Landslide Hazard Knowledge, Risk Perception and Preparedness in Southeast Bangladesh

Predictive landslide susceptibility modeling in the southeastern hilly region of Bangladesh: application of machine learning algorithms in Khagrachari district

Landslides pose a severe threat to people, buildings, and infrastructure. The rugged terrain of the Chattogram Hill Tract region in southeastern Bangladesh frequently experiences landslides, particularly during rainy seasons. This study provides a comparative analysis of innovative machine learning (ML) algorithms used for the purpose of landslide susceptibility (LS) mapping for the Khagrachari district of Bangladesh. The dataset for this study comprises 15 landslide conditioning factors and 127 landslide inventory points. The landslide inventory points included 71 landslide and 56 non-landslide points. Then, the data were split randomly into training data (70%) and testing data (30%). Three ML algorithms, namely random forest (RF), boosted regression trees (BRT), and k-nearest neighbor (KNN), were utilized to evaluate the LS zone. The models were validated using the area under the curve (AUC), overall accuracy, precision, and recall. Based on the AUC value, the BRT model demonstrated the highest performance with a value of 0.95, while the AUC values for RF and KNN were 0.91 and 0.86, respectively. Besides, overall accuracy, precision, and recall values (0.82, 0.81, and 0.86) also indicated BRT as the most effective model. The results showed that maximum rainfall and elevation were the most influential factors for both BRT and RF models. This research provides valuable insight into understanding the LS areas in Khagrachari, aiding in informed decision-making regarding landslide-related concerns in the region, and can be applied to the broader scale to develop effective planning and mitigation strategies for comprehensive disaster management and natural hazard response.

GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh

The frequency of landslides and related economic and environmental damage has increased in recent decades across the hilly areas of the world, no exception is Bangladesh. Considering the first step in landslide disaster management, different methods have been applied but no methods found as best one. As a result, landslide assessment using different methods in different geographical regions has significant importance. The research aims to prepare and evaluate landslide susceptibility maps (LSMs) of the Chattogram district using three machine learning algorithms of Logistic Regression (LR), Random forest (RF) and Decision and Regression Tree (DRT). Sixteen landslide conditioning factors were determined considering topographic, hydro-climatic, geologic and anthropogenic influence. The landslide inventory database (255 locations) was randomly divided into training (80 %) and testing (20 %) sets. The LSMs showed that almost 9-12 % of areas of the Chattogram district are highly susceptible to landslides. The highly susceptible zones cover the Chattogram district's hill ranges where active morphological processes (erosion and denudation) are dominant. The ROC values for training data were 0.943, 0.917 and 0.947 and testing data were 0.963, 0.934 and 0.905 for LR, RF and DRT models, respectively. The accuracy is higher than the previous research in comparison to the extent of the study area and the size of the inventory. Among the models, LR showed the highest prediction rate and DRT showed the highest success rate. According to susceptibility zones, DRT is the more realistic model followed by LR. The maps can be applied at the local scale for landslide hazard management.

Enhancing landslide risk reduction strategies in Southeast Bangladesh

Since 2000, landslides in southeast Bangladesh have resulted in over 700 deaths, most of which were in informal settlements. For instance, the 2007 landslides in informal settlements in Chittagong and the 2017 landslides in Rangamati took 127 and 150 lives, respectively. Although the government of Bangladesh claims to implement risk reduction, the number of deaths associated with landslides is increasing. Hence, this study investigated the ways to enhance landslide risk reduction interventions by addressing several scientific and technical issues related to disaster risk reduction. This study conducted focus group discussions, key informant interviews and expert interviews with key stakeholders in landslide risk management to collect qualitative data. Moreover, the historical accounts of settlements, media reporting, institutional action plans and policies were reviewed.

