Harnessing Machine Learning to Estimate Aquaculture’s Contributions to The Economy of Southwest Bangladesh

The presentation detailed the use of machine learning techniques to extract information from freely available satellite images and estimate the area of waterbodies used for aquaculture in seven districts in southern Bangladesh, one of country’s most important aquaculture zones producing fish for dom...

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Bibliographic Details
Main Authors: Belton, Ben, Haque, Mohammad Mahfujul, Ali, Hazrat, Nejadhashemi, Amir Pouyan, Hernández, Ricardo, Khondker, Murshed-E-Jahan, Ferriby, Hannah
Format: Ponencia
Language:Inglés
Published: WorldFish 2022
Subjects:
Online Access:https://hdl.handle.net/10568/127061
Description
Summary:The presentation detailed the use of machine learning techniques to extract information from freely available satellite images and estimate the area of waterbodies used for aquaculture in seven districts in southern Bangladesh, one of country’s most important aquaculture zones producing fish for domestic markets and crustaceans for export. The research combined machine learning derived estimates of aquaculture farm area per district with data from statistically representative farm surveys to estimate farm size, productivity, and total output, economic value of production, on-farm employment generation by gender, and demand for formulated and non-formulated feeds.