Harnessing Machine Learning to Estimate Aquaculture’s Contributions to the Economy of Southwest Bangladesh - World Aquaculture Singapore 2022

Aug 3, 2026

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The presentation outlines a data-driven approach to quantify how aquaculture supports the regional economy in Southwest Bangladesh. It combines field surveys across multiple districts with machine learning applied to remotely sensed imagery to estimate total aquafarm area and derive productivity, revenues, margins, feed use, and employment intensity. Per-hectare survey averages are scaled by estimated total area to calculate production quantity, production value, farm income, feed demand, and job creation. The framework can also extend to upstream and downstream value-chain impacts.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages15

Reading Time38 min

AccessFree to download

Project Overview

Zone of Interest

Methodology

Machine Learning Framework

Similar Estimates of Farm Area from Machine Learning

HARNESSING MACHINELEARNING TOESTIMATEAQUACULTURE’S CONTRIBUTIONS TO THEECONOMY OFSOUTHWEST BANGLADESH Ben Belton(Michigan State University),M.Mahfujul Haque(Bangladesh Agricultural University)Hazrat Ali(WorldFish),Amir Pouyan Nejadhashemi(Michigan State University),RicardoHernandez,(CIAT),Khondker Murshed-e-Jahan,(WorldFish),Hannah Ferriby(Michigan StateUniversity) World Aquaculture Singapore 2022December 1,2022Photo:Google Earth MICHIGARSTATE WorldFish Alliance CIAT BRovoesaity er MISSISSIPPI STATE UNIVERSITYMGLOBAL CENTER FORAQUATIC FOOD SECURITY PROJECT OVERVIEW ·"Harnessing Machine Learning to Estimate AquacultureProduction and Value Chain Performance in Bangladesh” ·Worked in seven main aquaculture districts in SW Bangladesh in2020-21 ·Component 1 Survey a representative sample of 721 farmers,329 fishtraders,79 feed suppliers,80 hatcheries ·Component 2 Use machine learning to extract and analyze data onaquaculture from remotely sensed images; ·Combine with survey data to estimate aquaculture's contributions to theregional economy # ZONE OF INTEREST Jashore Satkhira Khulna Bagerhat Gopalganj Barisal Bhola USAIDMISSISSIPPI STATE UNIVERSITYTWFROM THE AMERICAN PEOPLEMICHIGAR STATECIATGLOBAL CENTER FORAQUATIC FOOD SECURITY # METHODOLOGY ·Estimated total aquafarm area in 7 districts of S Bangladesh fromremote sensed images using machine learning. ·From survey,calculated average rates of:Farm productivity (t/ha);Gross revenue (farmgate value +own consumed&gifted value);Gross margins (gross revenue -production costs);Feed use(t/ha);Employment (FTEs/ha) ·Multiplied per ha average by total area to estimate total:Quantityof production,Value of production,Farm income,Amount of feedused,Jobs created. ·Can use same technique to estimate total production of micronutrients &number of people employed upstream and indownstream value chains in the same districts Alliance CIAT # MACHINE LEARNING FRAMEWORK USAIDMISSISSIPPI STATE UNIVERSITYFROM THE AMERICAN PEOPLEMICHIGARSTATEWorldFishCIATGLOBAL CENTER FORAQUATIC FOOD SECURITY Alliance USAID FROM THE AMERICAN PEOPLE MICHIGARSTATE WorldFish Alliance CIAT MISSISSIPPI STATE UNIVERSITYTWGLOBAL CENTER FORAQUATIC FOOD SECURITY # SIMILAR ESTIMATES OF FARM AREA FROMMACHINE LEARNING &DOF quaculture area)000 ha) 300 279276 250■FIL estimated area of aquaculture farms ■DOF 2020 area of ponds +shrimp prawn farms200150100 7480 7265 7273503834612 118650 SatkhiraUSAID Alliance MISSISSIPPI STATE UNIVERSITYTw MICHIGARSTATE GLOBAL CENTER FOR CIAT AQUATIC FOOD SECURITY FROM THE AMERICAN PEOPLE WorldFish BRovoesaity # SMALL AVERAGE FARM SIZE All districts Satkhira Khulna Jashore Gopalganj Bhola Barisal Bagerhat Average area of aquaculture waterbodies per farm(ha) Alliance BRovoesaity MISSISSIPPI STATE UNIVERSITY GLOBAL CENTER FOR AQUATIC FOOD SECURITY Number of aquaculture farms ESTIMATED NUMBER OF FARMS=547,000 ),000) BarisalBholaUSAIDMISSISSIPPI STATE UNIVERSITYTwFROM THE AMERICAN PEOPLEMICHIGARSTATEWorldFishCIATGLOBAL CENTER FOR Alliance BRovoesaity AQUATIC FOOD SECURITY TOTAL VALUE OF PRODUCTION=1.45 BILLION USDTOTAL VALUE OF FARM PROFIT=0.67 BILLION USD USAIDMISSISSIPPI STATE UNIVERSITYTWFROM THE AMERICAN PEOPLEMICHIGARSTATEGLOBAL CENTER FORBRovoesaityAQUATIC FOOD SECURITY Alliance

FAQs

Which data sources are used to estimate aquaculture’s economic contributions?

The approach uses a representative survey of farmers, fish traders, feed suppliers, and hatcheries, combined with machine learning analysis of remotely sensed images to estimate aquafarm area.

How are survey results converted into estimates of total regional outcomes?

Average per-hectare rates from the survey—such as productivity, revenue, margins, feed use, and employment—are multiplied by the total estimated aquafarm area to compute quantities, values, income, feed use, and jobs created.

Can the technique assess impacts beyond farm-level production?

Yes. The same estimation concept can be used to infer upstream and downstream value-chain outcomes, including micronutrient production and employment for additional population segments in the same districts.

Aug 3, 2026

Upload by Jiven