The plight of the Bangladeshi silk industry: An empirical investigation

In spite of having a glorious history in the sericulture industry Bangladesh still is not a bright name in silk production and export. Although the agro-climatic situation in Bangladesh greatly favors the development of silk industry, Bangladesh produces very little amount of silk products every year, whereas India, situated beside Bangladesh, is the second largest producer of sericulture. To investigate the reason behind this, a questionnaire survey has been undertaken in which only the owners or managers have been considered as representatives of the industry. A total of 21 silk enterprises was randomly sampled. Data analyses show that almost 57% of the silk enterprises have less than 40 decimal of land while only 19% have more than 100 decimal of land. These enterprises provided very limited facilities for their workers and mostly depended on imported raw materials. Owners pointed out several constraints to the development of silk industry in Bangladesh including insufficient government patronization and recommended several remedial measures including that the Bangladesh Silk Board (BSB) gives out production credit without too much conditions, adoption of modern technology, and information dissemination . It is evident that government, through BSB and BSRTI (Bangladesh Silk Research and Training Institute) has to play a crucial role to pull this industry up from the brink of destruction

Snow Property Controls on Modeled Ku-Band Altimeter Estimates of First-Year Sea Ice Thickness: Case Studies From the Canadian and Norwegian Arctic

Uncertainty in snow properties impacts the accuracy of Arctic sea ice thickness estimates from radar altimetry. On first-year sea ice (FYI), spatiotemporal variations in snow properties can cause the Ku-band main radar scattering horizon to appear above the snow/sea ice interface. This can increase the estimated sea ice freeboard by several centimeters, leading to FYI thickness overestimations. This article examines the expected changes in Ku-band main scattering horizon and its impact on FYI thickness estimates, with variations in snow temperature, salinity, and density derived from ten naturally occurring Arctic FYI Cases encompassing saline/nonsaline, warm/cold, simple/complexly layered snow (4–45 cm) overlying FYI (48–170 cm). Using a semi-empirical modeling approach, snow properties from these Cases are used to derive layer-wise brine volume and dielectric constant estimates, to simulate the Ku-band main scattering horizon and delays in radar propagation speed. Differences between modeled and observed FYI thickness are calculated to assess sources of error. Under both cold and warm conditions, saline snow covers are shown to shift the main scattering horizon above from the snow/sea ice interface, causing thickness retrieval errors. Overestimates in FYI thicknesses of up to 65% are found for warm, saline snow overlaying thin sea ice. Our simulations exhibited a distinct shift in the main scattering horizon when the snow layer densities became greater than 440 kg/m 3 , especially under warmer snow conditions. Our simulations suggest a mean Ku-band propagation delay for snow of 39%, which is higher than 25%, suggested in previous studies

Physical length scales of wind-blown snow redistribution and accumulation on relatively smooth Arctic first-year sea ice

Snow thickness measurements over relatively smooth Arctic first-year sea ice, obtained near Cambridge Bay, Nunavut, Canada (2014, 2016 and 2017) and near Elson Lagoon, Alaska, USA (2003 and 2006), are analyzed to quantify physical length-scales and their relevant scaling behaviors. We use the Multi-Fractal Temporally Weighted Detrended Fluctuation Analysis (MF-TWDFA) method to detect two major physical length-scales from both the study areas. Our results suggest that physical processes underlying the formation of snow dunes are consistent and that the wind is the main process shaping the redistribution and variability of snow thickness. One scale, around 10 m, appears to be related to the formation of the snow "dunes", while the other scale, between 30 m and 60 m, is likely associated with the various interactions of the snow dunes including merging, calving and lateral linking showing self-organized characteristics. We suggest that a simple cellular automata model can be used to generate the variability of snow thickness on smooth Arctic first-year sea ice

