Landslides investigations from geoinformatics perspective: quality, challenges, and recommendations

• Main Authors: Saied Pirasteh, Jonathan Li
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2017-12-01
• Series: Geomatics, Natural Hazards & Risk
• Subjects: landslide; remote sensing and gis; dem; als; lidar; uav
• Online Access: http://dx.doi.org/10.1080/19475705.2016.1238850

Understanding and assessing the landslides is immensely important to scientists and policy-makers alike. Remote sensing conventional methods and modelling approaches in geographical information system (GIS) tend to be limited to authentic quality and spatial coverage. This study aims to identify challenges and quality of landslides assessment based on remotely sensed data by the mean of existing works of the literature and practices we attempted in the Zagros and Alborz Mountains in Iran and the red rock shield Lake, China. Remote sensing data for landslides investigations require a high-resolution digital elevation model (DEM) from either aerial photography, satellite images, airborne laser scanning (ALS) or terrestrial Light Detection and Ranging (LiDAR) derived in order to enable a reliable and valid output performance. This paper presents weaknesses and strengths of the existing remote sensing techniques in the last decades and further provides recommendations for a reliable approach to the future landslide studies. Also, this study estimates the operational use of state-of-the-art technologies (i.e. unmanned airborne vehicle (UAV)) for landslides assessment in the near future that is a realistic ambition if we can continue to build on recent achievements. However, this paper does not deliver a detailed methodology of a DEM generation from the remote sensing approach for landslides assessment.