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| 1 | Debris Flows Risk Analysis and Direct Loss Estimation:the Case Study of Valtellina di Tirano,Italy显示文摘Landslide risk analysis is one of the primary studies providing essential instructions to the subsequent risk management process. The quantification of tangible and intangible potential losses is a critical step because it provides essential data upon which judgments can be made and policy can be formulated. This study aims at quantifying direct economic losses from debris flows at a medium scale in the study area in Italian Central Alps. Available hazard maps were the main inputs of this study. These maps were overlaid with information concerning elements at risk and their economic value. Then, a combination of both market and construction values was used to obtain estimates of future economic losses. As a result, two direct economic risk maps were prepared together with risk curves, useful to summarize expected monetary damage against the respective hazard probability. Afterwards, a qualitative risk map derived using a risk matrix officially provided by the set of laws issued by the regional government, was prepared. The results delimit areas of high economic as well as strategic importance which might be affected by debris flows in the future. Aside from limitations and inaccuracies inherently included in risk analysis process, identification of high risk areas allows local authorities to focus their attention on the 'hot-spots', where important consequences may arise and local(large) scale analysis needs to be performed with more precise cost-effectiveness ratio. The risk maps can be also used by the local authorities to increase population's adaptive capacity in the disaster prevention process. | Jan BLAHUT Thomas GLADE Simone STERLACCHINI | 2014 | Journal of Mountain Science2014，11，2： | 5 |
| 2 | National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data显示文摘China is one of the countries where landslides caused the most fatalities in the last decades. The threat that landslide disasters pose to people might even be greater in the future, due to climate change and the increasing urbanization of mountainous areas. A reliable national-scale rainfall induced landslide susceptibility model is therefore of great relevance in order to identify regions more and less prone to landsliding as well as to develop suitable risk mitigating strategies. However, relying on imperfect landslide data is inevitable when modelling landslide susceptibility for such a large research area. The purpose of this study is to investigate the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China. In this context, it is aimed to explore the benefit of mixed effects modelling to counterbalance associated bias propagations. Six influencing factors including lithology, slope,soil moisture index, mean annual precipitation, land use and geological environment regions were selected based on an initial exploratory data analysis. Three sets of influencing variables were designed to represent different solutions to deal with spatially incomplete landslide information: Set 1(disregards the presence of incomplete landslide information), Set 2(excludes factors related to the incompleteness of landslide data), Set 3(accounts for factors related to the incompleteness via random effects). The variable sets were then introduced in a generalized additive model(GAM: Set 1 and Set 2) and a generalized additive mixed effect model(GAMM: Set 3) to establish three national-scale statistical landslide susceptibility models: models 1, 2 and 3. The models were evaluated using the area under the receiver operating characteristics curve(AUROC) given by spatially explicit and non-spatial cross-validation. The spatial prediction pattern produced by the models were also investigated. The results show that the landslide inventory incompleteness had a substantial impact on the outcomes of the statistical landslide susceptibility models. The cross-validation results provided evidence that the three established models performed well to predict model-independent landslide information with median AUROCs ranging from 0.8 to 0.9.However, although Model 1 reached the highest AUROCs within non-spatial cross-validation(median of 0.9), it was not associated with the most plausible representation of landslide susceptibility. The Model 1 