Integrating spatial, temporal, and size probabilities for the annual landslide hazard maps in the Shihmen watershed, Taiwan

Chen, Su‐Chin

doi:10.5194/nhess-13-2353-2013

Cited by 21 publications

(4 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most of these landslides cannot be related to major triggering events, such as intense rainstorms or strong earthquakes. Thus, an improvement of the spatiotemporal understanding of landslide processes in this region requires a systematic assessment of landslide events in the form of multi-temporal landslide inventories forming the basis for objective and spatially differentiated analyses of landslide hazard and risk [11,[16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data

et al. 2014

View full text Add to dashboard Cite

Abstract:In the past, different approaches for automated landslide identification based on multispectral satellite remote sensing were developed to focus on the analysis of the spatial distribution of landslide occurrences related to distinct triggering events. However, many regions, including southern Kyrgyzstan, experience ongoing process activity requiring continual multi-temporal analysis. For this purpose, an automated object-oriented landslide mapping approach has been developed based on RapidEye time series data complemented by relief information. The approach builds on analyzing temporal NDVI-trajectories for the separation between landslide-related surface changes and other land cover changes. To accommodate the variety of landslide phenomena occurring in the 7500 km 2 study area, a combination of pixel-based multiple thresholds and object-oriented analysis has been implemented including the discrimination of uncertainty-related landslide likelihood classes. Applying the approach to the whole study area for the time period between 2009 and 2013 has resulted in the multi-temporal identification of 471 landslide objects. A quantitative accuracy assessment for two independent validation sites has revealed overall high mapping accuracy (Quality Percentage: 80%), proving the suitability of the developed approach for efficient spatiotemporal landslide mapping over large areas, representing an important prerequisite for objective landslide hazard and risk assessment at the regional scale. OPEN ACCESSRemote Sens. 2014, 6 8027

show abstract

Section: Introductionmentioning

confidence: 99%

Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Apart from their potential to be replicated elsewhere, this set of factors was also selected for their suitability to capture both intrinsic (topography, geology and hydrology) and extrinsic (climate and land cover changes) [39], [40] aspects, being similar to those used in previous related studies [41]- [43]. Other variables such as slope aspect and wind speed were not considered for this case study.…”

Section: B Description Of the Factors Contributing To Rockfall Hazardmentioning

confidence: 99%

Spatial Statistical Modeling of Rockfall Hazard in a Mountainous Road in Cantabria (Spain)

Jato-Espino

Roldán-Valcarce

Collazos-Arias³

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

Rockfall events are one of the most frequent types of mass wasting in mountainous areas, causing service and traffic disruption, as well as infrastructure and human damage. Hence, having accurate tools to model these hazards becomes crucial to prevent fatalities, especially in a context of Climate Change whereby the effects of these phenomena might be exacerbated. Under this premise, this research concerned the development of a framework for assessing rockfall hazard in mountainous areas. First, a set of factors expected to favour rockfalls were processed and aggregated using spatial analysis tools, yielding a series of hazard maps with which to fit observed data through statistical modelling. The validation process was undertaken with the support of a database containing the number of rocks removed from a mountainous road section located in Cantabria, northern Spain. The results achieved, which demonstrated the accuracy of the proposed approach to reproduce rockfall hazard using frequency data, highlighted the primary role played by factors such as slope, runoff threshold and precipitation to explain the occurrence of these events. The effects of Climate Change were considerably influenced by the fluctuations in the projections of precipitation, which limited the variations in the spatial distribution and magnitude of rockfall hazard.

show abstract

“…Geological hazards are one of the most destructive natural hazard phenomena worldwide [1,2], often causing great harm to the lives and survival of local inhabitants and seriously damaging infrastructure development. Geohazard risk assessment has been an effective tool for geohazard prevention and control among government departments [3,4], and its results can show the probability of a geohazard's occurrence and its scale [5], so exploring geohazard risk assessment at different scales is always an important topic for the scientific community.…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment and Control for Geohazards at Multiple Scales: An Insight from the West Han River of Gansu Province in China

Ye,

Tian,

et al. 2024

Water

View full text Add to dashboard Cite

Risk assessment provides a powerful tool for the early warning and risk mitigation of geohazards. However, few efforts have been made regarding risk assessment and dynamic control at multiple scales. With respect to this issue, the West Han River catchment in the Gansu Province of China was taken as a study area, and geohazard risk assessments at three different scales were carried out, namely regional, local and site scales. Hazard assessment was performed using the combination of the information value and hierarchical analysis models, infinite slope stability model, and FLO-2D model. Vulnerability was estimated from two viewpoints, including physical vulnerability and social vulnerability, by applying remote sensing and semi-quantitative methods. Finally, risk mapping and zonation was obtained from the products of hazard and vulnerability, and corresponding measures of risk management and control at different scales were recommended. The results indicated that the geohazard risk at the regional scale was the highest under the earthquake and rainfall conditions with a 100-year (100a) return period, respectively, and the area of very high risk level reached 5%. When the rainfall condition had a return period of 50 years, only 1% of the area was located in the very high-risk region. Additionally, the overall risk was higher in the central and northeastern parts of the region under heavy rainfall and earthquake conditions. The overall risk level in Longlin-Leiba Town (at the local scale) responded more significantly to heavy rainfall conditions, with higher risk in the southwestern, central, and northeastern parts of the region. For the site scale (Wujiagou debris flow), only 2% of the total area was identified as very high-risk even under heavy rainfall with a 100a return period, but the proportions for the low and moderate levels reached 30% and 56%, respectively. The present study can provide scientific references for geohazard risk assessment and control.

show abstract

Integrating spatial, temporal, and size probabilities for the annual landslide hazard maps in the Shihmen watershed, Taiwan

Cited by 21 publications

References 33 publications

Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data

Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data

Spatial Statistical Modeling of Rockfall Hazard in a Mountainous Road in Cantabria (Spain)

Risk Assessment and Control for Geohazards at Multiple Scales: An Insight from the West Han River of Gansu Province in China

Contact Info

Product

Resources

About