{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T06:38:52Z","timestamp":1769841532592,"version":"3.49.0"},"reference-count":6,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2019,8,27]],"date-time":"2019-08-27T00:00:00Z","timestamp":1566864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging. The aim of this Special Issue \u201cHyperspectral Imaging and Applications\u201d is to publish new ideas and technologies to facilitate the utility of hyperspectral imaging in data exploitation and to further explore its potential in different applications. This Special Issue has accepted and published 25 papers in various areas, which can be organized into 7 categories, Data Unmixing, Spectral variability, Target Detection, Hyperspectral Image Classification, Band Selection, Data Fusion, Applications.<\/jats:p>","DOI":"10.3390\/rs11172012","type":"journal-article","created":{"date-parts":[[2019,8,27]],"date-time":"2019-08-27T11:13:30Z","timestamp":1566904410000},"page":"2012","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Editorial for Special Issue \u201cHyperspectral Imaging and Applications\u201d"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5450-4891","authenticated-orcid":false,"given":"Chein-I","family":"Chang","sequence":"first","affiliation":[{"name":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian 116026, China"},{"name":"Remote Sensing Signal and Image Processing Laboratory, Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore, MD 21250, USA"}]},{"given":"Meiping","family":"Song","sequence":"additional","affiliation":[{"name":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian 116026, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1082-114X","authenticated-orcid":false,"given":"Junping","family":"Zhang","sequence":"additional","affiliation":[{"name":"Harbin Institute of Technology, Harbin 150001, China"}]},{"given":"Chao-Cheng","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National Taipei University of Technology (Taipei Tech), Taipei 10608, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,27]]},"reference":[{"key":"ref_1","unstructured":"Chang, C.-I. (2003). Hyperspectral Imaging: Techniques for Spectral Detection and Classification, Kluwer Academic\/Plenum Publishers."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Plaza, A., and Chang, C.-I. (2007). High Performance Computing in Remote Sensing, Chapman & Hall\/CRC Press.","DOI":"10.1201\/9781420011616"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Chang, C.-I. (2016). Real-Time Progressive Hyperspectral Image Processing: Endmember Finding and Anomaly Detection, Springer.","DOI":"10.1007\/978-1-4419-6187-7"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Chang, C.-I. (2017). Real-Time Recursive Hyperspectral Sample and Band Processing: Algorithm Architecture and Implementation, Springer.","DOI":"10.1007\/978-3-319-45171-8"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Chang, C.-I. (2007). Hyperspectral Data Exploitation: Theory and Applications, John Wiley & Sons.","DOI":"10.1002\/0470124628"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Chang, C.-I. (2013). Hyperspectral Data Processing: Algorithm Design and Analysis, John Wiley & Sons.","DOI":"10.1002\/9781118269787"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/17\/2012\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:14:17Z","timestamp":1760188457000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/17\/2012"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,27]]},"references-count":6,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["rs11172012"],"URL":"https:\/\/doi.org\/10.3390\/rs11172012","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,27]]}}}