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A substantial amount of researches have been done on the understanding and assessment of resilience from multiple perspectives, e.g., ecological, social, economic, and disaster management; however, recent international approach is trending toward more systematic and comprehensive risk assessment processes. Pivotal element of such approach is to emphasizing on promoting resilience in the face of climate change impacts. Conceptualization and identification of parameters to assess climate change resilience is one of the remaining challenges that academia is facing. Reviewing the principles of the climate change resilience highlighted in the literature, the goal of this study is to introduce a theoretical model about the climate change resilience concept to facilitate and enhance future climate change resilience-related researches. The model proposed in this study is named as the climate change resilience of place (C-CROP) model, a geo-based model which is designed to assess climate change resilience for any geographic region with an approach to the incorporation of nature-based solution (NBS). C-CROP model considers vulnerability, exposure, sensitivity to climate change on one side; another side is co-benefit, climate proofing, and disservices of proposed NBS. An operational framework of the C-CROP model is also proposed, that allows spatially explicit assessment of climate change resilience in real world by developing an indicator-based framework and comprehensive mapping using the geospatial approach. Therefore, this model includes vulnerability hotspots identification; better understanding of the pathways of resilience; and solutions (i.e., NBS) to infer the impacts and effectiveness of resilience-building interventions.

Globally, coastal zones, rivers and riverine areas, and deltas carry enormous values for ecosystems, socio-economic, and environmental perspectives. These often highly populated areas are generally significantly different from interior hinterlands in terms of population density, economic activities, and geophysical and ecological processes. Geospatial technologies are widely used by scholars from multiple disciplines to understand the dynamic nature of shoreline changes globally. In this paper, we conduct a systematic literature review to identify and interpret research patterns and themes related to shoreline change detection from 2000 to 2021. Two databases, Web of Science and Scopus, were used to identify articles that investigate shoreline change analysis using geospatial technique such as remote sensing and GIS analysis capabilities (e.g., the Digital Shoreline Analysis System (DSAS). Between the years 2000 and 2021, we initially found 1622 articles, which were inspected for suitability, leading to a final set of 905 articles for bibliometric analysis. For systematic analysis, we used Rayyan—a web-based platform used for screening literature. For bibliometric network analysis, we used the CiteSpace, Rayyan, and VOSviewer software. The findings of this study indicate that the majority of the literature originated in the USA, followed by India. Given the importance of protecting the communities living in the riverine areas, coastal zones, and delta regions, it is necessary to ask new research questions and apply cutting-edge tools and technology, such as machine learning approach and GeoAI, to fill the research gaps on shoreline change analysis. Such approaches could include, but are not limited to, centimeter level accuracy with high-resolution satellite imagery, the use of unmanned aerial vehicles (UAV), and point cloud data for both local and global level shoreline change and analysis. Published version

Coastal residents of Bangladesh are now confronted with the increased incidence, variability, and severity of weather-related hazards and disasters due to climate change-induced sea level rise (SLR). Many researchers hold the view that as a consequence residents of such area have either already migrated to inland locations or intend to so in the near future. We examine the migration of households following a flash flood event that took place in August 2020 and address intentions for future migration in the Lower Meghna Estuary of coastal Bangladesh. The data obtained for this study include 310 household surveys, field observations, and informal discussions with respondents and local people. Based on the analysis of the field data, this empirical research found one household migrated to other district within one year after the event. When the respondents were asked about their future migration intensions, only a tiny proportion, namely 21 (6.77%) households, likely will leave the study area to settle in other districts while the remaining 289 households likely will stay in the Lakshmipur district. This finding challenges the existing narratives about vulnerability to environmentally induced migration. Moreover, it provides evidence of non-migration, which is a new as well as thriving area of investigation in relation to coastal Bangladesh. Published version

