River dynamics - a geospatial analysis of Jamuna (Brahmaputra) River in Bangladesh during 1973-2019 using Landsat satellite remote sensing data and GIS.

The present study is designed to illuminate the dynamics of the Jamuna River in Bangladesh for 46 years, from 1973 to 2019. About 240 km of the Jamuna River course was assessed using remote sensing and GIS. Landsat remote sensing imageries were processed, and bank lines were extracted and analysed using GIS. The main objective of the study was to understand the pattern of bed movement of the Jamuna River. The river dynamics were assessed based on bank erosion, accretion, bank line shifts, channel width, and river course and confluence shift. Area vulnerable to erosion was assessed using historical erosion rate and trend analysis. The result revealed that the river area increased by about 48% over 46 years. The total eroded area was about 1038 km2, with 35.40% more erosion on the left bank than on the right. Due to higher erosion than deposition, the river widened. The average width of the river increased by about 56.40% during the period. The average rate of shifting was higher on the left bank than on the right, indicating the eastward movement of the river. Impact analysis showed that overall, a total of 822 km2 and 390 km2 of croplands and settlements were eroded during the period 1973-2019. The width of the confluence at the Padma River junction decreased by about 28%. The straight shift of the confluence was 9.27 km towards the southeast. The vulnerable area assessment anticipated that there would be more erosion on the left bank than on the right, and that Kurigram, Tangail and Jamalpur are the districts most susceptible to future left bank erosion. And, the lower reach of the right bank of the Padma River is at high vulnerable to erosion at the confluence. The methods and analysis adopted in this study can be applied to any other braided river to monitor the dynamics of the river and to formulate an action plan to protect the river from erosion.

Geospatial modelling on the spread and dynamics of 154 day outbreak of the novel coronavirus (COVID-19) pandemic in Bangladesh towards vulnerability zoning and management approaches.

The novel COVID-19 is a worldwide transmitted pandemic and has received global attention. Since there is no effective medication yet, to minimize and control the transmission of the COVID-19, non-pharmaceutical interventions (NPIs) are followed globally. However, for the implementation of needful NPIs through effective management strategies and planning, space-time-based information on the nature, magnitude, pattern of transmission, hotspots, the potential risk factors, vulnerability, and risk level of the pandemic are important. Hence, this study was an attempt to in-depth assess and analyze the COVID-19 outbreak and transmission dynamics through space and time in Bangladesh using 154 day real-time epidemiological data series. District-level data were analyzed for the geospatial analysis and modelling using GIS. Getis-Ord Gi* statistics was applied for the hotspot analysis, and on the other hand, the analytical hierarchy process-based weighted sum method (AHP-WSM) was used for the modelling of vulnerability zoning of COVID-19. In Bangladesh, the status of the pandemic COVID-19 still is in exposure level. Disease transmitted at a high rate (20.37%), and doubling time of the cases were 11 days (latest week of the study period). The fatality rate was comparatively low (1.3%), and the recovery rate was about 57.50%. Geospatial analysis exhibits the disease propagates from the central parts, and Dhaka was the most exposed district followed by Chattogram, Narayanganj, Cumilla, and Bogra. A single strong clustering pattern in the central part, which spread out mainly to the south-eastern part, was identified as a prime hotspot in both the cases and deaths distributions. Additionally, potential linkages between the transmission of disease and the selected factors that gear up the spreading of the disease were identified. The central, eastern, and south-eastern parts were recognized as high vulnerable zone, and conversely, the western, south-western, north-western, and north-eastern parts as medium vulnerable zone. The vulnerable zoning exercise made it possible to identify vulnerable areas with the different magnitude that require urgent intervention through proper management and action plan, and accordingly, comprehensive management strategies were anticipated. Thus, this study will be a useful guide towards understanding the space-time-based investigations and vulnerable area delineation of the COVID-19 and assist to formulate an effective management action plan to reduce and control the disease propagation and impacts. By appropriate adjustment of some factors with local relevance, COVID-19 vulnerability zoning derived here can be applied to other regions, and generally can be used for any other infectious disease. This method was applied at a regional scale, but the availability of larger scale data of the determining factors could be applied in small areas too, and accordingly, management strategies can be formulated.

Assessing regional environmental quality by integrated use of remote sensing, GIS, and spatial multi-criteria evaluation for prioritization of environmental restoration.

This study was an attempt to analyse the regional environmental quality with the application of remote sensing, geographical information system, and spatial multiple criteria decision analysis and, to project a quantitative method applicable to identify the status of the regional environment of the study area. Using spatial multi-criteria evaluation (SMCE) approach with expert knowledge in this study, an integrated regional environmental quality index (REQI) was computed and classified into five levels of regional environment quality viz. worse, poor, moderate, good, and very good. During the process, a set of spatial criteria were selected (here, 15 criterions) together with the degree of importance of criteria in sustainability of the regional environment. Integrated remote sensing and GIS technique and models were applied to generate the necessary factors (criterions) maps for the SMCE approach. The ranking, along with expected value method, was used to standardize the factors and on the other hand, an analytical hierarchy process (AHP) was applied for calculating factor weights. The entire process was executed in the integrated land and water information system (ILWIS) software tool that supports SMCE. The analysis showed that the overall regional environmental quality of the area was at moderate level and was partly determined by elevation. Areas under worse and poor quality of environment indicated that the regional environmental status showed decline in these parts of the county. The study also revealed that the human activities, vegetation condition, soil erosion, topography, climate, and soil conditions have serious influence on the regional environment condition of the area. Considering the regional characteristics of environmental quality, priority, and practical needs for environmental restoration, the study area was further regionalized into four priority areas which may serve as base areas of decision making for the recovery, rebuilding, and protection of the environment.