Environmental Modelling & Software, Год журнала: 2024, Номер 183, С. 106231 - 106231
Опубликована: Окт. 11, 2024
Язык: Английский
CATENA, Год журнала: 2023, Номер 233, С. 107499 - 107499
Опубликована: Сен. 7, 2023
Язык: Английский
Процитировано
21
Scientific Data, Год журнала: 2025, Номер 12(1)
Опубликована: Фев. 5, 2025
Язык: Английский
Процитировано
1
Heliyon, Год журнала: 2023, Номер 9(7), С. e17972 - e17972
Опубликована: Июль 1, 2023
Landslide susceptibility mapping is a common practice for landslide assessment across the world. Like many other mountainous areas of world, Bangladesh facing frequent catastrophic landslides causing severe damage to economy and society. As result, several types research have been conducted on in Bangladesh. In current research, systematic review existing literature related assess its contemporary trend with global research. The publications analyzed this were extracted from website comprising by manual search. aspects considered are year publication, journal where published, location/size study area, inventory data type, assessment/mapping method, thematic variables used, DEM characteristics, accuracy methods acquired models. Chi-square test was correlation measured relation between selected features map but no significant relationship found. studies concentrated into three administrative districts Chattogram, Rangamati Cox's Bazar mainly covering city centre. publication rate increasing not following trend. Though various models used compared, application machine deep learning algorithms very limited evidence Physically-based Most cases, prepared conducting field survey, size small. will help future practitioner area.
Язык: Английский
Процитировано
14
Landslides, Год журнала: 2024, Номер unknown
Опубликована: Окт. 25, 2024
Abstract Landslide susceptibility maps serve as the basis for hazard and risk assessment, well risk-informed land use planning at various spatial scales. Researchers create these aiming to fulfil a variety of purposes, including infrastructure restrictive zoning. These applications require accurate specific information decisions based on have potential cost lives cause damage. The usability depends whether they provide required their accuracy be utilized intended purpose. Therefore, assessing predictive landslide is paramount importance. Typically, evaluated using same inventory that was used map, which does not actually test ability in future situations. In this study, we briefly reviewed purposes map creation literature stakeholder interviews assessed three posterior manner. We generated multi-temporal event after dates maps. devised method evaluate classified by making Unique Conditions Units (UCUs) compare posteriorly predicted classes new occurrences. Interviews with stakeholders revealed disconnection between aims set forth producers needs end users. Our assessment shows overall predictions plausible results; however, interpretations different cases make them less likely used. When comparing UCUs, densities overlap classes, indicating low performance Direct comparison all agreement pinpoints uncertainties data methods This study highlights need purpose-oriented mapping capabilities respective purposes.
Язык: Английский
Процитировано
3
Reviews of Geophysics, Год журнала: 2025, Номер 63(1)
Опубликована: Фев. 21, 2025
Abstract Assessing landslide risk is a fundamental requirement to plan suitable prevention actions. To date, most studies focus on individual slopes or catchments. Whereas regional, national continental scale assessments are hardly available because of methodological and/or data limitations. In this contribution, we present an overview all requirements and limitations in across spatial scales, by means hybrid form that combines elements original research with the comprehensive characteristics review study. The critically analyses each component analysis providing detailed explanation their state‐of‐the‐art, dedicated sections susceptibility, hazard, exposure, vulnerability. put theoretical framework test, also dive into case study, expressed at scale. Specifically, take main European mountain ranges provide reader textbook example assessment for such large territory. doing so, account issues associated cross‐national differences mapping. As result, identify landslide‐prone landscape explore possible economic consequences (human settlements agricultural areas). We analyze population during daytime nighttime. Moreover, modern view problem explored how outcomes should be delivered master planners geoscientific personnel alike. convert our output interactive Web Application ( https://pan‐european‐landslide‐risk.github.io/ ) include notions scientific communication both public as well technical audience.
