Abstract and keywords
Abstract:
An algorithm for studying the avalanche hazard of a territory based on a nearly periodic analysis of data proposed, which results in intervals of uniform function behavior. These intervals divided by uniformly spaced boundaries that form a rectangular grid in the space of linearized data. An algorithm for studying the avalanche hazard of a mountainous territory proposed, based on a nearly periodic analysis of linearized data obtained during the polygonal transformation of the original satellite image of a mountain range. Based on the results of applying the algorithm, a composition of uniform longitudinal and transverse intervals of uniform behavior of linearized data is determined, forming a system of critical spatial barriers of the original image that determine the degree of avalanche hazard of nearby territories.

Keywords:
avalanche, danger, near period, satellite image
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References

1. Snow avalanche in the Indian Himalayas: Hazard zonation and climate change trends in Kullu region of Himachal Pradesh, India / J.K. Bansal [et al.] // Physics and Chemistry of the Earth, Parts A/B/C. 2025. Vol. 138. P. 103882. DOI:https://doi.org/10.1016/j.pce.2025.103882

2. Review of spatial variability of snowpack properties and its importance for avalanche formation / J. Schweizer [et al.] // Cold Regions Science and Technology. 2008. Vol. 51. Iss. 2–3. P. 253–272. DOI: 1016/j.coldregions.2007.04.009

3. Lavinnaya aktivnost' v Rossii v usloviyah izmenyayushchegosya klimata / A.S. Turchaninova [i dr.] // Vestnik Rossijskogo fonda fundamental'nyh issledovanij. 2022. № 3–4 (115–116). S. 122–131.

4. Ricinskij reliktovyj nacional'nyj park. Federaciya al'pinizma i skalolazaniya. Sneg i laviny v gorah. Prognoz i bezopasnost'. Gudauta: RRNP, 2024. 36 s.

5. Barbolini M., Keylock C. A new method for avalanche hazard mapping using a combination of statistical and deterministic models // Natural Hazards and Earth System Sciences. 2002. Vol. 2. P. 239–245. DOI:https://doi.org/10.5194/nhess-2-239-2002

6. Singh A., Ganju A. A supplement to nearest-neighbour method for avalanche forecasting // Cold Regions Science and Technology. 2004. Vol. 39. Iss. 2–3. P. 105–113. DOI:https://doi.org/10.1016/j.coldregions.2004.03.005

7. Snow avalanche hazard prediction using machine learning methods / B. Choubin [et al.] // Journal of Hydrology. 2019. Vol. 577. P. 123929. DOI:https://doi.org/10.1016/j.jhydrol.2019.123929

8. Chen M., Mao S., Liu Yu. Big data: survey // Mobile Netw Appl. 2014. Vol. 19 (2). P. 171–209.

9. Jaseena K.U., David J.M. Issues, challenges, and solutions: big data mining // Comput Sci Inf Technol (CS & IT). 2014. Vol. 4. P. 131–40.

10. Big data analytics: a survey / C.W. Tsai [et al.] // J Big Data. 2015. Vol. 2 (1). P. 21.

11. Programma poligonal'nogo razbieniya izobrazheniy s ob'ektami nelineynoy struktury: svidetel'stvo o gosudarstvennoy registracii programmy dlya EVM № 2024688034 / Kuznecova K.A., Kalach A.V., Paramonov A.A., Smolenceva T.E., Kryneckiy B.A; zareg. 05.11.2024; opubl. 25.11.2024.

12. Programma poligonal'nogo razbieniya izobrazhenij s ob"ektami nelinejnoj struktury: svidetel'stvo o gosudarstvennoj registracii programmy dlya EVM № 2024688034 / Kuznecova K.A., Kalach A.V., Paramonov A.A., Smolenceva T.E., Kryneckij B.A; zareg. 05.11.2024; opubl. 25.11.2024.

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