Mapping Time-Space Brickfield Development Dynamics in Peri-Urban Area of Dhaka, Bangladesh

Due to the high demand for cheap construction materials, clay-made brick manufacturing has become a thriving industry in Bangladesh, with manufacturing kilns heavily concentrated in the peripheries of larger cities and towns. These manufacturing sites, known as brickfields, operate using centuries-old technologies which expel dust, ash, black smoke and other pollutants into the atmosphere. This in turn impacts the air quality of cities and their surroundings and may also have broader impacts on health, the environment, and potentially contribute to global climate change. Using remotely sensed Landsat imagery, this study identifies brickfield locations and areal expansion between 1990 and 2015 in Dhaka, and employs spatial statistics methods including quadrat analysis and Ripley’s K-function to analyze the spatial variation of brickfield locations. Finally, using nearest neighbor distance as density functions, the distance between brickfield locations and six major geographical features (i.e., urban, rural settlement, wetland, river, highway, and local road) were estimated to investigate the threat posed by the presence of such polluting brickfields nearby urban, infrastructures and other natural areas. Results show significant expansion of brickfields both in number and clusters between 1990 and 2015 with brickfields increasing in number from 247 to 917 (total growth rate 271%) across the Dhaka urban center. The results also reveal that brickfield locations are spatially clustered: 78% of brickfields are located on major riverbanks and 40% of the total are located in ecologically sensitive wetlands surrounding Dhaka. Additionally, the average distance from the brick manufacturing plant to the nearest urban area decreased from 1500 m to 500 m over the study period. This research highlights the increasing threats to the environment, human health, and the sustainability of the megacity Dhaka from brickfield expansion in the immediate peripheral areas of its urban center. Findings and methods presented in this study can facilitate data-driven decision making by government officials and city planners to formulate strategies for improved brick production technologies and decreased environmental impacts for this urban region in Bangladesh.

[1]  Alejandro Velázquez,et al.  Remote sensing and GIS-based regional geomorphological mapping—a tool for land use planning in developing countries , 2001 .

[2]  S M Qutubuddin,et al.  Ergonomic Evaluation of Tasks Performed by Workers in Manual Brick Kilns in Karnataka,India , 2013 .

[3]  Lelia Croitoru,et al.  Benefits and Costs of the Informal Sector: The Case of Brick Kilns in Bangladesh , 2012 .

[4]  J. Besag,et al.  Statistical Analysis of Spatial Point Patterns by Means of Distance Methods , 1976 .

[5]  Choyon Kumar Saha,et al.  Impact of brick kilning industry in peri-urban Bangladesh , 2016 .

[6]  Jun Wang,et al.  Satellite remote sensing of particulate matter and air quality assessment over global cities , 2006 .

[7]  Gholamali Shafabakhsh,et al.  GIS-based spatial analysis of urban traffic accidents: case study in Mashhad, Iran , 2017 .

[8]  Mohammadianmosammam Hassan,et al.  Examination of land use/land cover changes, urban growth dynamics, and environmental sustainability in Chittagong city, Bangladesh , 2016, Environment, Development and Sustainability.

[9]  Ijaz Hossain,et al.  Transition from traditional brick manufacturing to more sustainable practices , 2003 .

[10]  P. Haase Spatial pattern analysis in ecology based on Ripley's K-function: Introduction and methods of edge correction , 1995 .

[11]  Atsuyuki Okabe,et al.  The K-Function Method on a Network and Its Computational Implementation , 2010 .

[12]  P. Greig-Smith,et al.  The Use of Random and Contiguous Quadrats in the Study of the Structure of Plant Communities , 1952 .

[13]  A-Xing Zhu,et al.  Enabling point pattern analysis on spatial big data using cloud computing: optimizing and accelerating Ripley’s K function , 2016, Int. J. Geogr. Inf. Sci..

[14]  R. Lasco,et al.  Assessing Air Quality in Dhaka City , 2015 .

