1,720,977 research outputs found
Mercury contamination in deposited dust and its bioaccumulation patterns throughout Pakistan
No full textSpatial distribution of dust-bound trace elements in Pakistan and their implications for human exposure
No full textIndustries' Location as Jeopardy for Sustainable Urban Development in Asia : A Review of the Bangladesh Leather Processing Industry Relocation Plan
No full textThe article reviews the Bangladesh leather processing industriesâ relocation plan by applying the Social Theories of the City and the three environmental economics theoriesâWillingness to Pay, Pigovian Tax and Hedonic Pricing Method on the data collected by a questionnaire survey among the industriesâ owners and from the original project documents. Results prove the strong unwillingness of leather industriesâ owners to relocate and pay for relocation, failure at imposing Pigovian tax and the high hedonic prices of the houses including threats to inhabitantsâ health in the redeveloped residential area. In addition to high subsidy and compensation, historic growth trends and potential risks of flood and surface water resource pollution of Dhaka defy sustainability issues. Considering three consecutive failures to meet the relocation deadlines, these results claim that redeveloping an environment friendly leather processing zone at the present location will ensure sustainable urban development.</p
Human and Ecological Impacts of Freshwater Degradation on Large Scales. Development and Integration of Spatial Models with Ecological Models for Spatial-ecological Analyses
No full textIn the new epoch of Anthropocene, global freshwater resources are experiencing extensive degradation from a multitude of stressors. Consequently, freshwater ecosystems are threatened by a considerable loss of biodiversity as well as substantial decrease in adequate and secured freshwater supply for human usage, not only on local scales, but also on regional to global scales. Large scale assessments of human and ecological impacts of freshwater degradation enable an integrated freshwater management as well as complement small scale approaches. Geographic information systems (GIS) and spatial statistics (SS) have shown considerable potential in ecological and ecotoxicological research to quantify stressor impacts on humans and ecological entitles, and disentangle the relationships between drivers and ecological entities on large scales through an integrated spatial-ecological approach. However, integration of GIS and SS with ecological and ecotoxicological models are scarce and hence the large scale spatial picture of the extent and magnitude of freshwater stressors as well as their human and ecological impacts is still opaque. This Ph.D. thesis contributes novel GIS and SS tools as well as adapts and advances available spatial models and integrates them with ecological models to enable large scale human and ecological impacts identification from freshwater degradation. The main aim was to identify and quantify the effects of stressors, i.e climate change and trace metals, on the freshwater assemblage structure and trait composition, and human health, respectively, on large scales, i.e. European and Asian freshwater networks. The thesis starts with an introduction to the conceptual framework and objectives (chapter 1). It proceeds with outlining two novel open-source algorithms for quantification of the magnitude and effects of catchment scale stressors (chapter 2). The algorithms, i.e. jointly called ATRIC, automatically select an accumulation threshold for stream network extraction from digital elevation models (DEM) by assuring the highest concordance between DEM-derived and traditionally mapped stream networks. Moreover, they delineate catchments and upstream riparian corridors for given stream sampling points after snapping them to the DEM-derived stream network. ATRIC showed similar or better performance than the available comparable algorithms, and is capable of processing large scale datasets. It enables an integrated and transboundary management of freshwater resources by quantifying the magnitude of effects of catchment scale stressors. Spatially shifting temporal points (SSTP), outlined in chapter 3, estimates pooled within-time series (PTS) variograms by spatializing temporal data points and shifting them. Data were pooled by ensuring consistency of spatial structure and temporal stationarity within a time series, while pooling sufficient number of data points and increasing data density for a reliable variogram estimation. SSTP estimated PTS variograms showed higher precision than the available method. The method enables regional scale stressors quantification by filling spatial data gaps integrating temporal information in data scarce regions. In chapter 4, responses of the assumed climate-associated traits from six grouping features to 35 bioclimatic indices for five insect orders were