scholarly journals Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: application to the river Beiro basin (Spain)

2012 ◽  
Vol 12 (2) ◽  
pp. 327-340 ◽  
Author(s):  
D. Costanzo ◽  
E. Rotigliano ◽  
C. Irigaray ◽  
J. D. Jiménez-Perálvarez ◽  
J. Chacón
Keyword(s):  
Landslide Susceptibility ◽  
Large Scale ◽  
Goodness Of Fit ◽  
Predictive Performance ◽  
Controlling Factors ◽  
Slope Instability ◽  
Susceptibility Maps ◽  
Gis Matrix Method ◽  
Determining Factors ◽  
The One

Abstract. A procedure to select the controlling factors connected to the slope instability has been defined. It allowed us to assess the landslide susceptibility in the Rio Beiro basin (about 10 km2) over the northeastern area of the city of Granada (Spain). Field and remote (Google EarthTM) recognition techniques allowed us to generate a landslide inventory consisting in 127 phenomena. To discriminate between stable and unstable conditions, a diagnostic area had been chosen as the one limited to the crown and the toe of the scarp of the landslide. 15 controlling or determining factors have been defined considering topographic, geologic, geomorphologic and pedologic available data. Univariate tests, using both association coefficients and validation results of single-variable susceptibility models, allowed us to select the best predictors, which were combined for the unique conditions analysis. For each of the five recognised landslide typologies, susceptibility maps for the best models were prepared. In order to verify both the goodness of fit and the prediction skill of the susceptibility models, two different validation procedures were applied and compared. Both procedures are based on a random partition of the landslide archive for producing a test and a training subset. The first method is based on the analysis of the shape of the success and prediction rate curves, which are quantitatively analysed exploiting two morphometric indexes. The second method is based on the analysis of the degree of fit, by considering the relative error between the intersected target landslides by each of the different susceptibility classes in which the study area was partitioned. Both the validation procedures confirmed a very good predictive performance of the susceptibility models and of the actual procedure followed to select the controlling factors.

scholarly journals Evaluation of the landslide susceptibility map obtained by a GIS matrix method: a case of Al Hoceima city (northern Morocco)

2021 ◽  
Vol 119 ◽  
pp. 04002
Author(s):  
Taoufik Byou
Keyword(s):  
Landslide Susceptibility ◽  
Matrix Method ◽  
Characteristic Curve ◽  
Predictive Ability ◽  
Susceptibility Map ◽  
Susceptibility Maps ◽  
Gis Matrix Method ◽  
The Matrix ◽  
The One ◽  
Al Hoceima

This work presents a method for preparing landslide susceptibility maps based on an analysis between past movements and predisposing factors. The proposed methodology for determining susceptibility is an adaptation of the matrix method in the territory of the city of Al Hoceima (Northern Morocco). The data needed to evaluate vulnerability has based on the landslide inventory and the available cartographic documents. These data were prepared and integrated into a GIS. This phase of the data preparation has followed by assessment and susceptibility mapping. The obtained map was validated and compared with an independent landslide dataset than the one used to develop the model. The results of the ROC (receiver operating characteristic) curve demonstrate the good predictive ability (AUC = 0.94). We can deduce that the map correlates well with the existing terrain conditions. The successfully validated prediction will enable decision-makers to offer handy information for infrastructure construction and urban planning in the future or other areas with similar situations

scholarly journals A step beyond landslide susceptibility maps: a simple method to investigate and explain the different outcomes obtained by different approaches

Landslides ◽  
2019 ◽  
Vol 17 (3) ◽  
pp. 627-640 ◽  
Author(s):  
Ting Xiao ◽  
Samuele Segoni ◽  
Lixia Chen ◽  
Kunlong Yin ◽  
Nicola Casagli
Keyword(s):  
Landslide Susceptibility ◽  
Predictive Performance ◽  
Test Site ◽  
Morphological Features ◽  
Landslide Risk ◽  
Simple Method ◽  
Explanatory Variables ◽  
Susceptibility Maps ◽  
Area Under Roc Curve ◽  
Low Altitude

