Potential of two submontane broadleaved species (Acer opalus, Quercus pubescens) to reveal spatiotemporal patterns of rockfall activity

Favillier, Adrien; Lopez-Saez, Jérôme; Corona, Christophe; Trappmann, Daniel; Toe, David; Stoffel, Markus; Rovéra, Georges; Berger, Frédéric

doi:10.1016/j.geomorph.2015.06.010

Cited by 20 publications

(13 citation statements)

References 54 publications

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“…5). Similarly, a high barrier effect level BARI(x) was reached after 400 m. These values are in the same order of magnitude as those observed in dendrogeomorphological studies carried out in France where the number of rock impacts on trees was measured along the slope direction (Favillier et al, 2015). Therefore, consider a homogeneous forest stand on distances shorter than 400 m is realistic and the results presented in this study can directly be used in such conditions.…”

Section: Interests and Limitations Of Numerical Modelling In Rockfallsupporting

confidence: 78%

Novel quantitative indicators to characterize the protective effect of mountain forests against rockfall

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Bourrier

Monnet

et al. 2016

Ecological Indicators

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International audienceNatural hazards are frequent in mountain areas where they regularly cause casualties and damages to human infras-tructures. Mountain forests contribute in mitigating these hazards, in particular rockfalls. Assessing the protective effect of a forest against rockfall is a difficult task for both forest managers and rockfall experts. Accurate and simple tools are therefore required to efficiently evaluate the level of protection that results from the presence of forest. This study defines three novel indicators to quantify the protective effect of forests against rockfalls, regarding 1) the reduction of the frequency of rockfalls, 2) the reduction of their maximum intensity, and 3) the combination of the reduction of the frequency and the energy of the rocks. The first two indicators are relevant for rockfall experts whereas the third is mostly interesting for foresters as it summarizes the protective effect of forest. The Rockyfor3D model was adapted and used to simulate rockfalls propagation on 3886 different forest stands located in all the French Alps. The results of the simulations were used to calculate the three indicators for each forest stand. Finally, the relations between the forest structures and compositions and the indicators values were investigated. Our principal result shows that only three forest characteristics are required to accurately predict the indicators and evaluate the protective level of a forest against rockfall. The two first variables correspond to the basal area and the mean diameter at breast height (DBH) of the forest stand which are two parameters commonly used by forest managers. The third characteristic is the length of forest in the maximum slope direction which can be computed with a geographic information system (GIS). The method proposed in this study is easily reproducible and is suitable to evaluate the protective effect of European mountain forests at different scales. At local scale, the proposed indicators can enrich rockfall studies in which forests are usually set aside to simplify the evaluation. Moreover, the indicators may find direct applications with foresters by allowing them to identify the protective level of their forest and consequently to adapt their management. Finally, the indicators are convenient to perform spatial analysis and produce maps of the protective effect of mountain forests that could find many applications in land settlement or evaluation of ecosystem services

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Section: Interests and Limitations Of Numerical Modelling In Rockfallsupporting

confidence: 78%

Novel quantitative indicators to characterize the protective effect of mountain forests against rockfall

Dupire

Bourrier

Monnet

et al. 2016

Ecological Indicators

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“…For example, on long forested slopes, keeping a dense forest is not as important as on short slopes and a lower stand density could make the regeneration process easier without consequences on the protective effect against rockfall. Nevertheless, if the rockfall frequency is very high or the slope very steep the rate of broken trees after block impacts may increase significantly (Favillier et al, 2015). Therefore, in these configurations the stem density has to stay high enough to maintain a high protective effect even if the length of forest is important.…”

Section: Implications For Forest Managementmentioning

confidence: 99%

“…A significant part of the forested area in the Alps provides a natural protection against rockfall Brang et al, 2001). On forested slopes located below a departure area, it is common to observe scars on trees resulting from one or several rockfall impacts (Favillier et al, 2015). Each impact against a tree reduces the energy of the block which results in a lower velocity or a complete stop (Bertrand et al, 2013;.…”

Section: Introductionmentioning

confidence: 99%

The protective effect of forests against rockfalls across the French Alps: Influence of forest diversity