Journalists play a crucial role in the dissemination of health-related information. In developing countries, such as Nepal, the media are integral in shaping the national agenda and informing the public of important health issues. With an increasing need for a collaborative effort to attain optimal health for people, animals, and the environment, the One Health approach was used to characterize health reporting in Nepal. A comprehensive survey was administered to health journalists regarding their public, animal, and environmental health reporting habits. Seventy-one journalists completed the survey across three study sites. Many journalists indicated a history of reporting across all three sectors but did not routinely focus on health reporting in general. The majority of journalists perceived the quality and overall coverage of health-related topics increased over the last five years. However, few journalists reported receiving specialized training in any health sector. Although the overall quality of health reporting in the Nepali media showed improvements, many journalists acknowledged a lack of understanding of common health topics and a desire to learn more skills related to accurate health reporting. One Health provides a conceptual framework for understanding and promoting health communication through mass media to benefit humans, animals, and ecosystems.

Road traffic accidents pose serious threats to human lives and often cause premature deaths, disabilities, and socioeconomic impacts. The objective of this study is to analyze the fatal road traffic accidents in Bangladesh by performing a space–time characterization of fatality rates involving an innovative newspaper-based method in concert with gridded population data to construct a road traffic fatality database. Kernel density estimation, temporal data plots and space–time pattern mining tools that combine the Getis-Ord Gi* statistic with the Mann–Kendall test are used to describe spatio-temporal hotspots/coldspots and trends. Results show different patterns between the urban and rural areas of Bangladesh and higher rates of road traffic accidents occur in the metropolitan regions (Dhaka) and in a northern region centered on Sirajganj area. Most of the road traffic accidents took place in between 9:00 and 12:00 pm while the accident rates remain low between 12:00 and 3:00 am. Spacetime analysis results reveal a core region of persistently high rates along with four smaller regions with high and intensifying rates. The output of this study could be useful to reduce road traffic fatalities, injuries, increase awareness, and adopt necessary interventions for public safety through integrating both the local, regional, and central level decision makers of public transportation policy and issues in Bangladesh. The approach has potential to be translated to other developing countries.

Information collected from Focus Group Meetings (FGMs) and key informant interviews (KIIs) from Ramgati Upazilla of Lakshmipur District, Bangladesh, shows that once household members have lost their homes to riverbank erosion, they rarely migrate to distant places and stay in their immediate vicinity. The overwhelming majority of the victims rebuild their homes in nearby places on the lands of their relatives, friends, and neighbors, while some rebuild homes on government properties. This action is explained using the Community Capital Framework (CCF) and Place Attachment or Sense of Place concepts. The CCF asserts that overall resilience in the face of a disaster comes from focusing on the assets in place prior to the exposure to danger across multiple dimensions such as human, social, political, financial, built, natural, and cultural capitals. These capital assets overlap each other. For example, abundant natural capital can easily translate into financial capital, which, in turn, creates a strong set of built capital, if there is political capital to administer resources. The displaced people in the study area tend to remain in the local area because of strong ties to the surrounding communities and abundant natural resources in terms of availability of potential to re-establish river-based livelihoods, access fresh and formalin free fish and vegetables, and breathe pure air. Local people are known to generously provide free land for building homes, and displaced households often receive financial support from local and national governments. All these resources make for strong ties to the locality, and therefore survivors hesitate to move to distant unknown places.

