Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine

Information on the spatial distribution of aquaculture ponds, especially the inland brackish aquaculture, is crucial for effective and sustainable aquaculture management. Google Earth Engine (GEE) has been utilized to quickly map aquaculture ponds in different parts of the world, but the application...

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Main Authors: Tew, Yi Lin, Tan, Mou Leong, Narimah Samat,, Chan, Ngai Weng, Mohd Amirul Mahamud,, Muhammad Azizan Sabjan,, Lee, Lai Kuan, See, Kok Fong, Wee, Seow Ta
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2022
Online Access:http://journalarticle.ukm.my/19130/1/4.pdf
http://journalarticle.ukm.my/19130/
https://www.ukm.my/jsm/malay_journals/jilid51bil2_2022/KandunganJilid51Bil2_2022.html
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spelling my-ukm.journal.191302022-08-01T01:44:39Z http://journalarticle.ukm.my/19130/ Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine Tew, Yi Lin Tan, Mou Leong Narimah Samat, Chan, Ngai Weng Mohd Amirul Mahamud, Muhammad Azizan Sabjan, Lee, Lai Kuan See, Kok Fong Wee, Seow Ta Information on the spatial distribution of aquaculture ponds, especially the inland brackish aquaculture, is crucial for effective and sustainable aquaculture management. Google Earth Engine (GEE) has been utilized to quickly map aquaculture ponds in different parts of the world, but the application is still limited in tropical regions. Selection of an optimal water index is essential to accurately map the aquaculture ponds from the Landsat 8 satellite images that are available in GEE. This study aims to evaluate the capability of three different water indices, namely Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI) and Automated Water Extraction Index (AWEI), in mapping of the aquaculture ponds in Sungai Udang, Pulau Pinang, Malaysia. The results show that MNDWI is the best index for aquaculture ponds extraction in Sungai Udang, with an accuracy of 81.87% and Kappa coefficient of 0.61. Meanwhile, the accuracy of NDWI and AWEI as compared to the digitized aquaculture ponds are 58.21 and 61.60%, and Kappa coefficient of 0.33 and 0.36, respectively. Then, MNDWI was applied to calculate the spatial changes of aquaculture ponds from 2014 to 2020. The result indicates that the area of aquaculture ponds has expanded by 26.16% since the past seven years. Penerbit Universiti Kebangsaan Malaysia 2022 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/19130/1/4.pdf Tew, Yi Lin and Tan, Mou Leong and Narimah Samat, and Chan, Ngai Weng and Mohd Amirul Mahamud, and Muhammad Azizan Sabjan, and Lee, Lai Kuan and See, Kok Fong and Wee, Seow Ta (2022) Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine. Sains Malaysiana, 51 (2). pp. 369-378. ISSN 0126-6039 https://www.ukm.my/jsm/malay_journals/jilid51bil2_2022/KandunganJilid51Bil2_2022.html
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Information on the spatial distribution of aquaculture ponds, especially the inland brackish aquaculture, is crucial for effective and sustainable aquaculture management. Google Earth Engine (GEE) has been utilized to quickly map aquaculture ponds in different parts of the world, but the application is still limited in tropical regions. Selection of an optimal water index is essential to accurately map the aquaculture ponds from the Landsat 8 satellite images that are available in GEE. This study aims to evaluate the capability of three different water indices, namely Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI) and Automated Water Extraction Index (AWEI), in mapping of the aquaculture ponds in Sungai Udang, Pulau Pinang, Malaysia. The results show that MNDWI is the best index for aquaculture ponds extraction in Sungai Udang, with an accuracy of 81.87% and Kappa coefficient of 0.61. Meanwhile, the accuracy of NDWI and AWEI as compared to the digitized aquaculture ponds are 58.21 and 61.60%, and Kappa coefficient of 0.33 and 0.36, respectively. Then, MNDWI was applied to calculate the spatial changes of aquaculture ponds from 2014 to 2020. The result indicates that the area of aquaculture ponds has expanded by 26.16% since the past seven years.
format Article
author Tew, Yi Lin
Tan, Mou Leong
Narimah Samat,
Chan, Ngai Weng
Mohd Amirul Mahamud,
Muhammad Azizan Sabjan,
Lee, Lai Kuan
See, Kok Fong
Wee, Seow Ta
spellingShingle Tew, Yi Lin
Tan, Mou Leong
Narimah Samat,
Chan, Ngai Weng
Mohd Amirul Mahamud,
Muhammad Azizan Sabjan,
Lee, Lai Kuan
See, Kok Fong
Wee, Seow Ta
Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine
author_facet Tew, Yi Lin
Tan, Mou Leong
Narimah Samat,
Chan, Ngai Weng
Mohd Amirul Mahamud,
Muhammad Azizan Sabjan,
Lee, Lai Kuan
See, Kok Fong
Wee, Seow Ta
author_sort Tew, Yi Lin
title Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine
title_short Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine
title_full Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine
title_fullStr Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine
title_full_unstemmed Comparison of three water indices for tropical aquaculture ponds extraction using Google Earth Engine
title_sort comparison of three water indices for tropical aquaculture ponds extraction using google earth engine
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2022
url http://journalarticle.ukm.my/19130/1/4.pdf
http://journalarticle.ukm.my/19130/
https://www.ukm.my/jsm/malay_journals/jilid51bil2_2022/KandunganJilid51Bil2_2022.html
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score 13.211869