Ordinal Logistic Regression to Automatic Classify Shallow Landslide Risk Level in Sao Paulo City, Brazil

2020 ◽  
pp. 467-474
Author(s):  
Erica Akemi Goto ◽  
Keith C. Clarke
Keyword(s):  
Logistic Regression ◽  
Sao Paulo ◽  
Shallow Landslide ◽  
Ordinal Logistic Regression ◽  
Risk Level ◽  
Landslide Risk ◽  
São Paulo

Mapping of risk and susceptibility of shallow-landslide in the city of São Paulo, Brazil

Geomorphology ◽  
2012 ◽  
Vol 169-170 ◽  
pp. 30-44 ◽  
Author(s):  
Fabrizio de Luiz Rosito Listo ◽  
Bianca Carvalho Vieira
Keyword(s):  
Sao Paulo ◽  
Shallow Landslide ◽  
São Paulo ◽  
The City

Landslide risk assessment considering socionatural factors: methodology and application to Cubatão municipality, São Paulo, Brazil

2021 ◽  
Author(s):  
Paulo Rodolpho Pereira Hader ◽  
Fábio Augusto Gomes Vieira Reis ◽  
Anna Silvia Palcheco Peixoto
Keyword(s):  
Risk Assessment ◽  
Sao Paulo ◽  
Landslide Risk ◽  
São Paulo ◽  
Landslide Risk Assessment

scholarly journals Abortion withdrawal of sexual violence pregnancy: the role of the sex offender

2020 ◽  
Vol 30 (2) ◽  
pp. 170-178 ◽  
Author(s):  
Renata Macedo Martins Pimentel ◽  
Jefferson Drezett ◽  
Hugo Macedo Jr ◽  
Solange Andreoni ◽  
Rebeca Souza e Silva
Keyword(s):  
Logistic Regression ◽  
Sexual Violence ◽  
Pregnant Women ◽  
Gestational Age ◽  
Sex Offender ◽  
Sao Paulo ◽  
Legal Abortion ◽  
São Paulo ◽  
Convenience Sample ◽  
Low Education

Introduction: Unwanted pregnancy is a serious consequence for women who experience sexual violence. Although deciding on abortion is frequent in these cases, there is not much information on women who give up abortion in this circumstance. Objective: To analyse the associated factors in abortion withdrawal of sexual violence pregnancy. Methods: A cross-sectional epidemiological study with a convenience sample of adolescents and women with pregnancy due to sexual violence and requesting legal abortion between August 1994 and December 2012, at Hospital Pérola Byington, São Paulo, Brazil. Pregnant women who gave up abortion after receiving the procedure approval were included and, in another group, pregnant women who completed the abortion. The variables were selected from a digitized database and analyzed using SPSS 15.0 software. The outcome was abortion withdrawal. The study variables were age; low education level; gestational age; color/black ethnicity; not being united; declare religion; serious threat from the aggressor; known offender; and residence of the aggressor. Odds ratios with 95% confidence intervals were calculated. The analysis used Wald's chi-square test (?2W) and logistic regression with variable of interest defined as the known aggressor. The research was approved by the Research Ethics Committee of the Federal University of São Paulo, Opinion No. 6767. Results: The study included 941 women, 849 (90.2%) who had an abortion and 92 (9.8%) who gave up after being approved. Age ranged from 10-46 years, mean 23.2 ± 7.9 years, gestational age 4-22 weeks, average 11.9 ± 4.5 weeks. Among those who gave up abortion, 12.0% were <14 years old; 50.0% had gestational age ? 13 weeks; 50.0% had low education; 14.2% were black; 90.2% single; 85.9% declared to have religion; 50.0% were threatened; 12.0% of the cases occurred at the perpetrator's residence and 53.3% of the victims were raped by known perpetrators. In logistic regression, the only significant variable was the known perpetrator, increasing the victim's chance of giving up abortion twice. Conclusion: The known sex offender has influenced the woman or adolescent's decision to give up legal abortion.

scholarly journals Flash Flood Forecasting in São Paulo Using a Binary Logistic Regression Model

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 473
Author(s):  
Andrea Salomé Viteri López ◽  
Carlos Augusto Morales Rodriguez
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Flash Flood ◽  
Binary Logistic Regression ◽  
Flood Forecasting ◽  
Sao Paulo ◽  
São Paulo ◽  
Flood Events ◽  
The City

This study presents a flash flood forecasting model that uses a binary logistic regression method to determine the occurrence of flash flood events in different watersheds in the city of São Paulo, Brazil. This study is based on two years (2015–2016) of rain estimates from a dual-polarization S-band Doppler weather radar (SPOL) and flood locations observed by the Climate Emergency Management Center (CGE) of São Paulo City Hall. The logistic regression model is based on daily accumulated precipitation, a maximum precipitation rate, and daily rainfall duration. The model presented a probability of detection (POD) of 46% (71%) on average for flood events (conditional), while, for events without flash flood, it reached 98% probability. Despite the low averaged POD for flash flood occurrence, the model demonstrated a good performance for watersheds located in the east of the city near the Tietê River and in the southeast with probabilities above 50%.

scholarly journals Estimate of housing and population in landslide risk areas in California (USA) and coastal São Paulo (Brazil)