modelling results were inconsistent with geomorphological process knowledge and reflected a large extent the underlying data bias. The Model 2 susceptibility maps provided a less biased picture of landslide susceptibility. However, a lower predicted likelihood of landslide occurrence still existed in areas known to be underrepresented in terms of landslide data(e.g., the Kuenlun Mountains in the northern Tibetan Plateau). The non-linear mixed-effects model(Model 3) reduced the impact of these biases best by introducing bias-describing variables as random effects. Among the three models, Model 3 was selected as the best national-scale susceptibility model for China as it produced the most plausible portray of rainfall induced landslide susceptibility and the highest spatially explicit predictive performance(median AUROC of spatial cross validation 0.84) compared to the other two models(median AUROCs of 0.81 and 0.79, respectively). We conclude that ignoring landslide inventory-based incompleteness can entail misleading modelling results and that the application of non-linear mixed-effect models can reduce the propagation of such biases into the final results for very large areas. | Qigen Lin Pedro Lima Stefan Steger Thomas Glade Tong Jiang Jiahui Zhang Tianxue Liu Ying Wang | 2021 | Geoscience Frontiers2021，12，6： | 4 |
| 3 | Displacement characteristics and prediction of Baishuihe landslide in the Three Gorges Reservoir显示文摘In order to reach the designated final water level of 175 m, there were three impoundment stages in the Three Gorges Reservoir, with water levels of 135 m, 156 m and 175 m. Baishuihe landslide in the Reservoir was chosen to analyze its displacement characteristics and displacement variability at the different stages. Based on monitoring data, the landslide displacement was mainly influenced by rainfall and drawdown of the reservoir water level. However, the magnitude of the rise and drawdown of the water level after the reservoir water level reached 175 m did not accelerate landslide displacement. The prediction of landslide displacement for active landslides is very important for landslide risk management. The time series of cumulative displacement was divided into a trend term and a periodic term using the Hodrick-Prescott(HP) filter method. The polynomial model was used to predict the trend term. The extreme learning machine(ELM) and least squares support vector machine(LS-SVM) were chosen to predict theperiodic term. In the prediction model for the periodic term, input variables based on the effects of rainfall and reservoir water level in landslide displacement were selected using grey relational analysis. Based on the results, the prediction precision of ELM is better than that of LS-SVM for predicting landslide displacement. The method for predicting landslide displacement could be applied by relevant authorities in making landslide emergency plans in the future. | LI De-ying SUN Yi-qing YIN Kun-long MIAO Fa-sheng Thomas GLADE Chin LEO | 2019 | Journal of Mountain Science2019，16，9： | 3 |
| 4 | Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility显示文摘In recent decades, data-driven landslide susceptibility models(Dd LSM), which are based on statistical or machine learning approaches, have become popular to estimate the relative spatial probability of landslide occurrence. The available literature is composed of a wealth of published studies and that has identified a large variety of challenges and innovations in this field. This review presents a comprehensive up-to-date overview focusing on the topic of Dd LSM. This research begins with an introduction of the theoretical aspects of Dd LSM research and is followed by an in-depth bibliometric analysis of 2585 publications. This analysis is based on the Web of Science, Clarivate Analytics database and provides insights into the transient characteristics and research trends within published spatial landslide assessments. Following the bibliometric analysis, a more detailed review of the most recent publications from 1985 to 2020 is given. A variety of different criteria are explored in detail, including research design, study area extent,inventory characteristics, classification algorithms, predictors utilized, and validation technique performed. This section, dealing with a quantitativeoriented review expands the time-frame of the review publication done by Reichenbach et