{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:05:30Z","timestamp":1771466730489,"version":"3.50.1"},"reference-count":18,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"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>Hyperspectral imaging (HSI) has emerged as a promising, advanced technology in remote sensing and has demonstrated great potential in the exploitation of a wide variety of data. In particular, its capability has expanded from unmixing data samples and detecting targets at the subpixel scale to finding endmembers, which generally cannot be resolved by multispectral imaging. Accordingly, a wealth of new HSI research has been conducted and reported in the literature in recent years. The aim of this Special Issue \u201cAdvances in Hyperspectral Data Exploitation\u201c is to provide a forum for scholars and researchers to publish and share their research ideas and findings to facilitate the utility of hyperspectral imaging in data exploitation and other applications. With this in mind, this Special Issue accepted and published 19 papers in various areas, which can be organized into 9 categories, including I: Hyperspectral Image Classification, II: Hyperspectral Target Detection, III: Hyperspectral and Multispectral Fusion, IV: Mid-wave Infrared Hyperspectral Imaging, V: Hyperspectral Unmixing, VI: Hyperspectral Sensor Hardware Design, VII: Hyperspectral Reconstruction, VIII: Hyperspectral Visualization, and IX: Applications.<\/jats:p>","DOI":"10.3390\/rs14205111","type":"journal-article","created":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T22:21:11Z","timestamp":1665699671000},"page":"5111","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Editorial for Special Issue \u201cAdvances in Hyperspectral Data Exploitation\u201d"],"prefix":"10.3390","volume":"14","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 County, Baltimore, MD 21250, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunyan","family":"Yu","sequence":"additional","affiliation":[{"name":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian 116026, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6436-5883","authenticated-orcid":false,"given":"Yulei","family":"Wang","sequence":"additional","affiliation":[{"name":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian 116026, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4026-7450","authenticated-orcid":false,"given":"Haoyang","family":"Yu","sequence":"additional","affiliation":[{"name":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian 116026, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0470-9469","authenticated-orcid":false,"given":"Jiaojiao","family":"Li","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Integrated Service Networks, Xidian University, Xi\u2019an 710000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Physics and Optoelectronic Engineering, Xidian University, Xi\u2019an 710000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4527-9730","authenticated-orcid":false,"given":"Hsiao-Chi","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National Taipei University of Technology (Taipei Tech), Taipei 10608, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaorun","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,13]]},"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":"Chang, C.-I. (2013). Hyperspectral Data Processing: Algorithm Design and Analysis, Wiley.","DOI":"10.1002\/9781118269787"},{"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","unstructured":"Chang, C.-I. (2022). Advances in Hyperspectral Image Processing Techniques, Wiley. ISBN-13 978-1119687764, ISBN-10 1119687764."},{"key":"ref_7","unstructured":"Song, M., and Chang, C.-I. (2021). Hypersspectral Data Unmixing: Algorithm Design and Analysis, Hubei Science and Technology Press."},{"key":"ref_8","unstructured":"Chang, C.-I., Wang, Y., Xue, B., Wang, L., Yu, C., and Song, M. (2021). Hyperspectral Target Detection: Algorithm Design and Analysis, Hubei Science and Technology Press."},{"key":"ref_9","first-page":"16","article-title":"Simple models for complex natural surfaces: A strategy for hyperspectral era of remote sensing","volume":"1","author":"Adams","year":"1989","journal-title":"Proc. IEEE Int. Geosci. Remote Sens. Symp."},{"key":"ref_10","unstructured":"Pieters, C.M., and Englert, P.A. (1993). Remote Geochemical Analysis: Elemental and Mineralogical Composition, Cambridge University Press."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Hill, J., and Mergier, J. (1994). Image Spectroscopy\u2014A Tool for Environmental Observations, Springer.","DOI":"10.1007\/978-0-585-33173-7"},{"key":"ref_12","first-page":"2372","article-title":"A new approach to quantifying abundances of materials in multispectral images","volume":"4","author":"Smith","year":"1944","journal-title":"Proc. IEEE Int. Geosci. Remote Sens. Symp."},{"key":"ref_13","unstructured":"Gillespie, A.R., Smith, M.O., Adams, J.B., Willis, S.C., Fischer, A.F., and Sabol, D.E. (1990, January 6\u20138). Interpretation of residual images: Spectral mixture analysis of AVIRIS images, Owens valley, California. Proceedings of the Second Airborne Visible\/Infrared Imaging Spectrometer (AVIRIS) Workshop, Pasadena, CA, USA."},{"key":"ref_14","first-page":"1036","article-title":"Quantitative determination of imaging spectrometer specifications based on spectral mixing models","volume":"1","author":"Goetz","year":"1989","journal-title":"Proc. IEEE Int. Geosci. Remote Sens. Symp."},{"key":"ref_15","first-page":"430","article-title":"The HYDICE instrument design","volume":"1","author":"Basedow","year":"1992","journal-title":"Proc. Int. Symp. Spectr. Sens. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1109\/79.974724","article-title":"Detection algorithms for hyperspectral imaging applications","volume":"19","author":"Manolakis","year":"2002","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_17","unstructured":"Benediktsson, J.A., and Ghamisi, P. (2015). Spectral-Spatial Classification of Hyperspectral Remote Sensing Images, Artech House."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Plaza, A., and Chang, I.-C. (2007). High Performance Computing in Remote Sensing, Chapman & Hall\/CRC Press.","DOI":"10.1201\/9781420011616"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/20\/5111\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:53:06Z","timestamp":1760143986000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/20\/5111"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,13]]},"references-count":18,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["rs14205111"],"URL":"https:\/\/doi.org\/10.3390\/rs14205111","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,13]]}}}