Understanding seasonal precipitation input into river basins is important for linking large-scale climate drivers with societal water resources and the occurrence of hydrologic hazards such as floods and riverbank erosion. Using satellite data at 0.25-degree resolution, spatial patterns of monsoon (June-July-August-September) precipitation variability between 1983 and 2015 within the Ganges&ndash, Brahmaputra&ndash, Meghna (GBM) river basin are analyzed with Principal Component (PC) analysis and the first three modes (PC1, PC2 and PC3) are related to global atmospheric-oceanic fields. PC1 explains 88.7% of the variance in monsoonal precipitation and resembles climatology with the center of action over Bangladesh. The eigenvector coefficients show a downward trend consistent with studies reporting a recent decline in monsoon rainfall, but little interannual variability. PC2 explains 2.9% of the variance and shows rainfall maxima to the far western and eastern portions of the basin. PC2 has an apparent decadal cycle and surface and upper-air atmospheric height fields suggest the pattern could be forced by tropical South Atlantic heating and a Rossby wave train stemming from the North Atlantic, consistent with previous studies. Finally, PC3 explains 1.5% of the variance and has high spatial variability. The distribution of precipitation is somewhat zonal, with highest values at the southern border and at the Himalayan ridge. There is strong interannual variability associated with PC3, related to the El Nino/Southern Oscillation (ENSO). Next, we perform a hydroclimatological downscaling, as precipitation attributed to the three PCs was averaged over the Pfafstetter level-04 sub-basins obtained from the World Wildlife Fund (Gland, Switzerland). While PC1 was the principal contributor of rainfall for all sub-basins, PC2 contributed the most to rainfall in the western Ganges sub-basin (4524) and PC3 contributed the most to the rainfall in the northern Brahmaputra (4529). Monsoon rainfall within these two sub-basins were the only ones to show a significant relationship (negative) with ENSO, whereas four of the eight sub-basins had a significant relationship (positive) with sea surface temperature (SST) anomalies in the tropical South Atlantic. This work demonstrates a geographic dependence on climate teleconnections in the GBM that deserves further study.

Following a targeted campaign of violence by Myanmar military, police, and local militias, more than half a million Rohingya refugees have fled to neighboring Bangladesh since August 2017, joining thousands of others living in overcrowded settlement camps in Teknaf. To accommodate this mass influx of refugees, forestland is razed to build spontaneous settlements, resulting in an enormous threat to wildlife habitats, biodiversity, and entire ecosystems in the region. Although reports indicate that this rapid and vast expansion of refugee camps in Teknaf is causing large scale environmental destruction and degradation of forestlands, no study to date has quantified the camp expansion extent or forest cover loss. Using remotely sensed Sentinel-2A and -2B imagery and a random forest (RF) machine learning algorithm with ground observation data, we quantified the territorial expansion of refugee settlements and resulting degradation of the ecological resources surrounding the three largest concentrations of refugee camps—Kutupalong–Balukhali, Nayapara–Leda and Unchiprang—that developed between pre- and post-August of 2017. Employing RF as an image classification approach for this study with a cross-validation technique, we obtained a high overall classification accuracy of 94.53% and 95.14% for 2016 and 2017 land cover maps, respectively, with overall Kappa statistics of 0.93 and 0.94. The producer and user accuracy for forest cover ranged between 92.98–98.21% and 96.49–92.98%, respectively. Results derived from the thematic maps indicate a substantial expansion of refugee settlements in the three refugee camp study sites, with an increase of 175 to 1530 hectares between 2016 and 2017, and a net growth rate of 774%. The greatest camp expansion is observed in the Kutupalong–Balukhali site, growing from 146 ha to 1365 ha with a net increase of 1219 ha (total growth rate of 835%) in the same time period. While the refugee camps’ occupancy expanded at a rapid rate, this gain mostly occurred by replacing the forested land, degrading the forest cover surrounding the three camps by 2283 ha. Such rapid degradation of forested land has already triggered ecological problems and disturbed wildlife habitats in the area since many of these makeshift resettlement camps were set up in or near corridors for wild elephants, causing the death of several Rohingyas by elephant trampling. Hence, the findings of this study may motivate the Bangladesh government and international humanitarian organizations to develop better plans to protect the ecologically sensitive forested land and wildlife habitats surrounding the refugee camps, enable more informed management of the settlements, and assist in more sustainable resource mobilization for the Rohingya refugees. Published version

