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Assessing climate-induced agricultural vulnerable coastal communities of Bangladesh using machine learning techniques

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Date
2020
Author
Jakariya, Md.
Alam, Sajadul
Rahman, Abir
Ahmed, Silvia
Elahi, Lutfe
Shabbir Khan, Abu Mohammad
Saad, Saman
Tamim, H.M.
Ishtiak, Taoseef
Mohammad Sayem, Sheikh
Shawkat Ali, Mirza
Akter, Dilruba
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Abstract
The agricultural arena in the coastal regions of South-East Asian countries is experiencing the mounting pressures of the adverse effects of climate change. Controlling and predicting climatic factors are difficult and require expensive solutions. The study focuses on identifying issues other than climatic factors using the Livelihood Vulnerability Index (LVI) to measure agricultural vulnerability. Factors such as monthly savings of the farmers, income opportunities, damage to cultivable lands, and water availability had significant impacts on increasing community vulnerability with regards to agricultural practice. The study also identified the need for assessing vulnerability after certain intervals, specifically owing to the dynamic nature of the coastal region where the factors were found to vary among the different study areas. The development of a climate-resilient livelihood vulnerability assessment tool to detect the most significant factors to assess agricultural vulnerability was done using machine learning (ML) techniques. The ML techniques identified nine significant factors out of 21 based on the minimum level of standard deviation (0.03). A practical application of the outcome of the study was the development of a mobile application. Custom REST APIs (application programming interface) were developed on the backend to seamlessly sync the app to a server, thus ensuring the acquisition of future data without much effort and resources. The paper provides a methodology for a unique vulnerability assessment technique using a mobile application, which can be used for the planning and management of resources by different stakeholders in a sustainable way
Palabras clave
Coastal livelihood; Livelihood vulnerability index; Geographic information system; Regression analysis; Mobile application
URI
http://hdl.handle.net/20.500.12010/11545
Link to resource
https://doi.org/10.1016/j.scitotenv.2020.140255
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Carrera 4 # 22-61 Teléfono: (+57 1) 242 7030 - 018000111022 Fax: (+57 1) 561 2107 Bogotá D.C., Colombia

Fundación Universitaria de Bogotá Jorge Tadeo Lozano | Vigilada Mineducación

Institución de educación superior privada, de utilidad común, sin ánimo de lucro y su carácter académico es el de Universidad.

Reconocimiento personería jurídica: Resolución 2613 del 14 de agosto de 1959 Minjusticia.

Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional.

 

Términos y condiciones | Políticas