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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">sergeogr</journal-id><journal-title-group><journal-title xml:lang="ru">Известия Российской академии наук. Серия географическая</journal-title><trans-title-group xml:lang="en"><trans-title>Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2587-5566</issn><issn pub-type="epub">2658-6975</issn><publisher><publisher-name></publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.7868/S2658697526030048</article-id><article-id custom-type="elpub" pub-id-type="custom">sergeogr-3177</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ТЕРРИТОРИАЛЬНАЯ ОРГАНИЗАЦИЯ ОБЩЕСТВА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>TERRITORIAL ORGANIZATION OF SOCIETY</subject></subj-group></article-categories><title-group><article-title>Факторы развития сети автомобильных дорог материкового Китая в 2014–2022 гг. на примере единиц административно-территориального деления второго уровня</article-title><trans-title-group xml:lang="en"><trans-title>Spatial Strategy for the Development of China’s Highway Network in the Period 2014–2022 уy. Using Second Level Administrative Divisions</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Коробко</surname><given-names>А. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Korobko</surname><given-names>A. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><email xlink:type="simple">akorobko9994@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Институт географии РАН</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Institute of Geography, Russian Academy of Sciences</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>18</day><month>08</month><year>2026</year></pub-date><volume>90</volume><issue>3</issue><fpage>500</fpage><lpage>511</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Коробко А.И., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Коробко А.И.</copyright-holder><copyright-holder xml:lang="en">Korobko A.I.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://izvestia.igras.ru/jour/article/view/3177">https://izvestia.igras.ru/jour/article/view/3177</self-uri><abstract><p>Для анализа неравномерности размещения сети автодорог Китайской Народной Республики (скоростных автомагистралей и дорог 1 и 2 классов) в динамике (2014–2022 гг.) использована уникальная дробная территориальная статистика по 334 ячейкам (округам), доступная только на китайском языке, а также картометрические расчеты с использованием данных сервиса Open Street Map. Это позволило составить очень подробные карты плотности автодорог, по которым выявлены географические различия в уровне транспортной освоенности территории Китая, которые не видны на обычных картах и даже в национальном атласе КНР. Выявлены главные ареалы развития автодорожной сети и ядра ее концентрации, а также пространственные лакуны в рисунке этой освоенности. К главным ареалам концентрации автодорожной сети относятся наиболее развитые и населенные городские агломерации — столичная агломерация ПекинТяньцзинь, агломерация Шанхая, агломерация дельты Жемчужной реки и Сычуаньская впадина. Наиболее заметно плотность автодорог увеличилась в центральных и западных районах страны с заметно меньшей плотностью населения и более низким уровнем экономического развития. Исходя из расчетов, основное влияние на увеличение плотности автодорог в 2014–2022 гг. наибольшее влияние оказывали именно густота населения и стремление к увеличению связности между центрами и соседними округами, а не размер их ВРП. Протяженность автодорожной сети увеличилась в этот период на одну треть, значительно расширилась зона охвата автодорогами территории районов, прилегающих к главным ареалам концентрации дорожной сети.</p></abstract><trans-abstract xml:lang="en"><p>To analyze the uneven distribution of the People’s Republic of China highway network (expressways and Class 1 and Class 2 roads) in dynamics (2014–2022), unique fractional territorial statistics for 334 cells (districts), available only in Chinese, as well as cartometric calculations using data from the Open Street Map service, were used. This made it possible to compile very detailed maps of the density of highways, which revealed geographical differences in the level of transport development of the territory of China, which are not visible on ordinary maps and even in the national atlas of the People’s Republic of China. The main areas of development of the road network and the cores of its concentration, as well as spatial gaps in the pattern of this development, have been identified. The main areas of concentration of the road network include the most developed and populated urban agglomerations—the Beijing-Tianjin metropolitan area, the Shanghai agglomeration, the Pearl River Delta agglomeration and the Sichuan Basin. The density of roads has increased most noticeably in the central and western regions of the country with significantly lower population density and lower level of economic development. Based on calculations, the main impact on the increase in highway density in 2014–2022 was caused by the density of the population and the desire to increase connectivity between the centers and neighboring districts, rather than the size of their GRP. The length of the road network increased by one third during this period, and the coverage area of the territories adjacent to the main areas of concentration of the road network significantly expanded.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>автомобильные дороги Китая</kwd><kwd>транспортная сеть</kwd><kwd>транспортная система Китая</kwd></kwd-group><kwd-group xml:lang="en"><kwd>highways</kwd><kwd>transport network</kwd><kwd>China</kwd><kwd>transport geography</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено в рамках темы Государственного задания Института географии РАН “Социально-экономическое пространство  России в условиях глобальных трансформаций: внутренние и внешние вызовы” № 124032900015-3 (FMWS-2024–0008).</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Лю Ж., Шувалова Н.А. 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