A recently funded US National Science Foundation project seeks to investigate monsoon variability within the Ganges-Brahmaputra-Meghna (GBM) river basin as a potential predictor for annual shoreline erosion rates in the lower coastal delta region. Many previous studies have examined the interannual variability of South Asian precipitation either within political boundaries or across large spans of latitudes and longitudes, but few have taken a more hydrologic approach by analyzing the atmospheric-oceanic forcings that lead to precipitation falling only within the GBM basin. The temporal climate patterns would likely be different from previous studies and are hypothesized to have a more direct effect on outlet discharge and erosion rates. In the present study, mean monsoon precipitation (June-July-August-September) for the 2309 0.25° grid boxes of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) was extracted using geospatial methods. A Principal Component (PC) analysis was performed over the period 1983 to 2015. The first PC explains 88.7% of the variance and resembles climatology with the center of action over Bangladesh. The eigenvector shows a downward trend consistent with studies reporting a recent decline in monsoon rainfall. The second PC explains 2.9% of the variance and concentrates rainfall in the western portion of the basin. The 2nd component has greater temporal variability than the 1st component and an apparent decadal cycle. An analysis of global precipitation indicates that the rainfall patterns obtained within the GBM are localized. Surface and upper-air atmospheric height fields suggest the 2nd PC pattern is forced by a Rossby wave train stemming from the North Atlantic.

Natural hazards lead to unexpected and often dire situations for people who have few resources and little control over the environment in which they live. Kutubdia, an island in the southeastern part of Bangladesh, experiences frequent natural hazards that impact the livelihoods of its people and put them in vulnerable situations. The research elaborated here is the result of 300 household surveys collected from persons in Kutub- dia's fishing communities. The surveys investigated the perception and consequences of natural hazards on the fishing communities. The results indicated that the experience of natural hazards—cyclones, erosion, and flooding are examples—have increased over the years. Coastal erosion displaced seventy-two (24 percent) fishers, forcing them to relocate their houses several times and imposing multiple challenges on their lives. Literacy was not associated with perceptions of environmental changes or changes in fishing. However, young fishers—less than forty years of age—perceived that environmental changes had affected fish catch more than their older colleagues. Keywords: natural hazards, perception, fishing communities, Kutubdia Island, Bangladesh In Bangladesh, fish and fisheries are an inseparable part of the day-to-day life and livelihoods of the people. The fisheries sector plays a significant role in alleviating protein shortages, providing jobs, earning foreign currencies, and the socioeconomic development of Bangladesh. The fisheries sector contributes 4.43 percent to the national GDP and 22.21 percent to the total agricultural GDP (DoF 2011). Currently, fisheries are the second largest export sector in Bangla- desh (Chowdhury, Sukhan, and Hannan 2010; Wahab and others 2012). In the fiscal year of 2010-2011, the total of the country's export earnings from this sec- tor was 2.73 percent (DoF 2011). An estimated 1.4 million people are engaged fulltime and 12 million people as part time in the fisheries sector (Ahmed, Halim, and Sultana 2012). An overwhelming majority of these people are con- centrated in the coastal areas of Bangladesh. The total population living in the coastal zone of Bangladesh is about 36 million (Islam 2004). The livelihoods of coastal communities are highly dependent on agriculture, fishing, forestry, transportation, and salt farming (Miah, Bari, and Rahman 2010). Although the people of Bangladesh are, in *We would like to acknowledge the Gandhi Scholarship and Beck Research Fund provided by the Depart

Pakistan is a developing nation that has historically been subjected to high flooding fatality events due to its socioeconomic characteristics, population geography, and landscape attributes. Flooding in Pakistan has historically resulted from heavy rain events or periodic landfalling tropical cyclones that have afflicted the nation throughout its history. This study aggregates flooding events in Pakistan over a 62-year period to identify peak years and seasonal cycles of when flood-related fatalities have historically been highest in the nation. Seasonally, Pakistan is especially prone to flood disasters during the summer monsoon months, and also during the months of November and December, when tropical cyclone activity periodically impacts the nation. Some of the earlier flooding events have not been well documented with respect to specific months or dates of occurrence, and have therefore been excluded from the seasonal analysis portion of the study. Over the past 60 years, exceptionally high numbers of flood-related fatalities occurred in the years 1950, 1965, and 2010; peak fatality flood years are mostly attributed to single catastrophic events caused primarily by large-scale river floods or landfalling tropical cyclones.