Contribution

By integrating primary and secondary data, this study found that several political-economic aspects are major anthropogenic contributors to the recent increase in landslides in the region. The contributing factors included the following: policy and action plans to raise regional population; land management; illegal deforestation; plans to establish hydroelectricity in hilly areas; ownership of settlements; manipulation of water, gas and electricity supply to illegal settlements; commercial plantations; lack of risk governance; unplanned development activities; natural population rise; increased settlement along hill slopes. This study identified and discussed lessons learned from previous landslide disasters, the weakness of early warning systems and their dissemination and ways to improve evacuation, rescue, relief and risk reduction. Finally, this study formulated recommendations for the effective implementation of landslide risk reduction in southeast Bangladesh.

Factors of cyclone disaster deaths in coastal Bangladesh

Bangladesh's success in disaster risk management is often evidenced by referencing the reduction of deaths caused by tropical cyclones - the Cyclone Gorky 1991 caused 147,000 deaths, the Cyclone Sidr 2007 caused 4500 deaths and only 6 deaths by the Cyclone Mora in 2017. This raises questions of how deaths occurred by tropical cyclones in the past and what factors still might contribute towards deaths from cyclone hazards? This study answers these questions through face-to-face interviews with 362 residents, field visits and observations across coastal Bangladesh. The findings indicate that there have been improvements in house structures and design, warning responses and evacuation processes to public cyclone shelters and informal cyclone shelter centres. In the past, due to a lack of built infrastructure, strong residential houses and public cyclone shelters, deaths occurred whilst living in fragile houses; attempting to survive through holding trees and floating in storm surges. The top ten factors that may still cause deaths by tropical cyclones include: (1) Living adjacent to the coast without an embankment or lack of embankment, or the failure of an established embankment; (2) the repeat of a 1991-like cyclone; (3) non-evacuation following early warning; (4) poor roads in remote areas to facilitate mass movement; (5) distance to and insufficient number of public cyclone shelters; (6) lack of protective measures for the rising number of elderly and disabled people; (7) community's unawareness; (8) communication failure during the emergency period; (9) failure to evacuate people from remote locations; and (10) Poor radio signal and mobile network issues resulting in no warning information being effectively and timely communicated. This study provides several key recommendations addressing these factors of deaths, to be implemented by individual, community, private sectors, non-government organisations (NGOs) and public sectors across coastal Bangladesh.

A review on landslide susceptibility mapping research in Bangladesh

Landslide susceptibility mapping is a common practice for landslide susceptibility assessment across the world. Like many other mountainous areas of the world, Bangladesh is facing frequent catastrophic landslides causing severe damage to the economy and society. As a result, several types of research have been conducted on landslides in Bangladesh. In the current research, a systematic review is conducted on the existing literature related to landslide susceptibility mapping to assess its contemporary trend with global research. The publications analyzed in this research were extracted from a website comprising landslide research of Bangladesh and by manual search. The aspects of the literature considered are year of publication, the journal where published, location/size of the study area, landslide inventory data type, susceptibility assessment/mapping method, thematic variables used, DEM characteristics, accuracy assessment methods and acquired accuracy of the models. The Chi-square test was conducted and correlation was measured to assess relation between selected features and map accuracy but no significant relationship was found. The studies are concentrated into three administrative districts of Chattogram, Rangamati and Cox's Bazar mainly covering the city centre. The publication rate is increasing but not following the global trend. Though various types of models are used and compared, the application of machine and deep learning algorithms are very limited and no evidence of Physically-based methods is found. Most of the cases, landslide inventory is prepared by conducting field survey, but the size is small. The research will help future practitioner in landslide susceptibility mapping research in the area.

