3390\/rs11050550","type":"journal-article","created":{"date-parts":[[2019,3,7]],"date-time":"2019-03-07T10:52:22Z","timestamp":1551955942000},"page":"550","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Hyperspectral and LiDAR Data Fusion Classification Using Superpixel Segmentation-Based Local Pixel Neighborhood Preserving Embedding"],"prefix":"10.3390","volume":"11","author":[{"given":"Yunsong","family":"Li","sequence":"first","affiliation":[{"name":"The State Key Laboratory of Integrated Services Networks, Xidian University, Xi\u2019an 710071, China"},{"name":"The School of Telecommunications Engineering, Xidian University, Xi\u2019an 710071, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6562-8040","authenticated-orcid":false,"given":"Chiru","family":"Ge","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Integrated Services Networks, Xidian University, Xi\u2019an 710071, China"},{"name":"The School of Telecommunications Engineering, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Weiwei","family":"Sun","sequence":"additional","affiliation":[{"name":"The Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China"}]},{"given":"Jiangtao","family":"Peng","sequence":"additional","affiliation":[{"name":"The Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan 430062, China"}]},{"given":"Qian","family":"Du","sequence":"additional","affiliation":[{"name":"The Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762, USA"}]},{"given":"Keyan","family":"Wang","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Integrated Services Networks, Xidian University, Xi\u2019an 710071, China"},{"name":"The School of Telecommunications Engineering, Xidian University, Xi\u2019an 710071, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.1109\/JSTARS.2014.2305441","article-title":"Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest","volume":"7","author":"Debes","year":"2014","journal-title":"IEEE J. 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