Record Details

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

CGSpace

View Archive Info
 
 
Field Value
 
Title Harnessing Machine Learning to Estimate Aquaculture’s Contributions to the Economy of Southwest Bangladesh
 
Creator Belton, Benjamin
Haque, Mohammad Mahfujul
Ali, Hazrat
Nejadhashemi, Amir Pouyan
Hernandez, Ricardo
Khondker, Murshed-e-Jahan
Ferriby, Hannah
 
Subject climate change
food systems
deltas
 
Description Abstract accepted for presentation at the Annual Meeting of the World Aquaculture Society held in Singapore on 29 November to 2 December 2022. 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.
 
Date 2022-12-01
2023-01-16T09:09:27Z
2023-01-16T09:09:27Z
 
Type Abstract
 
Identifier Belton, B., Haque, M. M., Ali, H., Nejadhashemi, A. P., Hernandez, R. A., Khondker, M. and Ferriby, H. 2022. Harnessing Machine Learning to Estimate Aquaculture’s Contributions to the Economy of Southwest Bangladesh. Paper abstract submitted to the World Aquaculture Society, Singapore, 1 December 2022
https://hdl.handle.net/10568/127166
 
Language en
 
Rights Other
Open Access
 
Format application/pdf