compared, their potential for changing distribution pattern under future climate change was evaluated and the most influential climatic aspects were identified (chapter 4). Traits of temperature preference grouping feature and the insect order Ephemeroptera exhibited the strongest response to climate as well as the highest potential for changing distribution pattern, while seasonal radiation and moisture were the most influential climatic aspects that may drive a change in insect distribution pattern. The results contribute to the trait based freshwater monitoring and change prediction. In chapter 5, the concentrations of 10 trace metals in the drinking water sources were predicted and were compared with guideline values. In more than 53% of the total area of Pakistan, inhabited by more than 74 million people, the drinking water was predicted to be at risk from multiple trace metal contamination. The results inform freshwater management by identifying potential hot spots. The last chapter (6) synthesizes the results and provides a comprehensive discussion on the four studies and on their relevance for freshwater resources conservation and management
Evaluation of Spatial interpolation techniques for mapping climate variables with low sample density: a case study using a new gridded dataset of Bangladesh
Get PDFDissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.This study explores and analyses the impact of sample density on the performances
of the spatial interpolation techniques. It evaluates the performances of two
alternative deterministic techniques – Thin Plate Spline and Inverse Distance
Weighting, and two alternative stochastic techniques – Ordinary Kriging and
Universal Kriging; to interpolate two climate indices - Annual Total Precipitation in
Wet Days and the Yearly Maximum Value of the Daily Maximum Temperature, in
a low sample density region - Bangladesh, for 60 years – 1948 to 2007. It implies
the approach of Spatially Shifted Years to create mean variograms with respect to
the low sample density. Seven different performance measurements - Mean
Absolute Error, Root Mean Square Errors, Systematic Root Mean Square Errors,
Unsystematic Root Mean Square Errors, Index of Agreement, Coefficient of
Variation of Prediction and Confidence of Prediction, have been applied to evaluate
the performance of the spatial interpolation techniques. The resulted performance
measurements indicate that for most of the years the Universal Kriging method
performs better to interpolate total precipitation, and the Ordinary Kriging method
performs better to interpolate the maximum temperature. Though the difference
surfaces indicate a very little difference in the estimating ability of the four spatial
interpolation techniques, the residual plots refer to the differences in the
interpolated surfaces by different techniques in terms of their over and under
estimation. The results also indicate that the Inverse Distance Weighting method
performs better for both indices, when the sample density is too low, but the
performance is questioned by the inclusion of measurement errors in the interpolated surfaces. All the error measurements show a decreasing trend with the
increasing sample density, and the index of agreement and confidence of prediction
show an increasing trend over years. Finally, the strong correlation between the
Sample Coefficient of Variation and the performance measurements, implies that
the more representative the samples are of the climate phenomenon, the more
improved are the performances of the spatial interpolation techniques. The
correlation between the sample coefficient of variation and the number of samples
implies that the high representativity of the sample is attainable with an increased
sample density
Cyclone Sidr Impacts on the Sundarbans Floristic Diversity
No full textThe Sundarbans - the world’s largest single block of tidal halophytic mangrove forest situated at the southwest of Bangladesh, plays a vital role in maintaining environmental sustainability of the country and the world in general. This study identified and quantified the extent and degree of damage caused to the floristic diversity of the Sundarbans by the tropical cyclone Sidr in 15 November 2007. It also quantified the extent and rate of the post-cyclone regeneration in the damaged flora. Unsupervised classification - ISODATA and the normalized difference vegetation index (NDVI) were carried out over a temporal series of 2007-2010 on four Landsat 7 Enhanced Thematic Mapper Plus (ETM +) images for the months of February. Land change analysis from the classification results show that three important floristic taxa - Heritiera fomes (Sundari), Excoecaria agallocha (Gewa) and Sonneratia apetala (Kewra) have been significantly affected by the cyclone. NDVI analysis indicates that 45% area of the Bangladesh’s part of the Sundarbans (approximately 2500 sq.km) was affected due to the cyclone action. Results further indicated that the average rate of post-cyclone floristic growth in 2009-2010 is four times higher than the average rate in 2008-2009. Thus the study identified a temporary loss of the diversity (in terms of relative abundance) in the affected three floristic taxa of the Sundarbans after that severe exogenous perturbation; which took three years to regenerate. Moreover, it showed the higher efficiency and promptness of remote sensing techniques in similar cases than the ground data based studies.</p