2018 ◽  
Vol 3 (61E) ◽  
pp. 319-337
Author(s):  
Saulo De Oliveira-Folharini ◽  
Regina Célia De-Oliveira ◽  
J. Christopher Brown
Keyword(s):  
Forest Fires ◽  
Census Data ◽  
Satellite Image ◽  
Sao Paulo ◽  
Landslide Risk ◽  
São Paulo ◽  
Risk Area ◽  
The Face ◽  
Risk Areas ◽  
High Precipitation

The States of California and São Paulo are associated historically with natural disasters including forest fires and high precipitation, respectively. These events end up causing numerous deaths and financial and social losses. Even in the face of loss of life, and in some cases despite the lack of urban planning, populations still choose to live in places of risk, valuing them for scenic beauty or exclusivity. The aim of this study is to estimate the amount of people and housing in landslide risk areas in California and the São Paulo state coastal zone, using satellite image classification, Aster DEM and census data. The results indicate that in California, from 2000 to 2016, the urban area increased 1.83% and São Paulo increased 14.92%, indicating that occupation in the landslide risk area in California was already consolidated, and in São Paulo there was a large increase in risk because the increased population. Compared to California, São Paulo’s population and housing is a much greater landslide risk.

scholarly journals Shallow landslide prediction in the Serra do Mar, São Paulo, Brazil

2010 ◽  
Vol 10 (9) ◽  
pp. 1829-1837 ◽  
Author(s):  
B. C. Vieira ◽  
N. F. Fernandes ◽  
O. A. Filho
Keyword(s):  
Sao Paulo ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Southeastern Brazil ◽  
Mountain Range ◽  
São Paulo ◽  
Catchment Scale ◽  
Landslide Prediction ◽  
Serra Do Mar ◽  
Number Of Cells

Abstract. Various methods are currently used in order to predict shallow landslides within the catchment scale. Among them, physically based models present advantages associated with the physical description of processes by means of mathematical equations. The main objective of this research is the prediction of shallow landslides using TRIGRS model, in a pilot catchment located at Serra do Mar mountain range, São Paulo State, southeastern Brazil. Susceptibility scenarios have been simulated taking into account different mechanical and hydrological values. These scenarios were analysed based on a landslide scars map from the January 1985 event, upon which two indexes were applied: Scars Concentration (SC – ratio between the number of cells with scars, in each class, and the total number of cells with scars within the catchment) and Landslide Potential (LP – ratio between the number of cells with scars, in each class, and the total number of cells in that same class). The results showed a significant agreement between the simulated scenarios and the scar's map. In unstable areas (SF≤1), the SC values exceeded 50% in all scenarios. Based on the results, the use of this model should be considered an important tool for shallow landslide prediction, especially in areas where mechanical and hydrological properties of the materials are not well known.

scholarly journals Association between self-control and health risk behaviors: a cross-sectional study with 9th grade adolescents in São Paulo

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Roberta Corradi Astolfi ◽  
Maria Alvim Leite ◽  
Cassio Henrique Gomide Papa ◽  
Marcelo Ryngelblum ◽  
Manuel Eisner ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Health Risk ◽  
Risk Behaviors ◽  
Multinomial Logistic Regression ◽  
Health Risk Behaviors ◽  
Sao Paulo ◽  
Self Control ◽  
Vulnerable Groups ◽  
São Paulo ◽  
9Th Grade

Abstract Background Self-control (SC) has been consistently found associated with diverse health risk behaviors (HRBs), but little research refers to low- and middle-income countries. Furthermore, there is evidence that some HRBs tend to aggregate, however studies with the specific purpose of addressing the relation between SC and multiple health risk behaviors (MHRBs) are rare. The objective of this study is to analyze these associations and provide evidence to help filling these gaps. Methods A sample of 2106 9th grade students from the city of São Paulo responded a self-administered questionnaire in 2017. We tested the association of SC measured as an ordinal variable with four levels (higher, high, medium and low) with six HRBs (binge drinking, marijuana use, smoking, high consumption of ultra-processed food, sedentary behavior and bullying perpetration), in both separated and aggregated forms (MHRBs), controlling for potential confounders. Binary logistic regression was used to test the association between exposure (SC) and single outcomes. In order to analyze the association of SC with MHRBs, multinomial logistic regression was employed. Results SC was associated with five of six HRBs investigated and with MHRBs. The effect size of the association of SC and MHRBs increased in a steep pattern with accumulation of more HRBs. Conclusion Low self-control is associated with most HRBs investigated and the magnitude of the association increases when more than two or three HRBs are accumulated. There seems to be a group of adolescents in a position of pronounced vulnerability for MHRBs. This should be considered when designing public policy and prevention programs. In contexts of limited or scarce resources and public funds, interventions focusing the most vulnerable groups, instead of universal interventions, should be considered.

Chapter 10: Learning From Co-Produced Landslide Risk Mitigation Strategies in Low-Income Settlements in Medellín (Colombia) and São Paulo (Brazil)

2020 ◽  
pp. 243-266
Author(s):  
Harry Smith ◽  
Soledad Garcia-Ferrari ◽  
Gabriela Medero ◽  
Helena Rivera ◽  
Françoise Coupé ◽  
...  
Keyword(s):  
Low Income ◽  
Risk Mitigation ◽  
Sao Paulo ◽  
Mitigation Strategies ◽  
Landslide Risk ◽  
São Paulo ◽  
Risk Mitigation Strategies
Sign in / Sign up

Export Citation Format

Share Document