The geography of Kazakhstan is characterized by a diverse landscape and a small population. Therefore, certain automobile roads pass through unpopulated mountain regions, where physical road diagnostics are rare or almost absent, while landscape factors continue to affect the road. However, modern geo-information approaches and remote sensing could effectively provide the road diagnostics necessary to make timely control decisions regarding a road’s design, construction, and maintenance. To justify this assumption, we researched the deformation of a mountain road near Almaty city. Open access satellite images of and meteorological archival data for the region were processed. The resulting data were compared to validate the road’s deformation triggers. Extreme weather conditions’ impacts could be identified via road destruction (nearly 40 m longitudinal cracks, 15 m short transversal cracks, and two crack networks along a 50 m road section). The remotely sensed parameters (vertical displacement velocity, slope exposure, dissections, topographic wetness index, aspect, solar radiation, SAVI, and snow melting) show the complexity of triggers of extensive road deformations. The article focuses only on open access data from remote sensing images and meteorological archives. All the resulting data are available and open for all interested parties to use.

The research is part of the �Design of an intelligent system to forecast landslides' processes and their influence on the roads' technical and operational characteristics� project financed by the Ministry of Education and Science of the Republic of Kazakhstan by AP09260066 program. The research goal is in surveying deformed parts of �Almaty-Cosmostation� automobile road nearby critical slopes to identify in the next phases the causes of pavement degradation and formulate then the recommendation to prevent such degeneration. This site was chosen due to the extreme danger associated with the possible closure of the river flowing through the gorges along the road under study due to a landslide slope. This can lead to a change in the riverbed, the formation of a strong water flow, which will create a danger to the population, will lead to significant material damage. Main results. Within the framework of this project, new knowledge will be gained in the theory of forecasting the occurrence of landslide processes and their impact on the technical and economic indicators of highways, which undoubtedly has applied significance and contributes to the widespread introduction of intelligent systems for forecasting and making industry decisions. Detailed engineering and geological research of deformed parts of �Almaty-Cosmostation� automobile road nearby critical slopes are provided. The article results with the field researches to formulate causes of deterioration of the road pavement and formation of longitudinal and transversal cracks on it. To develop intelligent models for predicting landslide processes and their impact on the state of the road, the following types of work were carried out: georadar sounding method; Earth remote sensing methods; ground-satellite geodesy method; modeling and training of intelligent systems. Conclusions: The surface smoothness of the road pavement is partly below the minimum permissible level. The causes of the �irregular� (unusual) transversal cracks should be associated with slides of the rock masses and water falling from the rock slopes. Suggested causes of the grading�s slide slopes� erosion are the faint provision of surface drainage for the road pavement. The unevenness of the pavement on a micro level is connected to the uncompacted enough asphaltic concrete pavement and other pavement�s layers. The field researches� results will be used for training and testing of intellectual models.

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