AbstractLandslide susceptibility assessment is vital for landslide risk management and urban planning, and the scientific community is continuously proposing new approaches to map landslide susceptibility, especially by hybridizing state-of-the-art models and by proposing new ones. A common practice in landslide susceptibility studies is to compare (two or more) different models in terms of AUC (area under ROC curve) to assess which one has the best predictive performance. The objective of this paper is to show that the classical scheme of comparison between susceptibility models can be expanded and enriched with substantial geomorphological insights by focusing the comparison on the mapped susceptibility values and investigating the geomorphological reasons of the differences encountered. To this aim, we used four susceptibility maps of the Wanzhou County (China) obtained with four different classification methods (namely, random forest, index of entropy, frequency ratio, and certainty factor). A quantitative comparison of the susceptibility values was carried out on a pixel-by-pixel basis, to reveal systematic spatial patterns in the differences among susceptibility maps; then, those patterns were put in relation with all the explanatory variables used in the susceptibility assessments. The lithological and morphological features of the study area that are typically associated to underestimations and overestimations of susceptibility were identified. The results shed a new light on the susceptibility models, identifying systematic errors that could be probably associated either to shortcomings of the models or to distinctive morphological features of the test site, such as nearly flat low altitude areas near the main rivers, and some lithological units.

scholarly journals Retrospective evaluation of landslide susceptibility maps and review of validation practice

2021 ◽  
Vol 80 (15) ◽  
Author(s):  
Paul Fleuchaus ◽  
Philipp Blum ◽  
Martina Wilde ◽  
Birgit Terhorst ◽  
Christoph Butscher
Keyword(s):  
Landslide Susceptibility ◽  
Predictive Accuracy ◽  
Predictive Performance ◽  
Susceptibility Map ◽  
Retrospective Evaluation ◽  
Widespread Application ◽  
Evaluation Approach ◽  
Susceptibility Maps ◽  
Landslide Event ◽  
Landslide Susceptibility Maps

AbstractDespite the widespread application of landslide susceptibility analyses, there is hardly any information about whether or not the occurrence of recent landslide events was correctly predicted by the relevant susceptibility maps. Hence, the objective of this study is to evaluate four landslide susceptibility maps retrospectively in a landslide-prone area of the Swabian Alb (Germany). The predictive performance of each susceptibility map is evaluated based on a landslide event triggered by heavy rainfalls in the year 2013. The retrospective evaluation revealed significant variations in the predictive accuracy of the analyzed studies. Both completely erroneous as well as very precise predictions were observed. These differences are less attributed to the applied statistical method and more to the quality and comprehensiveness of the used input data. Furthermore, a literature review of 50 peer-reviewed articles showed that most landslide susceptibility analyses achieve very high validation scores. 73% of the analyzed studies achieved an area under curve (AUC) value of at least 80%. These high validation scores, however, do not reflect the high uncertainty in statistical susceptibility analysis. Thus, the quality assessment of landslide susceptibility maps should not only comprise an index-based, quantitative validation, but also an additional qualitative plausibility check considering local geomorphological characteristics and local landslide mechanisms. Finally, the proposed retrospective evaluation approach cannot only help to assess the quality of susceptibility maps and demonstrate the reliability of such statistical methods, but also identify issues that will enable the susceptibility maps to be improved in the future.

The necessity to consider the landslide data origin in statistically-based spatial predictive modelling – A landslide intervention index for South Tyrol (Italy)

2020 ◽  
Author(s):  
Stefan Steger ◽  
Volkmar Mair ◽  
Christian Kofler ◽  
Stefan Schneiderbauer ◽  
Marc Zebisch
Keyword(s):  
Statistical Models ◽  
Landslide Susceptibility ◽  
Intervention Strategy ◽  
Predictive Performance ◽  
Mixed Effects ◽  
Slope Instability ◽  
Landslide Inventory ◽  
Background Information ◽  
Explanatory Variables ◽  
Landslide Data