Язык: Английский
Процитировано
0
Revue internationale de géomatique, Год журнала: 2025, Номер 34(1), С. 121 - 141
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Environmental Modelling & Software, Год журнала: 2025, Номер unknown, С. 106512 - 106512
Опубликована: Май 1, 2025
Язык: Английский
Процитировано
0
EarthArXiv (California Digital Library), Год журнала: 2023, Номер unknown
Опубликована: Авг. 3, 2023
The initial inception of the landslide susceptibility concept defined it as a static property landscape, explaining proneness certain locations to generate slope failures. Since spread data-driven probabilistic solutions though, original definition has been challenged incorporate dynamic elements that would lead occurrence probability change both in space and time. This is starting point this work, which combines traditional strengths framework together with typical early warning systems. Specifically, we model occurrences norther sector Vietnam, using multi-temporal inventory recently released by NASA. A set (terrain) (cumulated rainfall) covariates are selected explain presence/absence distribution via Bayesian version binomial Generalized Additive Models (GAM). Thanks large spatiotemporal domain under consideration, include suite cross-validation routines, testing prediction through random sampling, well stratified spatial temporal sampling. We even extend test towards regions far away from study site, be used external validation datasets. overall performance appears quite high, Area Under Curve (AUC) values range excellent results, very few localized exceptions. structure may serve basis for new generation However, use Climate Hazards group Infrared Precipitation Stations (CHIRPS) rainfall component limits ability terms future prediction. Therefore, envision subsequent development take direction move unified forecast. Ultimately, proof-of-concept, have also implemented potential system Google Earth Engine.
Язык: Английский
Процитировано
8
International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2023, Номер 125, С. 103593 - 103593
Опубликована: Дек. 1, 2023
The initial inception of the landslide susceptibility concept defined it as a static property landscape, explaining proneness certain locations to generate slope failures. Since spread data-driven probabilistic solutions though, original definition has been challenged incorporate dynamic elements that would lead occurrence probability change both in space and time. This is starting point this work, which combines traditional strengths framework together with typical early warning systems. Specifically, we model occurrences norther sector Vietnam, using multi-temporal inventory recently released by NASA. A set (terrain) (cumulated rainfall) covariates are selected explain presence/absence distribution via Bayesian version binomial Generalized Additive Models (GAM). Thanks large spatiotemporal domain under consideration, include suite cross-validation routines, testing prediction through random sampling, well stratified spatial temporal sampling. We even extend test towards regions far away from study site, be used external validation datasets. overall performance appears quite high, Area Under Curve (AUC) values range excellent results, very few localized exceptions. structure may serve basis for new generation However, use Climate Hazards group Infrared Precipitation Stations (CHIRPS) rainfall component limits ability terms future prediction. Therefore, envision subsequent development take direction move unified forecast. Ultimately, proof-of-concept, have also implemented potential system Google Earth Engine.
Язык: Английский
Процитировано
8
Sustainability, Год журнала: 2024, Номер 16(10), С. 4044 - 4044
Опубликована: Май 12, 2024
Deriving rainfall thresholds is one of the most convenient and effective empirical methods for formulating landslide warnings. The previous threshold models only considered values areas with data. This study focuses on obtaining a each single via geostatistical interpolation historical landslide–rainfall We collect occurrence times locations landslides, along hourly data, Dazhou. integrate short-term long-term data preceding occurrences, categorizing them into four groups analysis: 1 h–7 days (H1–7), 12 (H12–D7), 24 (H24–D7), 72 (H72–D7). Then, we construct distribution map based 2014–2020 by means Kriging interpolation. process involves applying different splitting coefficients to distinguish landslides triggered versus rainfall. Subsequently, validate these using dataset 2021. results show that best H1–D7, H12–D7, H24–D7, H72–D7 are around 0.19, 0.52, 0.55, 0.80, respectively. accuracy predictions increases duration rainfall, from 48% H1–D7 67% H72–D7. performance indicates their potential practical application in sustainable development geo-hazard prevention. Finally, discuss reliability applicability this method considering various factors, including influence techniques, quality, weather forecast, human activities.
Язык: Английский
Процитировано
3