scholarly journals Characteristics of landslide path dependency revealed through multiple resolution landslide inventories in the Nepal Himalaya

2021 ◽  
Author(s):  
Storm Roberts ◽  
Joshua Jones ◽  
Sarah Boulton
Keyword(s):  
Strong Evidence ◽  
Landslide Susceptibility ◽  
Random Distribution ◽  
Path Dependency ◽  
Study Region ◽  
Nepal Himalaya ◽  
Size Type ◽  
Path Dependent ◽  
Region Size ◽  
Degree Of Overlap

Recent research in Umbria, Italy, has shown that landslide susceptibility is controlled by a process called path-dependency, which describes how past landslides control the locations of future landslides. To date, landslide path-dependency has only been characterised in Italy. This raises the question of whether this process occurs in other geomorphic settings, and thus whether path-dependency should be more universally included in landslide susceptibility assessments. Therefore, the main aim of this paper is to investigate and quantify landslide path dependency in the Nepal Himalaya. This is achieved by applying several path dependent metrics to three monsoon-triggered landslide inventories for the central-eastern Nepal Himalaya. These inventories were developed at two different spatial and temporal resolutions. As such, we aim not just to quantify landslide path-dependency, but also assess whether path dependency characteristics are resolution-dependent. We find strong evidence that landslide path dependency is occurring in Nepal, with all three inventories having more overlap between past and new landslides than expected from a random distribution, and a tentative observation that the expected degree of overlap between landslides decreases with time. Finally, whilst path-dependency is observable across both of the investigated inventory resolutions, we find that the rates and magnitudes of the quantified path dependent metrics are sensitive to inventory length, study region size and the size/type of landslides mapped. Overall, our results corroborate the path-dependency observations from Italy, confirming that this process does occur in other geomorphic settings, and thus suggesting that path-dependency should be explicitly and universally considered in landslide susceptibility approaches.

scholarly journals Dynamic path-dependent landslide susceptibility modelling

2020 ◽  
Vol 20 (1) ◽  
pp. 271-285 ◽  
Author(s):  
Jalal Samia ◽  
Arnaud Temme ◽  
Arnold Bregt ◽  
Jakob Wallinga ◽  
Fausto Guzzetti ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Central Italy ◽  
Path Dependency ◽  
Space Time ◽  
Added Value ◽  
Susceptibility Maps ◽  
Multi Temporal ◽  
Susceptibility Model ◽  
Characteristic Spatial Scale ◽  
Path Dependent

Abstract. This contribution tests the added value of including landslide path dependency in statistically based landslide susceptibility modelling. A conventional pixel-based landslide susceptibility model was compared with a model that includes landslide path dependency and with a purely path-dependent landslide susceptibility model. To quantify path dependency among landslides, we used a space–time clustering (STC) measure derived from Ripley's space–time K function implemented on a point-based multi-temporal landslide inventory from the Collazzone study area in central Italy. We found that the values of STC obey an exponential-decay curve with a characteristic timescale of 17 years and characteristic spatial scale of 60 m. This exponential space–time decay of the effect of a previous landslide on landslide susceptibility was used as the landslide path-dependency component of susceptibility models. We found that the performance of the conventional landslide susceptibility model improved considerably when adding the effect of landslide path dependency. In fact, even the purely path-dependent landslide susceptibility model turned out to perform better than the conventional landslide susceptibility model. The conventional plus path-dependent and path-dependent landslide susceptibility model and their resulting maps are dynamic and change over time, unlike conventional landslide susceptibility maps.

scholarly journals Dynamic path dependent landslide susceptibility modelling

2019 ◽  
Author(s):  
Jalal Samia ◽  
Arnaud Temme ◽  
Arnold Bregt ◽  
Jakob Wallinga ◽  
Fausto Guzzetti ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Central Italy ◽  
Path Dependency ◽  
Space Time ◽  
Added Value ◽  
Characteristic Time Scale ◽  
Characteristic Space ◽  
Multi Temporal ◽  
Susceptibility Model ◽  
Path Dependent