<p>Most statistically-based landslide susceptibility maps are supposed to portray the relative likelihood of an area to be affected by future landslides. Literature indicates that vital modelling decisions, such as the selection of explanatory variables, are frequently based on quantitative criteria (e.g. predictive performance). The results obtained by apparently well-performing statistical models are also used to infer the causes of slope instability and to identify landslide “safe” terrain. It seems that comparably few studies pay particular attention to background information associated with the available landslide data. This research hypothesizes that inappropriate modelling decisions and wrong conclusions are likely to follow whenever the origin of the underlying landslide data is ignored. The aims were to (i) analyze the South Tyrolean landslide inventory in the context of its origin in order to (ii) highlight potential pitfalls of performance driven procedures and to (iii) develop a predictive model that takes landslide background information into account. The available landslide data (1928 slide-type movements) of the province of South Tyrol (~7400 km²) consists of positionally accurate points that depict the scarp location of events that induced interventions by e.g. the road service or the geological office. An initial exploratory statistical analysis revealed general relationships between landslide presence/absence data and frequently used explanatory variables. Subsequent modelling was based on a Generalized Additive Mixed Effects Model that allowed accounting for (non-linear) fixed effects and additional “nuisance” variables (random intercepts). The evaluation of the models (diverse variable combinations) focused on modelled relationships, variable importance, spatial and non-spatial predictive performance and the final prediction surfaces. The results highlighted that the best performing models did not reflect the “actual” landslide susceptibility situation. A critical interpretation led to the conclusion that the models simultaneously reflected both, effects likely related to slope instability (e.g. low likelihood of flat and very steep terrain) and effects rather associated with the provincial landslide intervention strategy (e.g. few interventions at high altitudes, increasing number of interventions with decreasing distance to infrastructure). Attempts to separate the nuisance related to “intervention effects” from the actual landslide effects using mixed effects modelling proved to be challenging, also due to omnipresent spatial interrelations among the explanatory variables and the fact that some variables concurrently represent effects related to landslide predisposition and effects associated with the intervention strategy (e.g. altitude). We developed a well-performing predictive landslide intervention index that is in line with the actual data origin and allows identifying areas where future interventions are more or less likely to take place. The efficiency of past interventions (e.g. stabilization of slopes) was demonstrated during recent storm events, because previously stabilized slopes were not affected by new landslides. This also showed that the correct interpretation of the final map requires a simultaneous visualization of both, the spatially predicted index (from low to high) and the available landslide inventory (low likelihood due to past interventions). The results confirm that wrong conclusions can be drawn from excellently performing statistical models whenever qualitative background information is disregarded.</p>

scholarly journals Validation of landslide susceptibility maps (Case study: Urban area of the municipality of Banja Luka - B&H)

2017 ◽  
Vol 97 (1) ◽  
pp. 19-34 ◽  
Author(s):  
Novica Lovric ◽  
Radislav Tosic
Keyword(s):  
Urban Area ◽  
Landslide Susceptibility ◽  
Matrix Method ◽  
Statistical Index ◽  
Index Method ◽  
Good Opportunity ◽  
Susceptibility Maps ◽  
Gis Matrix Method ◽  
Banja Luka ◽  
Landslide Susceptibility Maps

Landslides represent a serious geo-hazard in many areas of the world. They are one of the most damaging and most significant geo-hazards in Bosnia and Herzegovina. In the previous research, three GIS-based methodologies (Index based method, Statistical index method, and Landslide susceptibility analysis), have been used to assess the landslide susceptibility in urban area of the Municipality of Banja Luka. Validation technique is performed by comparing existing landslide data from 2012 with obtained landslide susceptibility maps. In this research, the landslide susceptibility maps were supplemented by landslide susceptibility map which is prepared using a GIS Matrix method. The area and percentage distribution of the susceptibility classes in the study area were determined as a result of the four different techniques. The Statistical index method has provided the most satisfying results. As a consequence of heavy rains during the period from May to August 2014, 126 landslides occurred in the study area, and they offer a good opportunity to validate obtained landslide susceptibility maps of the study area with landslides that occurred in different periods of time. Validation was performed by using a ?degree of fit? method. The values of the degree of fit in high and very high category in all used methods are over 80%, except for GIS matrix method, where the percentage is 60%. The validation of obtained landslide susceptibility maps suggests that the applications of all the used techniques provide a good basis for creation landslide susceptibility maps, but the best results are given by using a Statistical index method.

