Identification of potential rockfall source areas at a regional scale using a DEM-based geomorphometric analysis

被引:79
|
作者
Loye, A. [1 ]
Jaboyedoff, M. [1 ]
Pedrazzini, A. [1 ]
机构
[1] Univ Lausanne, Inst Geomat & Risk Anal, Lausanne, Switzerland
关键词
HAZARD; SUSCEPTIBILITY; FALL;
D O I
10.5194/nhess-9-1643-2009
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The availability of high resolution Digital Elevation Models (DEM) at a regional scale enables the analysis of topography with high levels of detail. Hence, a DEM-based geomorphometric approach becomes more accurate for detecting potential rockfall sources. Potential rockfall source areas are identified according to the slope angle distribution deduced from high resolution DEM crossed with other information extracted from geological and topographic maps in GIS format. The slope angle distribution can be decomposed in several Gaussian distributions that can be considered as characteristic of morphological units: rock cliffs, steep slopes, footslopes and plains. A terrain is considered as potential rockfall sources when their slope angles lie over an angle threshold, which is defined where the Gaussian distribution of the morphological unit 'Rock cliffs' become dominant over the one of 'Steep slopes'. In addition to this analysis, the cliff outcrops indicated by the topographic maps were added. They contain however 'flat areas', so that only the slope angles values above the mode of the Gaussian distribution of the morphological unit 'Steep slopes' were considered. An application of this method is presented over the entire Canton of Vaud (3200 km(2)), Switzerland. The results were compared with rockfall sources observed on the field and orthophotos analysis in order to validate the method. Finally, the influence of the cell size of the DEM is inspected by applying the methodology over six different DEM resolutions.
引用
收藏
页码:1643 / 1653
页数:11
相关论文
共 50 条
  • [1] A New Approach for Identification of Potential Rockfall Source Areas Controlled by Rock Mass Strength at a Regional Scale
    Wang, Xueliang
    Liu, Haiyang
    Sun, Juanjuan
    [J]. REMOTE SENSING, 2021, 13 (05) : 1 - 13
  • [2] Probabilistic identification of rockfall source areas at regional scale in El Hierro (Canary Islands, Spain)
    Rossi, Mauro
    Sarro, Roberto
    Reichenbach, Paola
    Maria Mateos, Rosa
    [J]. GEOMORPHOLOGY, 2021, 381
  • [3] Definition and mapping of potential rockfall source and propagation areas at a regional scale in Basilicata region (Southern Italy)
    Losasso, Lucia
    Derron, Marc-Henri
    Horton, Pascal
    Jaboyedoff, Michel
    Sdao, Francesco
    [J]. RENDICONTI ONLINE SOCIETA GEOLOGICA ITALIANA, 2016, 41 : 175 - 178
  • [4] Rockfall source areas identification at local scale by integrating discontinuity-based threshold slope angle and rockfall trajectory analyses
    Yan, Jianhua
    Chen, Jianping
    Tan, Chun
    Zhang, Yansong
    Liu, Yongqiang
    Zhao, Xiaohan
    Wang, Qing
    [J]. ENGINEERING GEOLOGY, 2023, 313
  • [5] Identification of rockfall source areas using the seed cell concept and bivariate susceptibility modelling
    Tosevski, Aleksandar
    Pollak, Davor
    Perkovic, Dario
    [J]. BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, 2021, 80 (10) : 7551 - 7576
  • [6] Identification of rockfall source areas using the seed cell concept and bivariate susceptibility modelling
    Aleksandar Toševski
    Davor Pollak
    Dario Perković
    [J]. Bulletin of Engineering Geology and the Environment, 2021, 80 : 7551 - 7576
  • [7] Rockfall Hazard Assessment in the Taihang Grand Canyon Scenic Area Integrating Regional-Scale Identification of Potential Rockfall Sources
    Zhan, Jiewei
    Yu, Zhaoyue
    Lv, Yan
    Peng, Jianbing
    Song, Shengyuan
    Yao, Zhaowei
    [J]. REMOTE SENSING, 2022, 14 (13)
  • [8] Land scale division and multifunctional evaluation for Fuping County, China, based on DEM-based watershed analysis
    Yin, Haikui
    Wang, Shutao
    Chen, Yaheng
    Zhou, Yapeng
    Chen, Yuqi
    Xu, Hao
    [J]. SCIENTIFIC REPORTS, 2024, 14 (01):
  • [9] Classification of Eucalyptus plantation Site Index (SI) and Mean Annual Increment (MAI) prediction using DEM-based geomorphometric and climatic variables in Brazil
    Dos Reis, Aliny Aparecida
    Franklin, Steven E.
    Acerbi Junior, Fausto Weimar
    Ferraz Filho, Antonio Carlos
    de Mello, Jose Marcio
    [J]. GEOCARTO INTERNATIONAL, 2022, 37 (05) : 1256 - 1273
  • [10] IDENTIFICATION OF WET AREAS IN FOREST BY USING LIDAR BASED DEM
    Ivanovs, Janis
    Sietina, Irina
    Spalva, Gints
    [J]. 8TH INTERNATIONAL SCIENTIFIC CONFERENCE RURAL DEVELOPMENT 2017: BIOECONOMY CHALLENGES, 2017, : 611 - 615