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Integrating the Spatial Autocorrelation Structure of Irregularly Distributed Wind Measurement Stations to Model Wind Patterns Using R Cover

Integrating the Spatial Autocorrelation Structure of Irregularly Distributed Wind Measurement Stations to Model Wind Patterns Using R

Journal of Geospatial Surveying
Volume 2 (2022): Issue 2
By:   
Open Access
|Oct 2022
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DOI: https://doi.org/10.4038/jgs.v2i2.42 | Journal eISSN: 2792-1239
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Language: English
Page range: 30 - 42
Published on: Oct 26, 2022
Published by: Faculty of Geomatics, Sabaragamuwa University of Sri Lanka
In partnership with: Paradigm Publishing Services
Keywords:
Wind speed,
Wind direction,
Wind patterns,
Variograms,
Kriging,
R 4.0.2

© 2022 D. R. Welikanna, published by Faculty of Geomatics, Sabaragamuwa University of Sri Lanka
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.

Volume 2 (2022): Issue 2
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