First grammar books in the Habsburg Monarchy: individual initiative and regulatory interference by the state (1760s–1770s)

2020 ◽  
Vol 2019 (2 (11)) ◽  
pp. 137-157
Author(s):  
Olga V. Khavanova ◽  
Keyword(s):  
Eighteenth Century ◽  
State Policy ◽  
Large Scale ◽  
Language Use ◽  
Linguistic Diversity ◽  
Mother Tongue ◽  
German Language ◽  
Habsburg Monarchy ◽  
Private Initiative ◽  
The One

The second half of the eighteenth century in the lands under the sceptre of the House of Austria was a period of development of a language policy addressing the ethno-linguistic diversity of the monarchy’s subjects. On the one hand, the sphere of use of the German language was becoming wider, embracing more and more segments of administration, education, and culture. On the other hand, the authorities were perfectly aware of the fact that communication in the languages and vernaculars of the nationalities living in the Austrian Monarchy was one of the principal instruments of spreading decrees and announcements from the central and local authorities to the less-educated strata of the population. Consequently, a large-scale reform of primary education was launched, aimed at making the whole population literate, regardless of social status, nationality (mother tongue), or confession. In parallel with the centrally coordinated state policy of education and language-use, subjects-both language experts and amateur polyglots-joined the process of writing grammar books, which were intended to ease communication between the different nationalities of the Habsburg lands. This article considers some examples of such editions with primary attention given to the correlation between private initiative and governmental policies, mechanisms of verifying the textbooks to be published, their content, and their potential readers. This paper demonstrates that for grammar-book authors, it was very important to be integrated into the patronage networks at the court and in administrative bodies and stresses that the Vienna court controlled the process of selection and financing of grammar books to be published depending on their quality and ability to satisfy the aims and goals of state policy.

The Green New Deal

2019 ◽  
Author(s):  
Robert C. Hockett
Keyword(s):  
New Deal ◽  
Large Scale ◽  
Public Investment ◽  
Climate Science ◽  
Time Frame ◽  
White Paper ◽  
Good News ◽  
Carbon Neutrality ◽  
The One ◽  
In Virtue Of

This white paper lays out the guiding vision behind the Green New Deal Resolution proposed to the U.S. Congress by Representative Alexandria Ocasio-Cortez and Senator Bill Markey in February of 2019. It explains the senses in which the Green New Deal is 'green' on the one hand, and a new 'New Deal' on the other hand. It also 'makes the case' for a shamelessly ambitious, not a low-ball or slow-walked, Green New Deal agenda. At the core of the paper's argument lies the observation that only a true national mobilization on the scale of those associated with the original New Deal and the Second World War will be up to the task of comprehensively revitalizing the nation's economy, justly growing our middle class, and expeditiously achieving carbon-neutrality within the twelve-year time-frame that climate science tells us we have before reaching an environmental 'tipping point.' But this is actually good news, the paper argues. For, paradoxically, an ambitious Green New Deal also will be the most 'affordable' Green New Deal, in virtue of the enormous productivity, widespread prosperity, and attendant public revenue benefits that large-scale public investment will bring. In effect, the Green New Deal will amount to that very transformative stimulus which the nation has awaited since the crash of 2008 and its debt-deflationary sequel.

DEVELOPMENT OF LANDSLIDE SUSCEPTIBILITY MAPS IN COLORADO

2016 ◽  
Author(s):  
Kassandra Lindsey ◽  
◽  
Matthew L. Morgan ◽  
Karen A. Berry
Keyword(s):  
Landslide Susceptibility ◽  
Susceptibility Maps ◽  
Landslide Susceptibility Maps
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