dc.description.abstract |
Landslides are one of the important natural threats that often cause loss of life and property in
Kazakhstan. One of the regions affected by landslides of different types and sizes that occur for
different reasons in the country is the Rudny Altay Region in the east of Kazakhstan. This study deals
with the landslide susceptibility assessment using remote sensing methods in Rudny Altai region of
East Kazakhstan. The landslide inventory map was created based on historical information, remote
sensing images, and field surveys. Images of 4 selected sites (Tikhaya, Berezovka, Manat and
Chernovaya) were examined to determine potential landslide susceptibility. In combined Analytical
Hierarchy Process method and GIS (AHP-GIS) used in this study, values are assigned to the selected
indicators (layers) from low to high landslide susceptibility potential (1-5). Thus, to assess the potential
of landslide processes, the following indicators were selected: calculated values of surface slope
according to the NASADEM digital elevation model, soil density, average monthly precipitation
OpenLandMap, and median values of the normalized difference vegetation index (NDVI). As a result,
the data were obtained and maps of landslide susceptibility of the study areas were created. According
to the research results, the highest coefficient of damage to the area by landslide processes is noted in
Tikhaya, and the lowest - in Manat. On average, the coefficient of landslide damage in the Rudny Altai
area is 0.03, which is a low indicator for this region. The results obtained with the study showed that
about 25% of the study area had moderate to high landslide susceptibility. Accordingly, landslide
susceptibility is high in the southwest and south of the study area, especially in mountainous areas
where slopes are steep and in sloping areas in the south. It was revealed that the results obtained in this
study are quite successful in determining the landslide susceptibility of the study area. The findings of
the study can contribute in the effective management of the Rudny Altai Region. |
ru |