Spatially shifting temporal points: estimating pooled within-time series variograms for scarce hydrological data
Get PDFBhowmik, A. K., & Cabral, P. (2015). Spatially shifting temporal points: estimating pooled within-time series variograms for scarce hydrological data. Hydrology and Earth System Sciences: discussions, 2015(12), 2243-2265. https://doi.org/10.5194/hessd-12-2243-2015publishersversionpublishe
Digital elevation model (DEM), surveyed stream network (SSN), mask and stream sampling points (SSP)
No full textRepresentativeness impacts on accuracy and precision of climate spatial interpolation in data-scarce regions
No full textBhowmik, A. K., & Costa, A. C. (2015). Representativeness impacts on accuracy and precision of climate spatial interpolation in data-scarce regions. Meteorological Applications, 22(3), 368-377. https://doi.org/10.1002/met.1463Data scarcity is a major scientific challenge for accuracy and precision of the spatial interpolation of climatic fields, especially in climate-stressed developing countries. Methodologies have been suggested for coping with data scarcity but data have rarely been checked for their representativeness of corresponding climatic fields. This study proved that satisfactory accuracy and precision can be ensured in spatial interpolation if data are satisfactorily representative of corresponding climatic fields despite their scarcity. The influence of number and representativeness of climate data on accuracy and precision of their spatial interpolation has been investigated and compared. Two precipitation and temperature indices were computed for a long time series in Bangladesh, which is a data-scarce region. The representativeness was quantified by dispersion in the data and the accuracy and precision of spatial interpolation were computed by four commonly used error statistics derived through cross-validation. The precipitation data showed very little and sometimes null representativeness whereas the temperature data showed very high representativeness of the corresponding fields. Consequently, precipitation data denoted scarcity but the temperature data denoted sufficiency regarding the required number of data for ensuring satisfactory accuracy and precision for spatial interpolation. It was also found that with the available data, accurate and precise precipitation surfaces can be produced only for representative synoptic spatial scales whereas such temperature surfaces can be generated for the regional scale of Bangladesh. It is highly recommended that the rain-gauge network of Bangladesh be increased or redistributed for computing representative regional precipitation surfaces.publishersversionpublishe
A geostatistical approach to the seasonal precipitation effect on Boro rice production in Bangladesh
Get PDFBhowmik, A. K., & Costa, A. C. (2012). A geostatistical approach to the seasonal precipitation effect on Boro rice production in Bangladesh. International Journal of Geosciences, 3(3), 443-462. DOI: 10.4236/ijg.2012.33048Geographical assessments on the relationship between climate variability and crop production are important for planning adaptation programs to climate change impacts on Asian rice production. This paper analyses the seasonal precipitation consequences to irrigated crop yields, in opposition to the idea that irrigated crop yields are not affected by precipitation changes. Geostatistical methods are applied to assess changes in the patterns of seasonal precipitation and corresponding changes in the Boro crop production in Bangladesh. Surfaces depicting changes in the monsoon, non-monsoon and total precipitation from 2006 to 2007, and changes in three varieties of Boro crop yield and Total Boro yield from 2006-2007 to 2007-2008 crop years are generated through Splines, Inverse Distance Weighting and Ordinary Kriging methods. Performance evaluation of these models is also performed. The relationships between the surfaces of different precipitation seasons and the surfaces of different Boro yield seasons are then assessed. The results show that there is a significant correlation between seasonal precipitation changes and Boro yield changes with notable correlation coefficients and similarity in the patterns. A significant conformity of the high precipitation zones to the high Boro yielding zones is also depicted.publishersversionpublishe
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