{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:43:39Z","timestamp":1760240619205,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T00:00:00Z","timestamp":1565308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011688","name":"Electronic Components and Systems for European Leadership","doi-asserted-by":"publisher","award":["692455"],"award-info":[{"award-number":["692455"]}],"id":[{"id":"10.13039\/501100011688","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["TEC2017-86722-C4-1-R"],"award-info":[{"award-number":["TEC2017-86722-C4-1-R"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007757","name":"Agencia Canaria de Investigaci\u00f3n, Innovaci\u00f3n y Sociedad de la Informaci\u00f3n","doi-asserted-by":"publisher","award":["POC 2014-2020"],"award-info":[{"award-number":["POC 2014-2020"]}],"id":[{"id":"10.13039\/501100007757","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The utilization of hyperspectral imaging sensors has gained a significant relevance among many different applications due to their capability for collecting a huge amount of information across the electromagnetic spectrum. These sensors have been traditionally mounted on-board satellites and airplanes in order to extract information from the Earth\u2019s surface. Fortunately, the progressive miniaturization of these sensors during the last lustrum has enabled their use in other remote sensing platforms, such as drones equipped with hyperspectral cameras which bring advantages in terms of higher spatial resolution of the acquired images, more flexible revisit times and lower cost of the flight campaigns. However, when these drones are autonomously flying and taking real-time critical decisions from the information contained in the captured images, it is crucial that the whole process takes place in a safe and predictable manner. In order to deal with this problem, a simulation environment is presented in this work to analyze the virtual behavior of a drone equipped with a pushbroom hyperspectral camera used for assisting harvesting applications, which enables an exhaustive and realistic validation and verification of the drone real-time hyperspectral imaging system prior to its launch. To the best of the authors\u2019 knowledge, the proposed environment represents the only solution in the state-of-the-art that allows the virtual verification of real-time hyperspectral image processing algorithms under realistic conditions.<\/jats:p>","DOI":"10.3390\/rs11161852","type":"journal-article","created":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T11:11:31Z","timestamp":1565349091000},"page":"1852","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Simulation Environment for Validation and Verification of Real Time Hyperspectral Processing Algorithms on-Board a UAV"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5488-1654","authenticated-orcid":false,"given":"Pablo","family":"Horstrand","sequence":"first","affiliation":[{"name":"Institute for Applied Microelectronics (IUMA), University of Las Palmas de GC (ULPGC), 35017 Las Palmas de GC, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 Fco.","family":"L\u00f3pez","sequence":"additional","affiliation":[{"name":"Institute for Applied Microelectronics (IUMA), University of Las Palmas de GC (ULPGC), 35017 Las Palmas de GC, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2360-6721","authenticated-orcid":false,"given":"Sebasti\u00e1n","family":"L\u00f3pez","sequence":"additional","affiliation":[{"name":"Institute for Applied Microelectronics (IUMA), University of Las Palmas de GC (ULPGC), 35017 Las Palmas de GC, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tapio","family":"Lepp\u00e4lampi","sequence":"additional","affiliation":[{"name":"Creanex Oy, 33540 Tampere, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Markku","family":"Pusenius","sequence":"additional","affiliation":[{"name":"Creanex Oy, 33540 Tampere, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martijn","family":"Rooker","sequence":"additional","affiliation":[{"name":"R&amp;D Projects Department, TTTech Computertechnik AG, 1040 Vienna, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Michel, S., Gamet, P., and Lefevre-Fonollosa, M. (2011, January 6\u20139). HYPXIM\u2014A hyperspectral satellite defined for science, security and defence users. Proceedings of the 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lisbon, Portugal.","DOI":"10.1109\/WHISPERS.2011.6080864"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1364\/OPN.26.10.000026","article-title":"Hyperspectral Imaging for Safety and Security","volume":"26","author":"Coffey","year":"2015","journal-title":"Opt. Photon. News"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ting-ting, Z., and Fei, L. (2012, January 29\u201331). Application of hyperspectral remote sensing in mineral identification and mapping. Proceedings of the 2012 2nd International Conference on Computer Science and Network Technology, Changchun, China.","DOI":"10.1109\/ICCSNT.2012.6525900"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Nieke, J., and Rast, M. (2018, January 22\u201327). Towards the Copernicus Hyperspectral Imaging Mission For The Environment (CHIME). Proceedings of the IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518384"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1049\/iet-ipr.2018.6533","article-title":"Guest Editorial: Hyperspectral Imaging and Applications","volume":"13","author":"Ren","year":"2019","journal-title":"IET Image Process."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ad\u00e3o, T., Hru\u0161ka, J., P\u00e1dua, L., Bessa, J., Peres, E., Morais, R., and Sousa, J.J. (2017). Hyperspectral imaging: A review on UAV-based sensors, data processing and applications for agriculture and forestry. Remote Sens., 9.","DOI":"10.3390\/rs9111110"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2427","DOI":"10.1080\/01431161.2016.1252477","article-title":"Forestry applications of UAVs in Europe: A review","volume":"38","author":"Torresan","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"6021","DOI":"10.1364\/OE.26.006021","article-title":"Do it yourself hyperspectral imager for handheld to airborne operations","volume":"26","author":"Sigernes","year":"2018","journal-title":"Opt. Express"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Arroyo-Mora, J.P., Kalacska, M., Inamdar, D., Soffer, R., Lucanus, O., Gorman, J., Naprstek, T., Schaaf, E.S., Ifimov, G., and Elmer, K. (2019). Implementation of a UAV\u2013Hyperspectral Pushbroom Imager for Ecological Monitoring. Drones, 3.","DOI":"10.3390\/drones3010012"},{"key":"ref_10","unstructured":"(2019, July 04). ENABLE-S3 Project. Available online: https:\/\/www.enable-s3.eu\/."