Predictive Model of Rainfall-Induced Landslides in High-Density Urban Areas of the South Primorsky Region (Russia)

Stepnova, Yu. A.; Stepnov, A. A.; Konovalov, A. V.; Gensiorovskiy, Yu. V.; Лобкина, В. А.; Muzychenko, L. E.; Muzychenko, A. A.; Orekhov, A. A.

doi:10.1007/s00024-021-02822-y

Cited by 9 publications

(4 citation statements)

References 26 publications

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“…Logit analysis is widely used for binary data classification in geoscience (e.g., Zhu et al 2017;Stepnova et al 2021). In the binary logistic model, the logistic response function is determined by a binary dependent variable (Harrell, 2015), where the two possible outcomes are labeled as 0 and 1.…”

Section: Methodsmentioning

confidence: 99%

A Logit-Based Binary Classifier of Tsunamigenic Earthquakes for the Northern Pacific Ocean

Konovalov

Samsonov

Stepnov

2022

Preprint

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In this study, logistic regression was used as a tool for deriving the binary classifier of tsunamigenic and nontsunamigenic earthquakes in the near-source zone. Earthquake source depth and moment magnitude were considered as predictors. The training dataset consisted of 767 M6.0+ submarine earthquakes, including 80 tsunamigenic and 687 nontsunamigenic events that occurred in the northern part of the Pacific Ocean from 1960 to 2020. The target area has already experienced significant and catastrophic tsunamis. The current analysis clearly showed that the data-driven logit model had a significantly lower false discovery rate relative to the threshold magnitude criteria that are widely used by tsunami warning agencies. At the same time, the balanced accuracy was about 71%, which suggests optimism for accurate tsunami forecasting based on the rapid interpretation of earthquake source parameters.

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Section: Methodsmentioning

confidence: 99%

A Logit-Based Binary Classifier of Tsunamigenic Earthquakes for the Northern Pacific Ocean

Konovalov

Samsonov

Stepnov

2022

Preprint

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“…Формирования оползня можно было избежать, сделав предварительную оценку увлажненности грунтов до начала работ. В [15] Проверка модели сделана через определение истинно положительных и истинно отрицательных результатов, а также определение ложных срабатываний и ложноотрицательных, ложноположительных результатов (подробнее в [15]). Метрики оценки эффективности модели представлены в (табл.…”

Section: результатыunclassified

Landslide Activation During the Development of Mountainous Areas

Lobkina,

Gensiorovsky

2024

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The development of mountainous areas for recreation increases the level of risk of activation of dangerous exogenous processes, primarily landslides and mudflows. Water accumulation in the ground in the regions prone to landslides and mudflows is one of the important factors determining the intensity of manifestation of these processes and significantly influencing their characteristics. The paper considers the case of landslide activation at the Gornyi Vozduh ski resort in December 2021. A predicive model is presented for rainfall-induced landslides on saturated soil slopes, whose parameters were adjusted to the conditions of southern Sakhalin. Data on landslides and mudflows within a 30 km radius from the Yuzhno-Sakhalinsk meteorological station were collected to calibrate the model. The predictive model uses data on daily precipitation, pre-event precipitation, and cumulative precipitation. All these data are publicly available allowing model calibration for the conditions of any nearest meteorological station. The daily precipitation threshold for likely landslide and mudflow initiation in the territory under consideration was determined to be 51.4 mm.

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“…The most pronounced anthropogenic influence has been evident in the reduction of forested areas, the destruction of natural habitats [4,5], mineral extraction activities [6,7], pollution of rivers and water bodies [8,9], urbanization expansion [10,11] (often unregulated in developing nations), and air pollution [12,13]. Concurrently, this trend has created additional conditions conducive to erosion [14,15], floods [16,17], landslides and avalanches [18,19], wildfires [20,21], and climate change [22,23] as a result of anthropogenic activities. These activities, in many instances, fail to consider the natural physical-geographical and historical nuances of regions and, regrettably, are frequently conducted without proper oversight.…”

Section: Introductionmentioning

confidence: 99%

Fatala River Basin (Republic of Guinea, Africa): Analysis of Current State, Air Pollution, and Anthropogenic Impact Using Geoinformatics Methods and Remote Sensing Data

Tabunschik,

Gorbunov,

Bratanov

et al. 2023

Sustainability

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This study conducts an in-depth analysis of anthropogenic transformation and air pollution within the confines of the Fatala River Basin situated in the Republic of Guinea, Africa. The foundation of this investigation relies upon interdisciplinary geoinformatics methodologies and data acquired through remote sensing, specifically drawing from Sentinel-5P and Sentinel-2 satellite datasets. The primary objectives encompass scrutinizing the extant ecological conditions characterizing the Fatala River Basin and assessing the anthropogenic influences within its geographic expanse. The utilization of remote sensing data, as facilitated by the Sentinel-5P satellite, emerges as a potent instrument for meticulously monitoring environmental transformations. A comprehensive analysis of the designated area, conducted through remote sensing methodologies, is employed to ascertain the concentrations of various atmospheric constituents, including nitrogen dioxide, sulfur dioxide, formaldehyde, methane, ozone, and carbon monoxide. The findings gleaned from this inquiry reveal that, notwithstanding the dynamic growth of the extractive industry centered around the world’s preeminent bauxite province, the Fouta Djallon–Mandingo, the anthropogenic transformation of the Fatala River Basin exerts a comparatively minor influence on air quality. Statistical assessments, including correlation analysis, conducted between computed parameters delineating anthropogenic alterations within the Fatala River Basin, and a comprehensive atmospheric pollution index elucidate a lack of a significant nexus. It has been determined that air pollution within the Fatala River Basin is notably influenced by topographical features and the transport of contaminants from adjacent river basins. Consequently, this article makes a substantial contribution to our comprehension of the contemporary ecological state of the Fatala River Basin in the Republic of Guinea. It also holds significant importance in elucidating the ecological challenges specific to the researched region.

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Predictive Model of Rainfall-Induced Landslides in High-Density Urban Areas of the South Primorsky Region (Russia)

Cited by 9 publications

References 26 publications

A Logit-Based Binary Classifier of Tsunamigenic Earthquakes for the Northern Pacific Ocean

A Logit-Based Binary Classifier of Tsunamigenic Earthquakes for the Northern Pacific Ocean

Landslide Activation During the Development of Mountainous Areas

Fatala River Basin (Republic of Guinea, Africa): Analysis of Current State, Air Pollution, and Anthropogenic Impact Using Geoinformatics Methods and Remote Sensing Data

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