Abstract. This contribution tests the added value of including landslide path dependency in statistically-based landslide susceptibility modelling. A conventional pixel-based landslide susceptibility model was compared with a model that includes landslide path dependency, and with a purely path dependent landslide susceptibility model. To quantify path dependency among landslides, we used a Space-Time Clustering (STC) measure derived from Ripley's space-time K function implemented on a point-based multi-temporal landslide inventory from the Collazzone study area in central Italy. We found that the values of STC obey an exponential decay curve with characteristic time scale of 17 years, and characteristic space scale of 60 meters. This exponential space-time decay of the effect of a previous landslide on landslide susceptibility was used as the landslide path dependency component of susceptibility models. We found that the performance of the conventional landslide susceptibility model improved considerably when adding the effect of landslide path dependency. In fact, even the purely path dependent landslide susceptibility model turned out to perform better than the conventional landslide susceptibility model. The conventional plus path dependent and path dependent landslide susceptibility model and their resulted maps are dynamic and change over time unlike conventional landslide susceptibility maps.

scholarly journals Estimation of Electricity Generation by an Electro-Technical Complex with Photoelectric Panels Using Statistical Methods

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1278
Author(s):  
Anna Turysheva ◽  
Irina Voytyuk ◽  
Daniel Guerra
Keyword(s):  
Random Distribution ◽  
Graphical Representation ◽  
Random Variable ◽  
Climatic Conditions ◽  
Characteristic Energy ◽  
Study Region ◽  
Factors Affecting ◽  
Solar Systems ◽  
The Republic ◽  
Technical Complex

This paper presents a computational tool for estimating energy generated by low-power photovoltaic systems based on the specific conditions of the study region since the characteristic energy equation can be obtained considering the main climatological factors affecting these systems in terms of the symmetry or skewness of the random distribution of the generated energy. Furthermore, this paper is aimed at determining any correlation that exists between meteorological variables with respect to the energy generated by 5-kW solar systems in the specific climatic conditions of the Republic of Cuba. The paper also presents the results of the influence of each climate factor on the distribution symmetry of the generated energy of the solar system. Studying symmetry in statistical models is important because they allow us to establish the degree of symmetry (or skewness), which is the probability distribution of a random variable, without having to make a graphical representation of it. Statistical skewness reports the degree to which observations are distributed evenly and proportionally above and below the center (highest) point of the distribution. In the case when the mentioned distribution is balanced, it is called symmetric.

scholarly journals Hybrid Integration Approach of Entropy with Logistic Regression and Support Vector Machine for Landslide Susceptibility Modeling

Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 884 ◽  
Author(s):  
Tingyu Zhang ◽  
Ling Han ◽  
Wei Chen ◽  
Himan Shahabi
Keyword(s):  
Support Vector Machine ◽  
Logistic Regression ◽  
Landslide Susceptibility ◽  
Shaanxi Province ◽  
Slope Aspect ◽  
Support Vector ◽  
Operating Characteristics ◽  
Study Region ◽  
Susceptibility Maps ◽  
Landslide Susceptibility Maps

The main purpose of the present study is to apply three classification models, namely, the index of entropy (IOE) model, the logistic regression (LR) model, and the support vector machine (SVM) model by radial basis function (RBF), to produce landslide susceptibility maps for the Fugu County of Shaanxi Province, China. Firstly, landslide locations were extracted from field investigation and aerial photographs, and a total of 194 landslide polygons were transformed into points to produce a landslide inventory map. Secondly, the landslide points were randomly split into two groups (70/30) for training and validation purposes, respectively. Then, 10 landslide explanatory variables, such as slope aspect, slope angle, altitude, lithology, mean annual precipitation, distance to roads, distance to rivers, distance to faults, land use, and normalized difference vegetation index (NDVI), were selected and the potential multicollinearity problems between these factors were detected by the Pearson Correlation Coefficient (PCC), the variance inflation factor (VIF), and tolerance (TOL). Subsequently, the landslide susceptibility maps for the study region were obtained using the IOE model, the LR–IOE, and the SVM–IOE model. Finally, the performance of these three models was verified and compared using the receiver operating characteristics (ROC) curve. The success rate results showed that the LR–IOE model has the highest accuracy (90.11%), followed by the IOE model (87.43%) and the SVM–IOE model (86.53%). Similarly, the AUC values also showed that the prediction accuracy expresses a similar result, with the LR–IOE model having the highest accuracy (81.84%), followed by the IOE model (76.86%) and the SVM–IOE model (76.61%). Thus, the landslide susceptibility map (LSM) for the study region can provide an effective reference for the Fugu County government to properly address land planning and mitigate landslide risk.