Snow microstructure on sea ice: Importance for remote sensing applications

European Geosciences Union (EGU) General Assembly, 19-30 Apr 2021.-- 2 pagesSnow plays a key role in interpreting satellite remote sensing data from both active and passive sensors in the high Arctic and therefore impacts retrieved sea ice variables from these systems ( e.g., sea ice extent, thickness and age). Because there is high spatial and temporal variability in snow properties, this porous layer adds uncertainty to the interpretation of signals from spaceborne optical sensors, microwave radiometers, and radars (scatterometers, SAR, altimeters). We therefore need to improve our understanding of physical snow properties, including the snow specific surface area, snow wetness and the stratigraphy of the snowpack on different ages of sea ice in the high Arctic. The MOSAiC expedition provided a unique opportunity to deploy equivalent remote sensing sensors in-situ on the sea ice similar to those mounted on satellite platforms. To aid in the interpretation of the in situ remote sensing data collected, we used a micro computed tomography (micro-CT) device. This instrument was installed on board the Polarstern and was used to evaluate geometric and physical snow properties of in-situ snow samples. This allowed us to relate the snow samples directly to the data from the remote sensing instruments, with the goal of improving interpretation of satellite retrievals. Our data covers the full annual evolution of the snow cover properties on multiple ice types and ice topographies including level first-year (FYI), level multi-year ice (MYI) and ridges. First analysis of the data reveals possible uncertainties in the retrieved remote sensing data products related to previously unknown seasonal processes in the snowpack. For example, the refrozen porous summer ice surface, known as surface scattering layer, caused the formation of a hard layer at the multiyear ice/snow interface in the winter months, leading to significant differences in the snow stratigraphy and remote sensing signals from first-year ice, which has not experienced summer melt, and multiyear ice. Furthermore, liquid water dominates the extreme coarsening of snow grains in the summer months and in winter the temporally large temperature gradients caused strong metamorphism, leading to brine inclusions in the snowpack and large depth hoar structures, all this significantly influences the signal response of remote sensing instrumentsPeer reviewe

Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice

Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0∘ (nadir) and 50∘. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous air–snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air–snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice

Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice

Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0∘ (nadir) and 50∘. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous air–snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air–snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice

Migration objectives and their fulfillment: A micro study of the rural-urban migrants of the slums of Dhaka city

Rural-Urban migration plays an important role in poverty reduction and economic development. In Bangladesh rural-urban migration is the most important factor for rapid urbanization with urban slums being a popular destination for poor rural-urban migrants. More than 15 million people live in the slums of six divisional cities of Bangladesh. Capital Dhaka alone contains about 3.4 million people in 4966 slums. Focusing on the two largest slums of Dhaka, the study reveals that predominantly migrants came from the northern and southern parts of the country and carried with them dreams of prosperity. This study evaluates the migration objectives, status and the fulfillment of their migration objectives based on a survey of 373 randomly selected temporary and permanent migrants. It was found that 82% of the migrants perceived that their migration objectives as had been either totally fulfilled or on the way of fulfillment. It was also discovered that although 68.10% of the migrants were satisfied with the socio- economic attainment of their migration objectives and wanted to come back to their place of origin after saving enough money, so that they could live the rest of their life out of poverty, they could not do so. The rural lack of earning opportunities did not permit them to reverse the rural-urban migration trend

Sea Ice Melt Onset Dynamics in the Northern Canadian Arctic Archipelago from RADARSAT, 1997-2014

An algorithm was developed to detect melt onset over Arctic sea ice using high-resolution SAR images from RADARSAT. The algorithm is based on the temporal evolution of the SAR backscatter coefficient (σ⁰), using an ice type specific threshold approach that also corrects for backscatter incidence angle variation. Using 4457 RADARSAT images, the algorithm was applied over sea ice in the northern CAA, thus generating a new time series of melt onset from 1997-2014. The mean annual melt onset date was on YD 164±4 (mid–June). No significant trend was found over the 18-year period, however, variability increased in post-2007 years. An earlier (later) melt onset was associated with increased (decreased) solar energy absorption and subsequently associated in lighter (heavier) September sea ice coverage in the northern CAA. RADARSAT estimates of melt onset were found to be in good agreement but more robust compared to passive microwave and scatterometer estimates

Monitoring Arctic Sea Ice from Spaceborne L-band Synthetic Aperture Radar

As the Arctic is vast and largely inaccessible, concerns point to the increasing role of innovative earth observation technology for monitoring sea ice environments and conditions. The enhanced capabilities of L-band synthetic aperture radar (SAR) make it a critical technology for developing effective sea ice monitoring strategies. The use of L-band SAR imagery is limited in sea ice research; therefore, it presents a unique opportunity to investigate its advantages and challenges relative to other frequencies. The overarching goal of this research is to characterize the relationship between sea ice geophysical and thermodynamic properties and L-band SAR signatures over the seasonal cycle. To achieve this, L-band SAR imagery was investigated for i) incidence angle induced backscatter variability, ii) snow-covered sea ice thermodynamic monitoring, and iii) newly formed sea ice identification and classification. At first, this doctoral work investigated incidence angle dependency for L-band SAR backscatter and developed an image processing workflow to normalize the incidence angle induced backscatter variability for operation sea ice monitoring. Next, time-series L-band SAR imagery was used to evaluate the first-ever full annual-cycle evolution of L-band backscatter over first-year and multi-year sea ice. Finally, a novel dual-frequency approach was developed to identify newly formed sea ice in the Arctic and demonstrated that a combination of C- and L-band could substantially increase sea ice classification accuracy. This doctoral research provided baseline information on the utility of L-band SAR imagery and demonstrated its advantages over other frequencies for sea ice measurement and monitoring, which will be invaluable to existing, pending and upcoming L-band SAR missions