kaz29Вестник Казахстанско-Британского технического университетаHerald of the Kazakh-British Technical University1998-66882959-8109Казахстанско-Британский Технический Университет10.55452/1998-6688-2025-22-1-150-162kaz29-1740Research ArticleКОМПЬЮТЕРНЫЕ НАУКИCOMPUTER SCIENCEПРОСТРАНСТВЕННО-ВРЕМЕННАЯ АНАЛИТИКА ГОРОДСКОГО НАСЕЛЕНИЯ С ПРИМЕНЕНИЕМ ТЕПЛОВЫХ КАРТSPATIOTEMPORAL ANALYTICS OF URBAN POPULATION USING HEAT MAPShttps://orcid.org/0000-0002-0850-0558БектемысоваГ. У.BektemyssovaG. U.

 канд. техн. наук 

 г. Алматы 

 Candidate of Technical Sciences 

 Almaty 

g.bektemisova@gmail.comhttps://orcid.org/0000-0002-1596-561XМолдагуловаА. Н.MoldagulovaA. N.

канд. физ.-матем. наук

 г. Алматы 

 Candidate of Physical and Mathematical Sciences 

 Almaty 

a.moldagulova@satbayev.universityhttps://orcid.org/0009-0001-6465-8894ШайкемелевГ. Т.ShaikemelevG. T.

 докторант 

 г. Алматы 

 PhD student 

 Almaty 

g.shaikemelev@gmail.comhttps://orcid.org/0009-0009-3371-9680ОмаровС. С.OmarovS. S.

 докторант 

 г. Алматы 

 PhD student 

 Almaty 

osskenesary@gmail.comhttps://orcid.org/0009-0004-2546-2751НуралыкызыС.NuralykyzyS.

 докторант

 г. Алматы 

 PhD student 

 Almaty 

s.nuralykyzy@satbayev.universityМеждународный университет информационных технологийКазахстанInternational InformationTechnology UniversityKazakhstanКазахский национальный исследовательский технический университет им. К.И. СатпаеваКазахстанKazakh National Research Technical University named after K.I. SatbayevKazakhstan202524032025221150162Copyright © Бектемысова Г.У., Молдагулова А.Н., Шайкемелев Г.Т., Омаров С.С., Нуралыкызы С., 20252025Бектемысова Г.У., Молдагулова А.Н., Шайкемелев Г.Т., Омаров С.С., Нуралыкызы С.Bektemyssova G.U., Moldagulova A.N., Shaikemelev G.T., Omarov S.S., Nuralykyzy S.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vestnik.kbtu.edu.kz/jour/article/view/1740

Пространственно-временная аналитика данных о движении и плотности населения играет решающую роль в построении «умного города», обеспечивая базу для оптимизации городского планирования, улучшения транспортных систем, повышения общественной безопасности населения, экологического мониторинга, развития цифровых сервисов и городской аналитики. В данной статье приведены результаты исследования по пространственно-временным закономерностям распределения и концентрации населения г. Алматы с использованием метода динамических тепловых карт. Для построения полной картины движения, плотности и активности населения использовались открытые географические данные из OpenStreetMap (OSM) и агрегированные данные мобильного оператора. Анализ нагрузки на городские квадранты размером 500×500 м на основе OSM позволил оценить ключевые закономерности изменения плотности населения в зависимости от времени суток. Визуализация пространственно-временных данных реализована с помощью библиотеки Python Folium, которая обеспечила создание наглядных интерактивных карт. Научная новизна исследования заключается в изучении урбанистических процессов г. Алматы на основе интегрированных данных из разных источников, отражающих пространственные и временные особенности динамики городского населения. Полученные результаты демонстрируют четкие паттерны концентрации населения, которые могут быть использованы для более точного прогнозирования и планирования распределения ресурсов и городской инфраструктуры.

Spatiotemporal analytics of population movement and density data plays a crucial role in building a «smart city», providing a basis for optimizing urban planning, improving transport systems, increasing public safety, environmental monitoring, developing digital services and urban analytics. This article presents the results of a study on spatiotemporal patterns of distribution and concentration of the population of Almaty using the method of dynamic heat maps. To build a complete picture of the movement, density and activity of the population, open geographic data from OpenStreetMap (OSM) and aggregated data from a mobile operator were used. Analysis of the load on urban quadrants of 500×500 meters based on OSM made it possible to assess the key patterns of change in population density depending on the time of day. Visualization of spatiotemporal data is implemented using the Python Folium library, which ensured the creation of clear interactive maps. The scientific novelty of the study lies in the study of urban processes in Almaty based on integrated data from different sources reflecting the spatiotemporal features of the dynamics of the urban population. The results obtained demonstrate clear patterns of population concentration that can be used to more accurately forecast and plan the allocation of resources and urban infrastructure.

пространственно-временная аналитикагородская средаплотность населениятепловая картагородское планированиеOpenStreetMapустойчивое развитие городаspatio-temporal analyticsurban environmentpopulation densityheat mapurban planningOpenStreetMapsustainable urban developmentСтатья представляет результаты исследований, проведенных в рамках грантового финансирования на 2023–2025 гг. по проекту ИРН AP19674517 «Разработка интеллектуальной карты планирования и оценки эффективности городской инфраструктуры на основе моделей анализа человеческой деятельности в условиях городской среды». Исследование выполнено при финансовой поддержке Комитета науки Министерства науки и высшего образования Республики Казахстан.ReferencesZanella A., Bui N., Castellani A., Vangelista L., & Zorzi, M. Internet of Things for Smart Cities. IEEE Internet of Things Journal, 2014. https://doi.org/10.1109/JIOT.2014.2306328.Zanella A., Bui N., Castellani A., Vangelista L., & Zorzi, M. Internet of Things for Smart Cities. 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The authors declare that there are no conflicts of interest present.