Coastal, Livelihood, Infrastructure, Cyclone, Bangladesh,

Keeping the dynamic nature of Coronaviruses (COVID-19) pandemic in mind, we have opted to explore the importance of the decentralization of COVID-19 testing centers across the country of Bangladesh in order to combat the pandemic. In doing so, we considered quantitative, qualitative, and geographic information systems (GIS) datasets to identify the location of existing COVID-19 testing centers. Moreover, we attempted to collect data from the existing centers in order to demonstrate testing times at the divisional level of the country. Results show that the number of testing centers is not enough to cater to the vast population of the country. Additionally, we found that the number of days it takes to receive the results from the COVID-19 testing centers is not optimal at divisional cities, let alone the remote rural areas. Finally, we propose a set of recommendations in order to enhance the existing system to assist more people under a testing range of COVID-19 viruses at the local level.

The northeastern region of Bangladesh often experiences flash flooding during the pre-harvesting period of the boro rice crop, which is the major cereal crop in the country. In this study, our objective was to delineate the impact of the 2017 flash flood (that initiated on 27 March 2017) on boro rice using multi-temporal Landsat-8 OLI and MODIS data. Initially, we opted to use Landsat-8 OLI data for mapping the damages; however, during and after the flooding event the acquisition of cloud free images were challenging. Thus, we used this data to map the cultivated boro rice acreage considering the planting to mature stages of the crop. Also, in order to map the extent of the damaged boro area, we utilized MODIS data as their 16-day composites provided cloud free information. Our results indicated that both the cultivated and damaged boro area estimates based on satellite data had strong relationships while compared to the ground-based estimates (i.e., r2 values approximately 0.92 for both cases, and RMSE of 18,374 and 9380 ha for cultivated and damaged areas, respectively). Finally, we believe that our study would be critical for planning and ensuring food security for the country.

PurposeThe opportunities and potentials of the coastal zone all over the world have not received much attention, and also the disaster mitigation approaches are seen as a curative measure rather than protective, both of which raise questions about sustainable coastal belt planning and development. What is needed is a multidisciplinary approach to tackle the complexity of social systems, and patterns of vulnerability in those systems. The aim of this paper is to attempt to understand those challenges in context of cyclone SIDR 2007 in Bangladesh.Design/methodology/approachThe combination of spatial and socio‐economic data in this study is based on an empirical analysis. After clustering the geographical boundary, a systematic random sampling technique was applied to identify the respondents for a household survey. A total of 47 percent of the respondents were illiterate and thus required the help of data collectors. In‐depth interviews were conducted with the victims of cyclone Sidr to ascertain their experiences during the event.FindingsThe heterogeneous characteristics of the respondents show that the impact of disasters varies from individual to individual, group to group and community to community. It is evident that an affected community waiting for relief and reconstruction materials attracts “dependency on relief works” which makes them more “vulnerable” to other calamities. In the long run it increases the poverty ratio and pressurizes them to stay in a “vulnerability trap” in any type of calamity. Furthermore, it reveals a socio‐infrastructural vulnerability and also the overall “social vulnerability” concepts by using a combination of socio‐spatial data.Originality/valueThis paper contains valuable information regarding the adaptation strategies to cyclone hazards resorted to by coastal peoples in Bangladesh.

Understanding the warming trends at local level is critical; and, the development of relevant adaptation and mitigation policies at those levels are quite challenging. Here, our overall goal was to generate local warming trend map at 1 km spatial resolution by using: (i) Moderate Resolution Imaging Spectroradiometer (MODIS)-based 8-day composite surface temperature data; (ii) weather station-based yearly average air temperature data; and (iii) air temperature normal (i.e., 30 year average) data over the Canadian province of Alberta during the period 1961–2010. Thus, we analysed the station-based air temperature data in generating relationships between air temperature normal and yearly average air temperature in order to facilitate the selection of year-specific MODIS-based surface temperature data. These MODIS data in conjunction with weather station-based air temperature normal data were then used to model local warming trends. We observed that almost 88% areas of the province experienced warming trends (i.e., up to 1.5°C). The study concluded that remote sensing technology could be useful for delineating generic trends associated with local warming.

Wildland fires are some of the critical natural hazards that pose a significant threat to the communities located in the vicinity of forested/vegetated areas. In this paper, our overall objective was to study the structural damages due to the 2016 Horse River Fire (HRF) that happened in Fort McMurray (Alberta, Canada) by employing primarily very high spatial resolution optical satellite data, i.e., WorldView-2. Thus, our activities included the: (i) estimation of the structural damages; and (ii) delineation of the wildland-urban interface (WUI) and its associated buffers at certain intervals, and their utilization in assessing potential risks. Our proposed method of remote sensing-based estimates of the number of structural damages was compared with the ground-based information available from the Planning and Development Recovery Committee Task Force of Regional Municipality of Wood Buffalo (RMWB); and found a strong linear relationship (i.e., r2 value of 0.97 with a slope of 0.97). Upon delineating the WUI and its associated buffer zones at 10 m, 30 m, 50 m, 70 m and 100 m distances; we found existence of vegetation within the 30 m buffers from the WUI for all of the damaged structures. In addition, we noticed that the relevant authorities had removed vegetation in some areas between 30 m and 70 m buffers from the WUI, which was proven to be effective in order to protect the structures in the adjacent communities. Furthermore, we mapped the wildland fire-induced vulnerable areas upon considering the WUI and its associated buffers. Our analysis revealed that approximately 30% of the areas within the buffer zones of 10 m and 30 m were vulnerable due to the presence of vegetation; in which, approximately 7% were burned during the 2016 HRF event that led the structural damages. Consequently, we suggest to remove the existing vegetation within these critical zones and also monitor the region at a regular interval in order to reduce the wildland fire-induced risk.

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Pan-sharpening is the process of fusing higher spatial resolution panchromatic (PAN) with lower spatial resolution multispectral (MS) imagery to create higher spatial resolution MS images. Here, our overall objective was to pan-sharpen Landsat-8 images and calculate vegetation greenness (i.e., normalized difference vegetation index (NDVI)), canopy structure (i.e., enhanced vegetation index (EVI)), and canopy water content (i.e., normalized difference water index (NDWI))-related variables. Our proposed methods consisted of: (i)