Abstract
This work is related to the Earth’s ionosphere simulation and prediction system developed in the Brazilian Space Weather program, which process a large number of data to provide total electron content (TEC) maps. We present improvements to the task of finding nearest neighbors for the interpolation method at homogeneous grid locations, which demands an important computational cost. Simulation points generated by 73 parallel executions of a physical-mathematical ionosphere model are used. The proposed approach is based on a custom code optimization and a variable reduction of the search space considering geographic information. We tested a different number of neighbors and geographic longitude ranges, using available libraries for approximate nearest neighbor (ANN), fast library for approximate nearest neighbor (FLANN) and a fast \(\varvec{K}\) Nearest Neighbors library for low-dimensional spaces (libnabo) in an ionosphere global simulation. Experiments have shown the proposed approach progressively overcomes the libraries’ best solution as the number of neighbors increases. The speedup was significantly improved for the majority of the scenarios tested. The approach was able to reduce processing time in low and mid-latitudes, while providing close-to-zero errors. On the other hand, errors are noticed at higher latitudes, especially near the poles where geomagnetic field lines converge, or the ionospheric model is unable to provide sufficient estimates.
Similar content being viewed by others
Availability of Data and Materials
Upon request Telmo dos Santos Klipp would be glad to facilitate access to data and materials related to the ionospheric system used in this work.
Notes
TEC maps available at: http://www2.inpe.br/climaespacial/portal/tec-supim-prevision/.
References
Arya S, Mount DM, Netanyahu NS et al (1998) An optimal algorithm for approximate nearest neighbor searching fixed dimensions. J ACM (JACM) 45(6):891–923. https://doi.org/10.1145/293347.293348
Bailey G (1996) A low latitude ionosphere-plasmasphere model. Handbook of Ionospheric Models, Solar-Terrestrial Energy Program
Bailey G, Balan N, Su Y (1997) The sheffield university plasmasphere ionosphere model-a review. J Atmos Sol Terr Phys 59(13):1541–1552. https://doi.org/10.1016/S1364-6826(96)00155-1
dos Santos Klipp T, Petry A, de Souza JR et al (2019) Evaluation of ionospheric models for central and south americas. Adv Space Res 64(10):2125–2136. https://doi.org/10.1016/j.asr.2019.09.005
Drob DP, Emmert JT, Crowley G et al (2008) An empirical model of the Earth’s horizontal wind fields: HWM07. J Geophys Res Space Phys 113(A12). https://doi.org/10.1029/2008JA013668
Elseberg J, Magnenat S, Siegwart R et al (2012) Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration. J Softw Eng Robot 3(1):2–12
Finlay CC, Maus S, Beggan CD et al (2010) International geomagnetic reference field: the eleventh generation. Geophys J Int 183(3):1216–1230. https://doi.org/10.1111/j.1365-246X.2010.04804.x
Muja M, Lowe DG (2009) Fast approximate nearest neighbors with automatic algorithm configuration. In: Ranchordas A, Araújo H (eds) VISAPP 2009- Proceedings of the Fourth International Conference on Computer Vision Theory and Applications, Lisboa, Portugal, February 5-8, 2009 - Volume 1. INSTICC Press, pp 331–340
Petry A, de Souza JR, de Campos Velho HF et al (2014) First results of operational ionospheric dynamics prediction for the brazilian space weather program. Adv Space Res 54(1):22–36. https://doi.org/10.1016/j.asr.2014.03.017
Petry A, Pereira AG, de Souza JR (2017) An approximate nearest neighbors search algorithm for low-dimensional grid locations. Earth Sci Inform 10(2):183–196. https://doi.org/10.1007/s12145-016-0282-2
Picone JM, Hedin AE, Drob DP et al (2002) NRLMSISE-00 empirical model of the atmosphere: Statistical comparisons and scientific issues. J Geophys Res Space Phys 107(A12):SIA 15-1-SIA 15-16. https://doi.org/10.1029/2002JA009430
Scherliess L, Fejer BG (1999) Radar and satellite global equatorial F region vertical drift model. J Geophys Res Space Phys 104(A4):6829–6842. https://doi.org/10.1029/1999JA900025
Shepard D (1968) A two-dimensional interpolation function for irregularly-spaced data. In: Proceedings of the 1968 23rd ACM national conference, pp 517–524
Tobiska W, Woods T, Eparvier F et al (2000) The SOLAR2000 empirical solar irradiance model and forecast tool. J Atmos Sol Terr Phys 62(14):1233–1250. https://doi.org/10.1016/S1364-6826(00)00070-5
Acknowledgements
Telmo dos Santos Klipp acknowledges Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - for PhD scholarship; Rhauani Weber Aita Fazul acknowledges CNPq – National Council for Scientific and Technological Development – Brazil – for Masters Scholarship.
Funding
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
Author information
Authors and Affiliations
Contributions
Telmo dos Santos Klipp and Adriano Petry implemented and tested the proposed NN search approach, and wrote the main manuscript text; Adriano Petry and André Grahl Pereira implemented and tested the baseline interpolation system for ionosphere simulation. André Grahl Pereira, Rhauani Weber Aita Fazul, Lucas Ferreira da Silva, Iago da Cunha, and Andrea Schwertner Charão implemented and tested NN search procedures using state-of-art libraries. All authors reviewed the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Communicated by: H. Babaie.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
dos Santos Klipp, T., Petry, A., Aita Fazul, R.W. et al. New approaches to improve nearest neighbors (NN) search in ionospheric simulation system. Earth Sci Inform 16, 3619–3627 (2023). https://doi.org/10.1007/s12145-023-01105-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12145-023-01105-5