A review of recent studies on landslide hazard in Latin America

Carrera, Alejandro César Valdés; Mendoza, Manuel E.; Carlón-Allende, Teodoro; Macías, José Luis

doi:10.1080/02723646.2021.1978372

Cited by 14 publications

(8 citation statements)

References 97 publications

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“…We found that 73% of the articles were published in international journals in the English language. According to Carrera et al [55], in Latin America 48.8% of all publications were in English, followed by Spanish (43.1%). These numbers show that Brazilian researchers tend to publish in English rather than in Portuguese (the native language).…”

Section: Year Of Publication and Where It Was Publishedmentioning

confidence: 98%

“…According to Reichenbach et al [54] there has been an increasing global trend of new publications on the susceptibility analysis of landslides starting in the year 2000. In Latin America, the number of studies on landslide hazards has been increasing since 2011 [55]. Brazil is following this regional and global trend (Figure 5).…”

Section: Year Of Publication and Where It Was Publishedmentioning

confidence: 99%

“…These numbers show that Brazilian researchers tend to publish in English rather than in Portuguese (the native language). Natural Hazards is the journal with the highest number of publications about susceptibility assessments in Brazil (≈27%), and it is among the five most common journals with publications related to landslides in Latin America [55]. According to Reichenbach et al [54], Natural Hazards is also one of the journals with the highest number of publications about landslide assessments worldwide.…”

Section: Year Of Publication and Where It Was Publishedmentioning

confidence: 99%

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Landslide Susceptibility Mapping in Brazil: A Review

2021

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Landslide susceptibility studies are a common type of landslide assessment. Landslides are one of the most frequent hazards in Brazil, resulting in significant economic and social losses (e.g., deaths, injuries, and property destruction). This paper presents a literature review of susceptibility mapping studies in Brazil and analyzes the methods and input data commonly used. The publications used in this analysis were extracted from the Web of Science platform. We considered the following aspects: location of study areas, year and where the study was published, methods, thematic variables, source of the landslide inventory, and validation methods. The susceptibility studies are concentrated in Brazil’s south and southeast region, with the number of publications increasing since 2015. The methods commonly used are slope stability and statistical models. Validation was performed based on receiver operating characteristic (ROC) curves and area under the curve (AUC). Even though landslide inventories constitute the most critical input data for susceptibility mapping, the criteria used for the creation of landslide inventories are not evident in most cases. The included studies apply various validation techniques, but evaluations with potential users and information on the practical applicability of the results are largely missing.

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Section: Year Of Publication and Where It Was Publishedmentioning

confidence: 98%

Section: Year Of Publication and Where It Was Publishedmentioning

confidence: 99%

Section: Year Of Publication and Where It Was Publishedmentioning

confidence: 99%

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Landslide Susceptibility Mapping in Brazil: A Review

2021

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“…Landslide is a common and extremely hazardous natural phenomenon, that poses serious threats to human lives and cause huge economic losses (Clague et al, 2012;Alam, 2020;Valdés Carrera et al, 2021). After a landslide, it is essential to determine quickly and accurately the magnitude and distribution area of the landslides for subsequent rescue.…”

Section: Introductionmentioning

confidence: 99%

A novel Dynahead-Yolo neural network for the detection of landslides with variable proportions using remote sensing images

Han

FANG²,

Li³

et al. 2023

Front. Earth Sci.

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Efficient and automatic landslide detection solutions are beneficial for regional hazard mitigation. At present, scholars have carried out landslide detection based on deep learning. However, continuous improvement regarding the accuracy of landslide detection with better feature extraction of landslides remain an essential issue, especially small-proportion landslides in the remote sensing images are difficult to identify up to date. To address this issue, we propose a detection model, the so-called Dynahead-Yolo which is designed by combining unifying scale-aware, space-aware, and task-aware attention mechanisms into the YOLOv3 framework. The proposed method focuses on the detailed features of landslide images with variable proportions, improving the ability to decode landslides in complex background environments. We determine the most efficient cascade order of the three modules and compare previous detection networks based on randomly generated prediction sets from the three study areas. Compared with the traditional YOLOv3, the detection rate of Dynahead-Yolo in small-proportion landslides and complex background landslides is increased by 13.67% and 14.12%, respectively.

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“…T test, F test, Poisson regression, Percentile threshold, Monte Carlo method, ANOVA, standard deviation) and non-parametric tests (Mann-Kendall test, Neumann trend, Landslide density histograms, Goodness-of-t, Omit error, Deterministic models necessitate extensive databases on the causative factors (slope geometry, soil properties, and hydrological systems). These factors are applied as input measures to stability models that compute safety factors(Valdés Carrera et al 2021). The deterministic models are dynamic and indicate a sensible way to address quantitative safety factors and climate change scenarios with land use/ change patterns.…”

mentioning

confidence: 99%

Classifying knowledge on climate change induced landslides in retrospect and prospect: A state-of-the-art review

Sharma

Sajjad

Roshani

et al. 2023

Preprint

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The frequency and intensity of landslides have increased due to variability in precipitation and temperature across the globe. Assessment of landslide risk is essential for devising effective mitigation and making societies resilient. Through an in-depth literature review from 1996 to 2021, this study carried out descriptive, thematic, and mechanism analyses of the current literature to identify the gaps in the literature and suggest a way forward. Findings revealed a steady increase in the publication of landslide studies over the years. Most of the studies were conducted on a regional scale. Modeling, landslides, climate change, multi-hazards, and vulnerability figured as the prominent keywords in the reviewed articles. Slope, precipitation, land use/land cover, proximity to coastal areas, risk, and adaptation strategies were found as the dominant thematic variables. A large number of reviewed articles utilized statistical models. Uncertainty in landslide-climate modeling, lack of advanced and interactive models for predicting landslide susceptibility; and less attention to environmental and economic vulnerability were identified as the major research gaps. Effective early warning systems, timely forecasting for landslides and effective risk assessment are also scant in the existing literature. The current study proposed a comprehensive future framework for landslide risk assessment and implies timely and appropriate landslide mitigation based on climate scenario data, deterministic models, and policy beliefs. Strengthening preventive actions, preparedness as an early warning system, immediate response mechanism, landslide adaptation behavior, socio-economic vulnerability, and decision support systems are suggested for future research.

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A review of recent studies on landslide hazard in Latin America

Cited by 14 publications

References 97 publications

Landslide Susceptibility Mapping in Brazil: A Review

Landslide Susceptibility Mapping in Brazil: A Review

A novel Dynahead-Yolo neural network for the detection of landslides with variable proportions using remote sensing images

Classifying knowledge on climate change induced landslides in retrospect and prospect: A state-of-the-art review

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