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
%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
}