%0 Journal Article %1 howard2012methods %A Howard, Allen Q. %A Naini, Thomas %D 2012 %J Remote Sensing %K and fields flow methods;vector models;fluid;LiDAR;retrievals;spatio-temporal semblance wind %N 12 %P 2329--2355 %R 10.3390/rs4082329 %T Four Methods for LIDAR Retrieval of Microscale Wind Fields %V 4 %X This paper evaluates four wind retrieval methods for micro-scale meteorology applications with volume and time resolution in the order of 30m3 and 5 s. Wind field vectors are estimated using sequential time-lapse volume images of aerosol density fluctuat

@article{howard2012methods, abstract = {This paper evaluates four wind retrieval methods for micro-scale meteorology applications with volume and time resolution in the order of 30m3 and 5 s. Wind field vectors are estimated using sequential time-lapse volume images of aerosol density fluctuat}, added-at = {2018-07-01T13:42:06.000+0200}, author = {Howard, Allen Q. and Naini, Thomas}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2486fb4db2367bfff1b31e3a9ff67edde/mwigger}, doi = {\url{10.3390/rs4082329}}, interhash = {6256b10c5c2b0538cbf72e984eb030ba}, intrahash = {486fb4db2367bfff1b31e3a9ff67edde}, issn = {2072-4292}, journal = {Remote Sensing}, keywords = {and fields flow methods;vector models;fluid;LiDAR;retrievals;spatio-temporal semblance wind}, number = 12, pages = {2329--2355}, timestamp = {2018-09-14T09:59:55.000+0200}, title = {Four Methods for LIDAR Retrieval of Microscale Wind Fields}, urldate = {11.03.2016}, volume = 4, year = 2012 }