{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:04:42Z","timestamp":1760241882570,"version":"build-2065373602"},"reference-count":14,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2018,10,12]],"date-time":"2018-10-12T00:00:00Z","timestamp":1539302400000},"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>We refute statements in \u201cZhou, K., et al. Wind gust detection and impact prediction for wind turbines. Remote Sens. 2018, 10, 514.\u201d about the impracticality of motion estimation methods to derive two-component vector wind fields from single scanning aerosol lidar data. Our assertion is supported by recently published results on the performance of two image-based motion estimation methods: cross-correlation (CC) and wavelet-based optical flow (WOF). The characteristics and performances of CC and WOF are compared with those of a two-dimensional variational (2D-VAR) method that was applied to radial velocity fields from a single scanning Doppler lidar. The algorithmic aspects of WOF and 2D-VAR are reviewed and we conclude that these two approaches are in fact similar and practical.<\/jats:p>","DOI":"10.3390\/rs10101625","type":"journal-article","created":{"date-parts":[[2018,10,12]],"date-time":"2018-10-12T10:54:03Z","timestamp":1539341643000},"page":"1625","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Comments on \u201cWind Gust Detection and Impact Prediction for Wind Turbines\u201d"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9694-7236","authenticated-orcid":false,"given":"Shane D.","family":"Mayor","sequence":"first","affiliation":[{"name":"California State University Chico, 400 West First Street, Chico, CA 95929, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2840-1837","authenticated-orcid":false,"given":"Pierre","family":"D\u00e9rian","sequence":"additional","affiliation":[{"name":"Independent researcher, 44000 Nantes, France"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,12]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Zhou, K., Cherukuru, N., Sun, X., and Calhoun, R. (2018). Wind gust detection and impact prediction for wind turbines. Remote Sens., 10.","key":"ref_1","DOI":"10.3390\/rs10040514"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/j.egypro.2017.10.378","article-title":"2D VAR single Doppler lidar vector retrieval and its application in offshore wind energy","volume":"137","author":"Cherukuru","year":"2017","journal-title":"Energy Procedia"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1175\/JTECH-D-15-0010.1","article-title":"Wavelet-based optical flow for two-component wind field estimation from single aerosol lidar data","volume":"32","author":"Mauzey","year":"2015","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1175\/JTECH-D-15-0009.1","article-title":"Optimization of the cross-correlation algorithm for two-component wind field estimation from single aerosol lidar data and comparison with Doppler lidar","volume":"33","author":"Hamada","year":"2016","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1175\/JTECH-D-11-00225.1","article-title":"Two-component horizontal aerosol motion vectors in the atmospheric surface layer from a cross-correlation algorithm applied to scanning elastic backscatter lidar data","volume":"29","author":"Mayor","year":"2012","journal-title":"J. Atmos. Ocean. Technol."},{"doi-asserted-by":"crossref","unstructured":"Mayor, S.D., D\u00e9rian, P., Mauzey, C.F., and Hamada, M. (2013). Two-component wind fields from scanning aerosol lidar and motion estimation algorithms. SPIE Lidar Remote Sens. Environ. Monit. XIV.","key":"ref_6","DOI":"10.1117\/12.2025337"},{"doi-asserted-by":"crossref","unstructured":"Mayor, S.D., D\u00e9rian, P., Mauzey, C.F., Spuler, S.M., Ponsardin, P., Pruitt, J., Ramsey, D., and Higdon, N.S. (2016). Comparison of an analog direct detection and a micropulse aerosol lidar at 1.5-micron wavelength for wind field observations\u2014with first results over the ocean. J. Appl. Remote Sens., 10.","key":"ref_7","DOI":"10.1117\/1.JRS.10.016031"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1175\/1520-0450(2001)040<1331:TDVWFF>2.0.CO;2","article-title":"Two-dimensional vector wind fields from volume imaging lidar data","volume":"40","author":"Mayor","year":"2001","journal-title":"J. Appl. Meteorol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"18395","DOI":"10.1029\/92JD01051","article-title":"The calculation of area-averaged vertical profiles of the horizontal wind velocity from volume imaging lidar data","volume":"97","author":"Schols","year":"1992","journal-title":"J. Geophys. Res."},{"unstructured":"Bieringer, P.E., Higdon, S., Bieberbach, G., Hurst, J., and Mayor, S.D. (,  2017). Assimilation of lidar backscatter and wind data into atmospheric transport and dispersion model. Proceedings of the Eighth Symposium on Lidar Atmospheric Applications, American Meteorological Society, Seattle, WA, USA. Available online: https:\/\/ams.confex.com\/ams\/97Annual\/webprogram\/Paper308839.html.","key":"ref_10"},{"key":"ref_11","first-page":"116","article-title":"Wavelets and optical flow motion estimation","volume":"6","author":"Herzet","year":"2012","journal-title":"Numer. Math. Theory Methods Appl."},{"unstructured":"Mauzey, C.F., D\u00e9rian, P., and Mayor, S.D. (2014, January 24\u201327). Wavelet-based optical flow for real-time wind estimation using CUDA. Proceedings of the GPU Technology Conference, San Jose, CA, USA.","key":"ref_12"},{"unstructured":"Mauzey, C.F., Lowe, J.P., and Mayor, S.D. (2012, January 14\u201317). Real-time wind velocity estimation from aerosol lidar data using graphics hardware. Proceedings of the GPU Technology Conference, San Jose, CA, USA.","key":"ref_13"},{"unstructured":"Held, A., Seith, T., Brooks, I.M., Norris, S.J., and Mayor, S.D. (2012, January 2\u20137). Intercomparison of lidar aerosol backscatter and in-situ size distribution measurements. Presentation number B-WG01S2P05. In Proceedings of the European Aerosol Conference, Granada, Spain.","key":"ref_14"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/10\/1625\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:25:17Z","timestamp":1760196317000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/10\/1625"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,12]]},"references-count":14,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2018,10]]}},"alternative-id":["rs10101625"],"URL":"https:\/\/doi.org\/10.3390\/rs10101625","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,10,12]]}}}