ENVIRONMENT MONITORING ALONG CHINA-EUROPE RAILWAY EXPRESS WITH REMOTE SENSING AND ARTIFICIAL INTELLIGENT TECHNOLOGY: A REGIONAL COLLABORATION PROJECT BETWEEN CHINA AND SERBIA

Abstract. The operation of the China-Europe railways has facilitated economic development and improved regional connectivity along the route, while impacting the environment. Effective monitoring of the environmental status along the railway is necessary to promote the sustainable development of the Belt and Road Initiative (BRI). Existing remote sensing-based monitoring methods depend on local prior knowledge and model selection, resulting in insufficient specificity when applying to the China-Europe railways, which have a large spatial extent and complex ground variability across nations. Financed by the 2020 China-CEEC Joint Education Project of Institutions of Higher Education, we combined the preponderant research fields of the Beijing University of Civil Engineering and Architecture (BUCEA) and the University of Novi Sad (UNS) and established an environmental monitoring process based on artificial intelligence and remote sensing techniques. More specifically, an online annotating platform and deep learning based classification procedure were established, followed by environmental analysis conducted with comprehensive indicators and a difference-in-difference method. Our results provide 10 years of monitoring data on the environmental status of the China-Europe Railway Express, based on which, the impacts of the economic corridors on the local environment before & after the establishment were evaluated specifically. This collaborative project supports the BRI initiative and highlights the potential for international collaboration in large-scale environmental monitoring.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
ENVIRONMENT MONITORING ALONG CHINA-EUROPE RAILWAY EXPRESS WITH REMOTE SENSING AND ARTIFICIAL INTELLIGENT TECHNOLOGY: A REGIONAL COLLABORATION PROJECT BETWEEN CHINA AND SERBIA ; volume:X-5/W1-2023 ; year:2023 ; pages:31-36 ; extent:6
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; X-5/W1-2023 (2023), 31-36 (gesamt 6)

Klassifikation
Biowissenschaften, Biologie

Urheber
Guo, X.
Huang, S.
Jiang, J.
Pavlovic, M.
Ding, S.
Vilotic, M.
Li, Y.

DOI
10.5194/isprs-annals-X-5-W1-2023-31-2023
URN
urn:nbn:de:101:1-2023052504252437734862
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
14.08.2025, 11:00 MESZ

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Beteiligte

  • Guo, X.
  • Huang, S.
  • Jiang, J.
  • Pavlovic, M.
  • Ding, S.
  • Vilotic, M.
  • Li, Y.

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