Effect of individual characteristics, risk perception, self-efficacy and social support on willingness to relocate due to floods and landslides

People may have to leave their home, environment, region and country because of disasters or disaster risks. Effective and efficient disaster risk reduction activities involving the community can reduce disaster risks and enable people to reside more safely and peacefully in their environment. The objective of this study was to investigate whether individual characteristics, risk perception, self-efficacy and perceived social support were correlated with the willingness to relocate due to floods and landslides. The data were collected from 947 people residing in Gümüşhane Province (Türkiye) using a survey. In the study, a total of ten models were tested with the help of ordinal logistic regression analysis. Consequently, the participants' willingness to relocate due to landslides was determined to be higher than the willingness to relocate due to floods. University students and people with chronic diseases and flood and landslide experiences had a greater willingness to relocate. Residence duration and informal social support were negatively correlated with relocation willingness. Those who believed that they could protect themselves in the event of a flood and landslide were more likely to relocate. Among risk perceptions, probability increased relocation willingness mostly due to floods, while fear increased relocation willingness mostly due to landslides. This study attempted to provide policy makers and scientists insight into disaster risk reduction and disaster risk communication related to relocation.

Where Does an Individual’s Willingness to Act on Alleviating the Climate Crisis in Korea Arise from?

Climate change is the result of anthropogenic activities and will lead to widespread and rapid changes on Earth in the following decades. The climate change crisis has led to economic, social, and cultural crises worldwide. This study analyzes the factors impacting the voluntary actions of individuals to mitigate the climate change crisis. Data were collected using a self-administered questionnaire survey from 650 Korean adults. Statistical analysis was performed using the statistical program IBM SPSS Statistics 25. The results show that the factors affecting an individual’s willingness to act on climate change mitigation were gender, social class, perceived severity, perceived benefits, perceived obstacles, environmental attitude, and social exclusion. In particular, the results show that social exclusion had a moderating effect on the severity of the willingness to act on climate change mitigation. Regarding the moderating effect of social exclusion, significance was determined for gender, social class, perceived severity, perceived benefits, perceived obstacles, environmental attitude, and social exclusion (R2 = 0.617). The government should thus make efforts to reduce social exclusion in order to strengthen individuals’ willingness to act on climate change mitigation.

Earthquake Threat! Understanding the Intention to Prepare for the Big One

Knowledge about how hazard-threatened individuals perceive risks and what influences their intentions to prepare is crucial for effective disaster management. We investigated (a) whether residents of objectively higher-risk earthquake areas within a city perceive greater risk, have stronger intentions to prepare, and report more preparation than residents of objectively lower-risk areas, (b) 10 antecedent factors as predictors of the intention to prepare for an earthquake, and (c) whether risk perception mediates the relations between nine antecedent factors and the intention to prepare. Notably, residents of high-risk areas did not express stronger intentions to prepare or report more preparations than did residents of low-risk areas, despite perceiving significantly greater risk. Risk perception mediated the relation between antecedent fatalism and the intention to prepare. Among the policy implications is a clear need for greater education of residents in high-risk earthquake areas.

Study of the Training of Environmentalists through Gamification as A University Course

The United Nations Agenda for 2030 lists Sustainable Development Goals which include quality education, which we have pursued in the Undergraduate Final Project of the Environmental Sciences Degree at the University of Granada (Spain). This entailed designing sustainable cities, including the management of natural hazards. We created an innovative didactic model using gamification, in which the student adopted the researcher role using the computer game Cities: Skylines as a simulation tool. Using a design-based method, we conducted a qualitative single-case study in which the professor observed the process and guided the student’s self-learning in a fun way. Under this guidance, the student made decisions alone in order to simulate a sustainable city, and afterwards to analyse the findings. Three variables were considered in order to evaluate the results concerning the quality of the student’s learning: (1) the experiment using the game, (2) motivation, and (3) the skills acquired. In all three, the student earned a high score. Of the 12 skills established as the specific goals of the teaching plan, the student reached a very high level in 10, and a high level in two, implying the overall success of the learning process. The study achieved its main goal, as an innovative didactic methodology was established based on student’s research, using gamification and simulation with a technological tool. Moreover, the case study gave positive results, with the student proving capable of developing scientific and professional competencies at an optimal level.