An Integrated Approach for Monitoring and Information Management of the Guanling Landslide (China)

Abstract

Landslide triggered by earthquake or rainstorm often results in serious property damage and human casualties. It is, therefore, necessary to establish an emergency management system to facilitate the processes of damage assessment and decision-making. This paper has presented an integrated approach for mapping and analyzing spatial features of a landslide from remote sensing images and Digital Elevation Models (DEMs). Several image interpretation tools have been provided for analyzing the spatial distribution and characteristics of the landslide on different dimensions: (1D) terrain variation analysis along the mass movement direction and (3D) morphological analysis. In addition, the results of image interpretation can be further discussed and adjusted on an online cooperating platform, which was built to improve the coordination of all players involved in different phases of emergency management, e.g., hazard experts, emergency managers, and first response organizations. A mobile-based application has also been developed to enhance the data exchange and on-site investigation. Our pilot study of Guanling landslide shows that the presented approach has the potential to facilitate the phases of landslide monitoring and information management, e.g., hazard assessment, emergency preparedness, planning mitigation, and response.

Application of a GIS-Based Slope Unit Method for Landslide Susceptibility Mapping along the Longzi River, Southeastern Tibetan Plateau, China

“…1 a i has the same importance as a j 3 a i is slightly more important than a j 5 a i is significantly more important than a j 7 a i is much more strongly important than a j 9 a i is extremely more important than a j 2, 4,6,8 Represents the intermediate value of the above Judgement If R c < 0.1, the judgement matrix is considered to have good consistency, which suggests the weight distribution is reasonable. Otherwise, the judgement matrix needs to be adjusted until reasonable consistency is achieved.…”

“…In recent years, different models have been used for landslide susceptibility mapping, such as an analytical hierarchy process [7][8][9], logistic regression [10,11], an artificial neural network [12,13], support vector machines [14,15], the entropy method, and the frequency ISPRS Int. J. Geo-Inf.…”

The application of civic technologies in a field survey of landslides

“…Measurements made using Kinect‐ or Tango‐type systems could also be applied in a crowdsourcing context (Hyyppä et al, ), allowing non‐experts to undertake specialized tasks for certain purposes more quickly and at lower costs (Capineri, ). Future landslide hazard studies require the use of multiscale and multitemporal spatially referenced data from a wide variety of sources that are shared through web‐based platforms (Hou, Lu, Wu, Xue, & Li, ). Computer‐aided territorial planning and accessibility to geographic data might support the development of breakthrough ideas in spatial planning and related decision‐making processes (Matta & Serra, ).…”

Identification of Micro-Scale Landforms of Landslides Using Precise Digital Elevation Models

“…The use of multiscale analytical techniques is becoming increasingly important due to the availability of fine-resolution digital elevation models (DEMs) and the inherent scale-dependency of many DEM-derived attributes [22]. A future vision for landslide mapping and monitoring is based on the use of multiscale and multitemporal spatially-referenced data from a wide variety of sources that are shared through web-based platforms [23]. In this article we present a multiscale approach for the identification of landslide features from data gathered by various remote sensing technologies at different scales but with similar data accuracy.…”