al. in 2018 by also accounting for the four years, 2017-2020. The originality of this research is acknowledged by combining together:(a) a recap of important theoretical aspects of Dd LSM;(b) a bibliometric analysis on the topic;(c) a quantitative-oriented review of relevant publications;and(d) a systematic summary of the findings, indicating important aspects and potential developments related to the Dd LSM research topic. The results show that Dd LSM are used within a wide range of applications with study area extents ranging from a few kilometers to national and even continental scales. In more than 70% of publications, a combination of the predictors, slope angle, aspect and geology are used. Simple classifiers, such as, logistic regression or approaches based on frequency ratio are still popular, despite the upcoming trend of applying machine learning algorithms. When analyzing validation techniques, 38% of the publications were not clear about the validation method used. Within the studies that included validation techniques, the AUROC was the most popular validation metric, being used accounting for 44% of the studies. Finally, it can be concluded that the application of new classification techniques is often cited as a main research scope, even though the most relevant innovation could also lie in tackling data-quality issues and research designs adaptations to fit the input data particularities in order to improve prediction quality. | Pedro LIMA Stefan STEGER Thomas GLADE Franny G.MURILLO-GARCIA | 2022 | Journal of Mountain Science2022，19，6： | 2 |
| 5 | A phase Ⅰ trial and pharmacokinetic study of aflibercept (VEGF Trap) in children with refractory solid tumors:a children's oncology group phase Ⅰ consortium report显示文摘 | Glade Bender J Blaney SM Borinstein S | | 0，，18： | 1 |
| 6 | Ultrasound-guided thoracic paravertebral blockade:a cadaveric study显示文摘 | Comie B Mc Glade D Ivanusic J | 2010 | Anesth Analg2010，110，6： | 1 |
| 7 | Intralesional steroid injection for proliferative parotid hemangiomas显示文摘 | Buckmiller LM Francis CL Glade RS | 2008 | Int J Pediatr Otorhinolaryngol2008，72，1： | 1 |
| 8 | Applying probability determination to refine landslide-triggering rainfall thresholds using an empirical 'Antecedent Daily Rainfall Model' 显示文摘 | Thomas Glade Michael Crozier Peter Smith | 2000 | Pure and Applied Geophysics2000，157，： | 1 |
| 9 | Vascular remodeling and clinical resistance to antiangiogenic cancer therapy 显示文摘 | Glade Bender J Cooney EM Kandel JJ | 2004 | Drug Resist Updat2004，7，： | 1 |
| 10 | CO2 laser resurfacing of intraoral lymphatic malformations: A 10-year experience 显示文摘 | Glade RS Buckmiller LM | 2009 | Int J Pediatr Otorhinolaryngol2009，73，10： | 1 |
| 11 | Intralesional steroid injection for proliferative parotid hemangiomas 显示文摘 | Buckmiller LM Francis CL Glade RS | 2008 | Int J Pediatr Otorbinolaryngol2008，72，1： | 1 |
| 12 | Immunoeapillarymigration with enzymelabeled antibodies: eapid quantification of C-reactive protein in humanplasma显示文摘 | Grubb AO | 1981 | Anal Biochem1981，116，： | 1 |
| 13 | Intralesional steroid injection for proliferative parotid hemangiomas显示文摘 | Buckmiller LM Francis CL Glade RS | 2008 | Int J Pediatr Otorhi- nolaryngol2008，72，1： | 1 |
| 14 | Weight regain after Roux-en- Y:a significant 20% complication related to PYY 显示文摘 | Meguid MM Glade MJ Middleton FA | 2008 | Nutrition2008，24，9： | 1 |
| 15 | Electric current enhanced defect mobility in Ni3 Ti intermetallics 显示文摘 | Javier E Garay Stephen C Glade Palak Asoka-kumar | 2004 | Applied Physics Letters2004，85，4： | 1 |
| 16 | Coblation adenotonsillectomy: an im Provement over electroeautery technique显示文摘 | Glade R S Pearson S E Zalzal G H | 2006 | Otolaryngol Head Neck Surg2006，134，5： | 1 |
| 17 | The role of the NMDA synapse in general anesthesia显示文摘 | FLOHR H GLADE U MOTZKO D | 1998 | Toxicol Lett1998，，： | 1 |
| 18 | Activation of m-calpain(calpain II)by epidermal growth factor is limited by PKA phosphorylation of m-calpain显示文摘 | 11 Shiraha H Glading A Chou J | | 0，，： | 1 |
| 19 | A comparison of open and laparoscop ic app roaches to adrenalectomy in patients withphaeochromocytoma显示文摘 | Davies M J Mc Glade DP Banting SW | 2004 | Anaesth Intensive Care2004，32，2： | 1 |
| 20 | Nutrition and performance of racingthoroughbreds显示文摘 | GLADE M J | 1983 | Equine Veterinary Journal1983，15，1： | 1 |
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