Next Article in Journal
Global Navigation Satellite Systems Reflectometry as a Remote Sensing Tool for Agriculture
Previous Article in Journal
Polarimetric Decomposition Analysis of ALOS PALSAR Observation Data before and after a Landslide Event
Remote Sens. 2012, 4(8), 2329-2355; doi:10.3390/rs4082329

Four Methods for LIDAR Retrieval of Microscale Wind Fields

, Jr. 1,2,*  and 2
1 Faculdade de Geofisíca, Instituto de Geociênces, Universidade Federal do Pará, Rua Augusto Correa, 01-Guamá, Belem-PA, 66075-110, Brazil 2 Department of Physics, Utah State University, Logan, UT 84322, USA
* Author to whom correspondence should be addressed.
Received: 25 June 2012 / Revised: 25 July 2012 / Accepted: 27 July 2012 / Published: 8 August 2012
View Full-Text   |   Download PDF [695 KB, uploaded 19 June 2014]   |   Browse Figures


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 fluctuations. Suitably designed mono-static scanning backscatter LIDAR systems, which are sensitive to atmospheric density aerosol fluctuations, are expected to be ideal for this purpose. An important application is wind farm siting and evaluation. In this case, it is necessary to look at the complicated region between the earth’s surface and the boundary layer, where wind can be turbulent and fractal scaling from millimeter to kilometer. The methods are demonstrated using first a simple randomized moving hard target, and then with a physics based stochastic space-time dynamic turbulence model. In the latter case the actual vector wind field is known, allowing complete space-time error analysis. Two of the methods, the semblance method and the spatio-temporal method, are found to be most suitable for wind field estimation.
Keywords: LIDAR; 3D; vector wind fields; spatio-temporal and semblance methods; fluid flow models; retrievals LIDAR; 3D; vector wind fields; spatio-temporal and semblance methods; fluid flow models; retrievals
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
MDPI and ACS Style

Howard, A.Q., , Jr.; Naini, T. Four Methods for LIDAR Retrieval of Microscale Wind Fields. Remote Sens. 2012, 4, 2329-2355.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here


Cited By

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert