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Quantifying spatio-temporal variation in aquaculture production areas in Satkhira, Bangladesh using geospatial and social survey

Despite Bangladesh being one of the leading countries in aquaculture food production worldwide, there is a considerable lack of updated scientific information about aquaculture activities in remote sites, making it difficult to manage sustainably. This study explored the use of geospatial and field...

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Autores principales: Nujaira, Hafeza, Prasad, Kumar Arun, Kumar, Pankaj, Yunus, Ali P., Kharrazi, Ali, Gupta, L. N., Kurniawan, Tonni Agustiono, Sajjad, Haroon, Avtar, Ram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754591/
https://www.ncbi.nlm.nih.gov/pubmed/36520938
http://dx.doi.org/10.1371/journal.pone.0278042
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author Nujaira, Hafeza
Prasad, Kumar Arun
Kumar, Pankaj
Yunus, Ali P.
Kharrazi, Ali
Gupta, L. N.
Kurniawan, Tonni Agustiono
Sajjad, Haroon
Avtar, Ram
author_facet Nujaira, Hafeza
Prasad, Kumar Arun
Kumar, Pankaj
Yunus, Ali P.
Kharrazi, Ali
Gupta, L. N.
Kurniawan, Tonni Agustiono
Sajjad, Haroon
Avtar, Ram
author_sort Nujaira, Hafeza
collection PubMed
description Despite Bangladesh being one of the leading countries in aquaculture food production worldwide, there is a considerable lack of updated scientific information about aquaculture activities in remote sites, making it difficult to manage sustainably. This study explored the use of geospatial and field data to monitor spatio-temporal changes in aquaculture production sites in the Satkhira district from 2017–2019. We used Shuttle Radar Topographic Mission digital elevation model (SRTM DEM) to locate aquaculture ponds based on the terrain elevation and slope. Radar backscatter information from the Sentinel-1 satellite, and different water indices derived from Sentinel-2 were used to assess the spatio-temporal extents of aquaculture areas. An image segmentation algorithm was applied to detect aquaculture ponds based on backscattering intensity, size and shape characteristics. Our results show that the highest number of aquaculture ponds were observed in January, with a size of more than 30,000 ha. Object-based image classification of Sentinel-1 data showed an overall accuracy above 80%. The key factors responsible for the variation in aquaculture were investigated using field surveys. We noticed that despite a significant number of aquaculture ponds in the study area, shrimp production and export are decreasing because of a lack of infrastructure, poor governance, and lack of awareness in the local communities. The result of this study can provide in-depth information about aquaculture areas, which is vital for policymakers and environmental administrators for successful aquaculture management in Satkhira, Bangladesh and other countries with similar issues.
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spelling pubmed-97545912022-12-16 Quantifying spatio-temporal variation in aquaculture production areas in Satkhira, Bangladesh using geospatial and social survey Nujaira, Hafeza Prasad, Kumar Arun Kumar, Pankaj Yunus, Ali P. Kharrazi, Ali Gupta, L. N. Kurniawan, Tonni Agustiono Sajjad, Haroon Avtar, Ram PLoS One Research Article Despite Bangladesh being one of the leading countries in aquaculture food production worldwide, there is a considerable lack of updated scientific information about aquaculture activities in remote sites, making it difficult to manage sustainably. This study explored the use of geospatial and field data to monitor spatio-temporal changes in aquaculture production sites in the Satkhira district from 2017–2019. We used Shuttle Radar Topographic Mission digital elevation model (SRTM DEM) to locate aquaculture ponds based on the terrain elevation and slope. Radar backscatter information from the Sentinel-1 satellite, and different water indices derived from Sentinel-2 were used to assess the spatio-temporal extents of aquaculture areas. An image segmentation algorithm was applied to detect aquaculture ponds based on backscattering intensity, size and shape characteristics. Our results show that the highest number of aquaculture ponds were observed in January, with a size of more than 30,000 ha. Object-based image classification of Sentinel-1 data showed an overall accuracy above 80%. The key factors responsible for the variation in aquaculture were investigated using field surveys. We noticed that despite a significant number of aquaculture ponds in the study area, shrimp production and export are decreasing because of a lack of infrastructure, poor governance, and lack of awareness in the local communities. The result of this study can provide in-depth information about aquaculture areas, which is vital for policymakers and environmental administrators for successful aquaculture management in Satkhira, Bangladesh and other countries with similar issues. Public Library of Science 2022-12-15 /pmc/articles/PMC9754591/ /pubmed/36520938 http://dx.doi.org/10.1371/journal.pone.0278042 Text en © 2022 Nujaira et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Nujaira, Hafeza
Prasad, Kumar Arun
Kumar, Pankaj
Yunus, Ali P.
Kharrazi, Ali
Gupta, L. N.
Kurniawan, Tonni Agustiono
Sajjad, Haroon
Avtar, Ram
Quantifying spatio-temporal variation in aquaculture production areas in Satkhira, Bangladesh using geospatial and social survey
title Quantifying spatio-temporal variation in aquaculture production areas in Satkhira, Bangladesh using geospatial and social survey
title_full Quantifying spatio-temporal variation in aquaculture production areas in Satkhira, Bangladesh using geospatial and social survey
title_fullStr Quantifying spatio-temporal variation in aquaculture production areas in Satkhira, Bangladesh using geospatial and social survey
title_full_unstemmed Quantifying spatio-temporal variation in aquaculture production areas in Satkhira, Bangladesh using geospatial and social survey
title_short Quantifying spatio-temporal variation in aquaculture production areas in Satkhira, Bangladesh using geospatial and social survey
title_sort quantifying spatio-temporal variation in aquaculture production areas in satkhira, bangladesh using geospatial and social survey
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754591/
https://www.ncbi.nlm.nih.gov/pubmed/36520938
http://dx.doi.org/10.1371/journal.pone.0278042
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