Hello,
I made a search on the web, and I have spotted some publications. Nonetheless, since my knowledge of the topic is less than basic, I would appreciate if anyone here could put me in the right direction.
I know that that could prove a 'BIG' question and that there could be many factors affecting the right (or the more appropriate) choice.
Given some features of the data I wish to work with (e.g., 1-sparse weather stations, i.e. not homogeneously covering the study area; 2-stations at different height above sea level), I am would appreciate to know an approach that could prove sound given the data at my disposal.
By the way, I use ArcGIS 10.1.
Best,
Gm
I suggest not to interpolate directions; instead I prefer to interpolate the two components of the wind field and then to compute the directions from the interpolated field.
Hello Haider,
thank you for your reply and for the attached document. As for my goal, is to generate (via interpolation) a continuous surface from sample points (wind direction data derived from weather stations).
I made a search about interpolation of wind data, and I did not find any explicit example related to wind direction. What I have found so far (below) deal with wind speed and, in one instance, with air temperature. Those references make a comparison between different interpolation approaches.
Eldrandaly, K. A., & Abu-Zaid, M. S. (2011). Comparison of Six GIS-Based Spatial Interpolation Methods for Estimating Air Temperature in Western Saudi Arabia. Journal of Environmental Informatics, 18(1), 38–45. doi:10.3808/jei.201100197
Goodin, W. R., McRae, G. J., & Seinfeld, J. H. (1979). A comparison of interpolation methods for sparse data: application to wind and concentration fields. Journal of Applied Meteorology, 18, 761–771. Retrieved from http://authors.library.caltech.edu/32732/
Luo, W., Taylor, M., & Parker, S. (2008). A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and Wales. International Journal of Climatology, 959(August 2007), 947–959. doi:10.1002/joc
The only (short) reference to wind direction that I have found in ArcGIS help is in the link provided below, where they elaborate on the Inverse Distance Weighting.
Any further suggestion, comment, hint is welcome.
Best,
Gm
http://webhelp.esri.com/ARCGISDESKTOP/9.2/index.cfm?TopicName=How_Inverse_Distance_Weighted_(IDW)_interpolation_works
Hi.. I'm not an expert but it is a directional data and has some analogies with geological bedding. May be you'll find useful this paper: https://www.researchgate.net/publication/261337336_A_method_for_the_assessment_of_the_influence_of_bedding_on_landslide_abundance_and_types?ev=prf_pub
Article A method for the assessment of the influence of bedding on l...
Ciao Gianmarco,
if you are working with directional dependent data, such as wind directions, maybe you should take a look to anisotropic interpolation methods. I hope it helps you.
Best,
Joan
Research on the method of wind speed interpolation based on spatially anisotropic analysis: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6885532
Developing Spatially Interpolated Surfaces and Estimating Uncertainty: http://www.epa.gov/airtrends/specialstudies/dsisurfaces.pdf
A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and Wales: http://onlinelibrary.wiley.com/doi/10.1002/joc.1583/pdf
Unified framework for anisotropic interpolation and smoothing of diffusion tensor images: http://www.sciencedirect.com/science/article/pii/S1053811906001261
hi Gianmarco,
Gumiaux et al. 2003, developed a methodology for circular (directional) data interpolation.
You may find the article at:
http://132.248.182.189/cursos/gest/Articulos/Geostatistics/Geostatistics%20applied%20to%20best-fit%20interpolation%20of%20orientation%20data.pdf
* Gumiaux, C., Gapais, D., & Brun, J. P. (2003). Geostatistics applied to best-fit interpolation of orientation data. Tectonophysics, 376(3), 241-259.
You can use the MM5 mesoscale model for estimating the wind, with the ability to integrate data from local weather stations . http://www.mmm.ucar.edu/mm5/
Currently several universities have this model online . I think that might help you in your research generating a subdomain in which you can estimate the values of wind at different heights in the area of your interest .
I hope this information helps you
Best Regards
Hi Gianmarco
Have you already come across this article?
http://www.sciencedirect.com/science/article/pii/S0305440313001064
Seems to deal with similar issues.
Best
Helen
I suggest not to interpolate directions; instead I prefer to interpolate the two components of the wind field and then to compute the directions from the interpolated field.
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