Dersleri yüzünden oldukça stresli bir ruh haline sikiş hikayeleri bürünüp özel matematik dersinden önce rahatlayabilmek için amatör pornolar kendisini yatak odasına kapatan genç adam telefonundan porno resimleri açtığı porno filmini keyifle seyir ederek yatağını mobil porno okşar ruh dinlendirici olduğunu iddia ettikleri özel sex resim bir masaj salonunda çalışan genç masör hem sağlık hem de huzur sikiş için gelip masaj yaptıracak olan kadını gördüğünde porn nutku tutulur tüm gün boyu seksi lezbiyenleri sikiş dikizleyerek onları en savunmasız anlarında fotoğraflayan azılı erkek lavaboya geçerek fotoğraflara bakıp koca yarağını keyifle okşamaya başlar
Reach Us +1-845-458-6882


Landslide Susceptibility Models In Tumbes Peninsula, South-Central Chile Coast (36S) | 96910

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Landslide susceptibility models in Tumbes Peninsula, South-Central Chile coast (36S)

Joint Event on 5th World Conference on Climate Change & 16th Annual Meeting on Environmental Toxicology and Biological Systems

Pablo Lopez Filun, Carolina Martinez, Cristian Henriquez and Jorge Quense

University of Bristol, UKPontifical Catholic University of ChileResearch Center for Integrated Disaster Risk Management, Chile

Posters & Accepted Abstracts: Environ Pollut Climate Change

DOI: 10.4172/2573-458X-C1-003

In the last few decades, the recurrence associated to landslides has evidenced a significant increased, especially in urban areas, where the effects related to these types of processes have generated human losses and infrastructure damages. In Chile, there is still no standardized methodology for assessing areas prone to landslides on a regional and local scale, consequently in the past years many efforts have been made to incorporate different methodologies from an institutional aspect, especially to guide territorial planning from a disaster risk management view. In this context, the purpose of this research is the application of the Linear Generalized Model (GLM) and the Generalized Additive Model (GAM) in the East coast of Tumbes Peninsula (36°S) to compare their predictive performance and their integration capacity as a methodology to guide territorial planning and risk management at local scales. The landslide susceptibility in Tumbes Peninsula (36°S) was evaluated through multivariate statistical methods. An analysis of the physical - natural factors of greater contribution to the susceptibility was made and the processes of greater recurrence and spatial activity were recognized. The analysis of the physical - natural factors was done through soil cover, geomorphology and derived models. The process recognition was carried out through the elaboration of a landslide inventory, where the lithological structure and type of movement associated with each process were identified. The susceptibility level was determined through the comparison of a Generalized Linear Model (GLM) and a Generalized Additive Model (GAM), where the areas of greater susceptibility to landslides processes were identified. The elaboration of the landslide inventory indicated that the rotational landslides are the most active, these were characterized by being conformed in a lithologic structure of silt - clay, loamy type, very fragile under saturation, during periods of intense precipitation. The execution of GLM and GAM models indicated a good spatial prediction of susceptibility with AUCROC values of 0.913 and 0.990. However, the level of significance of the predictor variables presented less statistical evidence in the GLM model with an AIC value 177,7 and greater significance in the GAM model with an AIC value of 10,2 indicating the high precision of the GAM model in the spatial estimation of susceptibility.

Pablo López Filun, Ph.D. in Civil Engineering student, University of Bristol, U.K. MSc in Geography, Pontifical Catholic University of Chile and BSc in Geography, University of Concepcion, Chile.