Evaluating the use of the landslide database in spatial planning in mountain communes (the Polish Carpathians)

Bucała-Hrabia, Anna; Kijowska-Strugała, Małgorzata; Śleszyński, Przemysław; Rączkowska, Zofia; Izdebski, Waldemar; Malinowski, Zbigniew

doi:10.1016/j.landusepol.2021.105842

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…The literature states that more developed SDS supplements the delivery of the sediment material to the river channel increases [3,56,57]. Considering the fact that the West Carpathians region is relatively densely populated (The Polish part of Carpathians includes 139 people•km −2 and in rural areas 100 people•km −2 ) [58] and the agriculture area is strongly fragmented, roads are one of the most important sources of sediment transported in the channel [3,7,56]. According to Froehlich and Walling [3], in the Carpathians, in high-medium mountains (Beskid S ądecki), unpaved roads provide 70%-80% of suspended sediment transported in the stream channel and this may cause road deepening around 6.6 mm per year.…”

Section: Discussionmentioning

confidence: 99%

Surface Drainage Systems Operating during Heavy Rainfall—A Comparative Analysis between Two Small Flysch Catchments Located in Different Physiographic Regions of the Western Carpathians (Poland)

Kroczak

Bryndal

Żychowski

2022

Water

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In this study, the river system and the surface drainage system (SDS) operating during heavy rainfall in two Carpathian catchments located in foothills and medium-high mountain areas were compared. The results revealed that regardless of the differences in the river systems and physiographical parameters of the catchments, the SDS operating during heavy rainfall becomes similar. This similarity is reflected in the density of the SDS (11.5–12.2 km·km−2) and the structure of the SDS, confirmed by Hortonian-type analysis. This similarity in the SDS was discussed in the context of the geomorphological transformation of the hillslopes and the hydrological response of a catchment to heavy rainfall.

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Section: Discussionmentioning

confidence: 99%

Surface Drainage Systems Operating during Heavy Rainfall—A Comparative Analysis between Two Small Flysch Catchments Located in Different Physiographic Regions of the Western Carpathians (Poland)

Kroczak

Bryndal

Żychowski

2022

Water

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“…In areas prone to landslide hazard (as well as in areas prone to flood hazard, which are not the object of this study), in Sardinia the PAI maps serve as a spatial reference for the PAI regulations, which restrict land uses and prevent land transformations depending on the magnitude of the hazard. In this way, the PAI provides a legally binding framework for municipal masterplans, whose zoning choices must comply with the PAI regulations, contrary to what has been reported in other countries [102], where new development in landslide hazard areas is not prohibited [103]. Hence, this higher-level regional planning tool contributes to limiting land-taking processes in fragile areas, while also providing relevant spatial information to planners in charge of drafting land use plans and appraising them through the SEA.…”

Section: Policy Implicationsmentioning

confidence: 92%

Land Take and Landslide Hazard: Spatial Assessment and Policy Implications from a Study Concerning Sardinia

Isola

Lai

Leone

et al. 2023

Land

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Land take and soil sealing imply land cover transitions that may possibly result in decreased capacity to resist landslides; hence, this study focuses on the relations between land-taking processes and landslide hazard by addressing the following research question: “To what extent do land-taking processes increase landslide hazard?” The impact of land take is assessed through a regression model which relates the level of landslide hazard to a set of land cover variables which include artificialized land; that is, land taken up through urbanization processes, and a set of covariates that represent land cover types grouped in accordance with the LEAC (land and ecosystem accounting) classification. This methodological approach is implemented into the spatial context of Sardinia, an insular Italian region, and shows that not only the amount of taken up artificialized land, but also other types of land covers, are likely to increase the magnitude of landslide hazard. A set of implications concerning planning policies related to land cover and land cover transitions are discussed in the concluding section, where policy recommendations are identified in order to mitigate the impacts of land cover transitions on landslide hazards.

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“…When applied to global landslide risk monitoring and disaster prevention, it can serve as a foundation for formulating appropriate natural disaster management policies. This is particularly crucial in low-to middle-income countries with high population density, where landslides in densely populated mountainous areas can lead to economic losses, casualties, and even direct and indirect costs for urban-scale constructions or infrastructure [50][51][52][53].…”

Section: Region B Serves As An Additional Study Area To Independently...mentioning

confidence: 99%

A Comparative Study of Landslide Susceptibility Mapping Using Bagging PU Learning in Class-Prior Probability Shift Datasets

Zhao,

Ma,

Dong

et al. 2023

Remote Sensing

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Landslide susceptibility mapping is typically based on binary prediction probabilities. However, non-landslide samples in modeling datasets are often unlabeled data, and the phenomenon of class-priori shift, that is, the proportion of landslide samples frequently deviates from real-world scenarios and is spatially heterogeneous. By comparing the classification performance and predicted probability distributions across multiple unbalanced datasets with known and unknown sample proportions, this study assesses the landslide susceptibility model’s generalization ability in the context of class-prior shifts. The study investigates the potential of Bagging PU Learning, a semi-supervised learning approach, in improving the generalization performance of landslide susceptibility models and proposes the Bagging PU-GDBT algorithm. Our findings highlight the effectiveness of Bagging PU Learning in enhancing the recall of landslides and the generalization capabilities of models on unbalanced datasets. This method reduces prediction uncertainties, especially in high and very high susceptibility zones. Furthermore, results emphasize the superiority of models trained on balanced datasets with 1:1 sample ratio for landslide susceptibility mapping over those trained on unbalanced datasets.

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Evaluating the use of the landslide database in spatial planning in mountain communes (the Polish Carpathians)

Cited by 10 publications

References 20 publications

Surface Drainage Systems Operating during Heavy Rainfall—A Comparative Analysis between Two Small Flysch Catchments Located in Different Physiographic Regions of the Western Carpathians (Poland)

Surface Drainage Systems Operating during Heavy Rainfall—A Comparative Analysis between Two Small Flysch Catchments Located in Different Physiographic Regions of the Western Carpathians (Poland)

Land Take and Landslide Hazard: Spatial Assessment and Policy Implications from a Study Concerning Sardinia

A Comparative Study of Landslide Susceptibility Mapping Using Bagging PU Learning in Class-Prior Probability Shift Datasets

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