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Development of an intelligent geographic information system for mountain roads monitoring: Ground data collection and analysis

Gulnara Nurpeissova (), Ainur Kairanbayeva (), Serik Nurakynov (), Dina Panyukova () and Kerey Panyukov ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 1, 168-190

Abstract: This study examines the development of an intelligent geographic information system for mountain road monitoring. To make well-informed and timely management decisions in the planning, construction, and maintenance of mountain roads, and to anticipate potential critical situations and their effects on road conditions, it is imperative to employ modern methodologies. This study involves data collection from a specific section of a mountain road situated near Almaty, Kazakhstan. We gathered data on the road section through visual assessment, measurements of the coefficient of adhesion, and the acquisition of material samples from the structural layers of the roadbed. Based on the visual assessment and surface adhesion measurements, it became evident that the deformation of the studied road section, which includes a network of cracks and "non-standard" transverse cracks, is attributed to mountain mass shifts and water flows from slopes. Laboratory analysis of the collected samples revealed that excessive water saturation could result in cracks during freeze-thaw cycles, while a low resistance coefficient would lead to softening during humid conditions. An Intelligent Geographic Information System (IGIS) will incorporate the collected data alongside open remote sensing and weather data. The objective is to utilize this integrated system in the future for forecasting road conditions and maintenance requirements for similar roads in mountainous regions of the area. The measurements are carried out according to the state standards. That makes the system useful for government management purposes.

Keywords: Forecasting; Geographic information system; Landslide processes; Remote sensing; Road condition; Road construction material; Road pavement; Road survey data; Weather data. (search for similar items in EconPapers)
Date: 2025
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