[15]  K. Badarinath,et al.  Spatial patterns in vegetation fires in the Indian region , 2008, Environmental monitoring and assessment.

[16]  Levente Juhasz,et al.  Cross-checking user activities in multiple geo-social media networks , 2018 .

[17]  Humberto Barrera-Jiménez Urban form, mobility and sustainability: A macroscopic prospective spatial analysis for road traffic safety planning in Medellin, Colombia , 2020 .

[18]  B. Das An evaluation of low back pain among female brick field workers of West Bengal, India , 2015, Environmental Health and Preventive Medicine.

[19]  Bandyopadhyay Bijetri Occupational Stress among Women Moulders : A Study in Manual Brick Manufacturing Industry of West Bengal , 2014 .

[20]  A. Gelfand,et al.  Spatial Point Patterns , 2010 .

[21]  Zia Wadud,et al.  Particulate pollution from brick kiln clusters in the Greater Dhaka region, Bangladesh , 2013, Air Quality, Atmosphere & Health.

[22]  A. Salam,et al.  Particulate black carbon and gaseous emission from brick kilns in Greater Dhaka region, Bangladesh , 2018, Air Quality, Atmosphere & Health.

[23]  D. Stoyan,et al.  Statistical Analysis and Modelling of Spatial Point Patterns , 2008 .

[24]  M. Baten,et al.  Carbon dioxide emission from brickfields around Bangladesh , 2015 .

[25]  J. Southworth,et al.  Analyzing Land Cover Change and Urban Growth Trajectories of the Mega-Urban Region of Dhaka Using Remotely Sensed Data and an Ensemble Classifier , 2017 .

[26]  English Only THE PEOPLE'S REPUBLIC OF BANGLADESH , 2006 .

[27]  P. Dixon,et al.  A new method to measure spatial association for ecological count data , 2002 .

[28]  Hartwig H. Hochmair,et al.  Where to catch ‘em all? – a geographic analysis of Pokémon Go locations , 2017, Geo spatial Inf. Sci..

[29]  R. W. Thomas,et al.  An introduction to quadrat analysis , 1977 .

[30]  Michael S. Rosenberg,et al.  Handbook of spatial point-pattern analysis in ecology , 2015, Int. J. Geogr. Inf. Sci..

[31]  Jalal Uddin Md. Shoaib,et al.  The Soils of Bangladesh , 2013 .

[32]  B. Ripley Tests of 'Randomness' for Spatial Point Patterns , 1979 .

[33]  B. Ripley The Second-Order Analysis of Stationary Point Processes , 1976 .

[34]  Marc Souris,et al.  Exploring spatial patterns and hotspots of diarrhea in Chiang Mai, Thailand , 2009, International journal of health geographics.

[35]  Michael G. Wing,et al.  Crime Mapping and Spatial Analysis in National Forests , 2006 .

[36]  Alice E. Milne,et al.  Spatial Analysis of Digital Imagery of Weeds in a Maize Crop , 2018, ISPRS Int. J. Geo Inf..

[37]  Pengpeng Xu,et al.  The modifiable areal unit problem in traffic safety: Basic issue, potential solutions and future research , 2016 .

[38]  Asaad Ahmed Nafees,et al.  Respiratory symptoms and illnesses among brick kiln workers: a cross sectional study from rural districts of Pakistan , 2012, BMC Public Health.

[39]  Marko Wagner,et al.  Spatial Pattern Analysis In Plant Ecology , 2016 .

[40]  Sarah McCaffrey,et al.  Social media approaches to modeling wildfire smoke dispersion: spatiotemporal and social scientific investigations , 2017 .

[41]  George L. W. Perry,et al.  A comparison of methods for the statistical analysis of spatial point patterns in plant ecology , 2006, Plant Ecology.

[42]  M. Rosetti,et al.  Spatial Distribution of Taenia solium Porcine Cysticercosis within a Rural Area of Mexico , 2008, PLoS neglected tropical diseases.

[43]  M. Charlton,et al.  Quantitative geography : perspectives on spatial data analysis by , 2001 .