},{"key":"ref_11","unstructured":"Rooker, M., Horstrand, P., Rodr\u00edguez, A., L\u00f3pez, S., Sarmiento, R., L\u00f3pez, J., Lattarulo, R., P\u00e9rez, J., Matute, J., and Slavik, Z. (2018, January 10\u201313). Towards improved validation of autonomous systems for smart farming. Proceedings of the Workshop on Smart Farming, CPS Week, Porto, Portugal."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"66919","DOI":"10.1109\/ACCESS.2019.2913957","article-title":"A UAV platform based on a hyperspectral sensor for image capturing and on-board processing","volume":"7","author":"Horstrand","year":"2019","journal-title":"IEEE Access"},{"key":"ref_13","unstructured":"(2019, May 22). DJI Matrice 600. Available online: https:\/\/www.dji.com\/matrice600."},{"key":"ref_14","unstructured":"(2019, May 22). Specim FX Series Hyperspectral Cameras. Available online: http:\/\/www.specim.fi\/fx\/."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Holder, M., Rosenberger, P., Winner, H., D\u2019hondt, T., Makkapati, V.P., Maier, M., Schreiber, H., Magosi, Z., Slavik, Z., and Bringmann, O. (2018, January 4\u20137). Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving. Proceedings of the 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA.","DOI":"10.1109\/ITSC.2018.8569423"},{"key":"ref_16","unstructured":"(2019, May 24). Grupo de Inteligencia Computacional, Universidad del Pa\u00eds Vasco\/Euskal Herriko Unibertsitatea (UPV\/EHU), Spain, Hyperspectral Imagery Synthesis Toolbox. Available online: http:\/\/www.ehu.es\/ccwintco\/index.php\/Hyperspectral_Imagery_Synthesis_tools_for_MATLAB."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1109\/JSTARS.2012.2194696","article-title":"Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches","volume":"5","author":"Plaza","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_18","unstructured":"Kozintsev, B. (1999). Computations with Gaussian Random Fields. [Ph.D. Thesis, University of Maryland]."},{"key":"ref_19","unstructured":"(2019, May 24). USGS Digital Spectral Library, Available online: http:\/\/speclab.cr.usgs.gov\/spectral-lib.html."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.rse.2003.12.013","article-title":"Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture","volume":"90","author":"Haboudane","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1760","DOI":"10.1109\/29.60107","article-title":"Adaptive multiple-band CFAR detection of an optical pattern with unknown spectral distribution","volume":"38","author":"Reed","year":"1990","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"ref_22","unstructured":"Schaum, A. (2004, January 6\u201313). Joint subspace detection of hyperspectral targets. Proceedings of the 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720), Big Sky, MT, USA."},{"key":"ref_23","unstructured":"Chang, C.I. (2013). Orthogonal Subspace Projection Revisited. Hyperspectral Data Processing: Algorithm Design and Analysis, John Wiley & Sons."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1109\/LGRS.2018.2869337","article-title":"Improving Hyperspectral Anomaly Detection With a Simple Weighting Strategy","volume":"16","author":"Zhu","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4076","DOI":"10.1109\/JSTARS.2018.2870123","article-title":"Hyperspectral Anomaly Detection Using Combined Similarity Criteria","volume":"11","author":"Vafadar","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"5029","DOI":"10.1109\/JSTARS.2018.2880749","article-title":"Hyperspectral Anomaly Detection Using Collaborative Representation With Outlier Removal","volume":"11","author":"Su","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1109\/LGRS.2018.2878869","article-title":"A Fast Recursive Collaboration Representation Anomaly Detector for Hyperspectral Image","volume":"16","author":"Ma","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zhao, C., Deng, W., Yan, Y., and Yao, X. (2017). Progressive Line Processing of Kernel RX Anomaly Detection Algorithm for Hyperspectral Imagery. Sensors, 17.","DOI":"10.3390\/s17081815"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Horstrand, P., Diaz, M., Guerra, R., Lopez, S., and Lopez, J.F. (2019). A Novel Hyperspectral Anomaly Detection Algorithm for Real-Time Applications With Push-Broom Sensors. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 1\u201311.","DOI":"10.1109\/JSTARS.2019.2919911"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"D\u00edaz, M., Guerra, R., Horstrand, P., L\u00f3pez, S., and Sarmiento, R. (2019). A Line-by-Line Fast Anomaly Detector for Hyperspectral Imagery. IEEE Trans. Geosci. Remote Sens., 1\u201315.","DOI":"10.1109\/TGRS.2019.2923921"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2736","DOI":"10.3390\/rs4092736","article-title":"Radiometric and Geometric Analysis of Hyperspectral Imagery Acquired from an Unmanned Aerial Vehicle","volume":"4","author":"Hruska","year":"2012","journal-title":"Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Habib, A., Han, Y., Xiong, W., He, F., Zhang, Z., and Crawford, M. (2016). Automated Ortho-Rectification of UAV-Based Hyperspectral Data over an Agricultural Field Using Frame RGB Imagery. Remote Sens., 8.","DOI":"10.3390\/rs8100796"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/16\/1852\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:09:46Z","timestamp":1760188186000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/16\/1852"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,9]]},"references-count":32,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2019,8]]}},"alternative-id":["rs11161852"],"URL":"https:\/\/doi.org\/10.3390\/rs11161852","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,8,9]]}}}