<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Landslides are among the major environmental hazards with large-scale socio-economic and environmental impacts that jeopardize socio-economic wellbeing in mountainous regions. Landslides are due to the interaction of several complex factors such as local or regional geology, geomorphology, topography, and seismic motions. The goal of this study is to review published articles on causes and effects of landslides in Central Asia throughout 2000–2020. In line with this goal, we have collected (using Scopus database), reviewed, and analyzed 79 papers published during 2000–2020. Our results revealed an increasing number of landslide studies in Central Asia during the period under investigation, with authors from Belgium dominating in the published outcomes (28% of total), followed by authors from Central-Asian countries. After then, the paper analyses the mostly applied models and frequently identified driving conditions and triggers of landsliding, such as aspect, altitude, soil types, precipitation, earthquakes and human interventions. Geographic information system (GIS) and remote sensing (RS) had not commonly been used in the papers between 2000 and 2010, and they have progressively been applied in landslide studies in Central Asia in the last decade. According to our analysis, geotechnical, geophysical and statistical methods were preferably used for the landslide studies in Central Asia.</p>
</abstract>

Landslides are among the major environmental hazards with large-scale socio-economic and environmental impacts that jeopardize socio-economic wellbeing in mountainous regions. Landslides are due to the interaction of several complex factors such as local or regional geology, geomorphology, topography, and seismic motions. The goal of this study is to review published articles on causes and effects of landslides in Central Asia throughout 2000–2020. In line with this goal, we have collected (using Scopus database), reviewed, and analyzed 79 papers published during 2000–2020. Our results revealed an increasing number of landslide studies in Central Asia during the period under investigation, with authors from Belgium dominating in the published outcomes (28% of total), followed by authors from Central-Asian countries. After then, the paper analyses the mostly applied models and frequently identified driving conditions and triggers of landsliding, such as aspect, altitude, soil types, precipitation, earthquakes and human interventions. Geographic information system (GIS) and remote sensing (RS) had not commonly been used in the papers between 2000 and 2010, and they have progressively been applied in landslide studies in Central Asia in the last decade. According to our analysis, geotechnical, geophysical and statistical methods were preferably used for the landslide studies in Central Asia.

Landslides in Central Asia: a review of papers published in 2000–2020 with a particular focus on the importance of GIS and remote sensing techniques

GeoScape

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Landslides are among the major environmental hazards with large-scale socio-economic and environmental impacts that jeopardize socio-economic wellbeing in...

Landslides in Central Asia: a review of papers published in 2000–2020 with a particular focus on the importance of GIS and remote sensing techniques

Pubblicato online: 30 dic 2021

Pagine: 134 - 145

Ricevuto: 27 giu 2021

Accettato: 15 nov 2021

DOI: https://doi.org/10.2478/geosc-2021-0011

Parole chiave
Landslide, Central Asia, Geo-information Systems, Remote Sensing, Conditioning factors, Models

© 2020 Sayidjakhon Khasanov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Landslides in Central Asia: a review of papers published in 2000–2020 with a particular focus on the importance of GIS and remote sensing techniques

Pubblicato online: 30 dic 2021

Pagine: 134 - 145

Ricevuto: 27 giu 2021

Accettato: 15 nov 2021

DOI: https://doi.org/10.2478/geosc-2021-0011

Parole chiaveLandslide, Central Asia, Geo-information Systems, Remote Sensing, Conditioning factors, Models

© 2020 Sayidjakhon Khasanov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Landslide, Central Asia, Geo-information Systems, Remote Sensing, Conditioning factors, Models