scholarly journals Implementing landslide path dependency in landslide susceptibility modelling

Landslides ◽  
2018 ◽  
Vol 15 (11) ◽  
pp. 2129-2144 ◽  
Author(s):  
Jalal Samia ◽  
Arnaud Temme ◽  
Arnold K. Bregt ◽  
Jakob Wallinga ◽  
John Stuiver ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Path Dependency

Path-dependency and coordination in multi-candidate elections with behavioral voters

2017 ◽  
Vol 29 (4) ◽  
pp. 520-545 ◽  
Author(s):  
Costel Andonie ◽  
Daniel Diermeier
Keyword(s):  
Stationary Distribution ◽  
Voting Behavior ◽  
Behavioral Model ◽  
Path Dependency ◽  
Plurality Rule ◽  
Aspiration Level ◽  
Initial State ◽  
Positive Impression ◽  
Path Dependent ◽  
Negative Impression

We consider a behavioral model of voting in multi-candidate elections under plurality rule. In the case of a positive impression of the campaign leader, voters increase their propensity to vote for that candidate, while in the case of a negative impression voters decrease their propensity. The formation of positive or negative impressions depends on an endogenous aspiration level. We show that in multi-candidate elections, in any stationary distribution, the winner receives a share of 50% of votes. Our results suggest that achieving coordination is ‘path-dependent’: whether voters manage to coordinate on the majority-preferred candidate critically depends on the initial state. We then identify conditions that make the election of the majority-preferred candidate more likely. However, even if the majority candidate is elected for sure, voting behavior is only partially coordinated.

scholarly journals Organizational Renewal in Family Firms

2014 ◽  
Vol 15 (2) ◽  
pp. 67-78 ◽  
Author(s):  
Sarah Drakopoulou Dodd ◽  
Vasilis Theoharakis ◽  
Angelo Bisignano
Keyword(s):  
Regression Analysis ◽  
Firm Performance ◽  
Strong Evidence ◽  
Succession Planning ◽  
Family Firms ◽  
Path Dependency ◽  
Organizational Renewal ◽  
The Past ◽  
The Future ◽  
High Level

The authors investigate whether organizational renewal impacts on the performance of family firms and identify aspects of ‘familiness’ acting as facilitators or inhibitors of organizational renewal. A survey instrument captured data on relevant family-related characteristics, organizational renewal and firm performance from the CEOs of 140 family firms in Greece. Regression analysis was used to test hypotheses. Strong evidence was found that organizational renewal impacts positively on the profit growth of family firms. Where CEOs had a strong growth aspiration for the future and were firm founders, and where succession planning was taking place, renewal was more likely to be enacted. Efforts are focused on creating a business that will thrive in the future, and not on curating an organizational heirloom shaped and constrained by the past. Their strong future focus liberates these family firms from possible cross-generational path dependency, allowing the special resources of their family's business to act instead as a springboard for ongoing organizational renewal. Conversely, those family firms with a high level of family altruism indicated by extensive kin employment seem to be more likely to be destined for stagnation than stewardship, as they promote (past-focused) historical family sentiment and tradition. The dangers of cross-generational path dependency indeed seem pronounced in such past-focused firms.

Foreign Aid and Democratization: Benin and Niger Compared

2005 ◽  
Vol 48 (3) ◽  
pp. 67-87 ◽  
Author(s):  
Mamoudou Gazibo
Keyword(s):  
Foreign Aid ◽  
Path Dependency ◽  
Financial Assistance ◽  
Democratic Process ◽  
Economic Support ◽  
Path Dependent ◽  
Critical Moments

Abstract:This article compares the democratization process in Benin and Niger in the decade from 1989 to 1999 and emphasizes the influence of external donors with regard to their economic support of democratization. The task is twofold. First, I try to understand why, though these two aid-dependent countries share many initial similarities, the former received more external financial assistance than the latter. I build upon New Institutionalist concepts such as timing, sequence, and path dependency to demonstrate that the probability and continuity of foreign aid depend both on the timing and on sequences of the transition—a combination that may or may not produce a path-dependent phenomenon with regard to the donors. Second, I argue that the capacity of foreign aid to foster democratization depends largely on its timing, particularly in critical moments of the democratic process.

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