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Bourrier

Monnet

et al. 2016

Forest Ecology and Management

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International audienceThe role of forests in the mitigation of natural hazards has been repeatedly demonstrated. The protective effect of mountain forests against rockfalls has especially been pointed out because it can constitute a natural and cost-effective protection measure in many situations. However, this particular ecosystem service may substantially differ according to the structure and the composition of the forest. Until now, the rockfall protection capability has always been studied at a local scale with only few forest types. Moreover, the comparison of the protective effect of the different forest types studied remains difficult because different methods and indicators were used. For the same reasons, it is not possible to draw conclusions about the influence of biological and structural diversities on the protection capabilities of forests from former works. The aims of this study were (1) to quantitatively assess the protective effect of forests at the French Alps scale and build a classification based on the protection capability, (2) to compare the protective effect of the different forest types present in the French Alps and (3) to analyse the relations between the protective effect and the forest diversity in terms of stand structure and tree composition. For this purpose, the model Rockyfor3D was used to simulate the propagation of rocks on 3886 different forest plots spread over the whole French Alps. Quantitative indicators characterizing the protective effect of each forest plot were then calculated from the simulation results and used to perform the different analyses. Our results emphasized the importance of taking into account the length of forest in the maximum slope direction for an accurate assessment of the protective effect. Thus, the minimum length of forest to get a reduction of 99% of the rockfall hazard was chosen as indicator to compare protective effect between forests. Using this indicator, half of the French Alpine forests presented a high level of protection after a short forested slope (190 m). A decreasing gradient in the protection capabilities was observed from forest types dominated by broadleaved species to those dominated by conifer species. Moreover, considering an equivalent proportion of conifers, stands dominated by shade-tolerant tree species showed better ability to reduce rockfall hazard. Finally, our study highlighted that a high biodiversity and a structural heterogeneity within the forest have a positive effect on the reduction of rockfalls hazard

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“…Due to the fact that artificial neural networks have various applications such as accurate prediction of complex material behavior, it could be applied for damage detection and structural integrities in corresponding multiple-variable problems. (Alves et al, 2015;Andrejiova, Grincova, & Marasova, 2019;Bhowmik, Krishnan, Hazra, & Pakrashi, 2019;Dia, Dieng, Gaillet, & Gning, 2019;Dorval, Meredieu, & Danjon, 2016;Egnew, Roueche, & Prevatt, 2018;Favillier et al, 2015;Kabir, Sadiq, & Tesfamariam, 2016;Kim, Hwang, & Jung, 2017;Noori Hoshyar, Samali, Liyanapathirana, & Taghavipour, 2019;Pérez-Ruiz et al, 2018;Wang et al, 2018; (Fakih, Mustapha, Tarraf, Ayoub, & Hamade, 2018;Froustey et al, 2017;J. Li & Zhang, 2016;Mayer & Mayer, 2019;Ovid'Ko, Sheinerman, Skiba, Krasnitiskiy, & Smirnov, 2015;Panettieri, Leclerc, Jumel, & Guitard, 2018;Y.…”

Section: Annmentioning

confidence: 99%

Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances<strong> </strong>

Mosavi¹

2019

Preprint

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The loss of integrity and adverse effect on mechanical properties can be concluded as attributing miro/macro-mechanics damage in structures, especially in composite structures. Damage as a progressive degradation of material continuity in engineering predictions for any aspects of initiation and propagation requires to be identified by a trustworthy mechanism to guarantee the safety of structures. Besides the materials design, structural integrity and health are usually prone to be monitored clearly. One of the most powerful methods for the detection of damage is machine learning (ML). This paper presents the state of the art of ML methods and their applications in structural damage and prediction. Popular ML methods are identified and the performance and future trends are discussed.

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Potential of two submontane broadleaved species (Acer opalus, Quercus pubescens) to reveal spatiotemporal patterns of rockfall activity

Cited by 20 publications

References 54 publications

Novel quantitative indicators to characterize the protective effect of mountain forests against rockfall

Novel quantitative indicators to characterize the protective effect of mountain forests against rockfall

The protective effect of forests against rockfalls across the French Alps: Influence of forest diversity

Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances<strong> </strong>

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