Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm

In this study, the harbor aquaculture area tested is Zhanjiang coast, and for the remote sensing data, we use images from the GaoFen-1 satellite. In order to achieve a superior extraction performance, we propose the use of an integration-enhanced gradient descent (IEGD) algorithm. The key idea of th...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yafeng Zhong, Siyuan Liao, Guo Yu, Dongyang Fu, Haoen Huang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	integration-enhanced gradient descent algorithm harbor aquaculture area extraction GaoFen-1 Science Q
Acceso en línea:	https://doaj.org/article/9c923b7a670c4754b310bc34758f4dae
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:9c923b7a670c4754b310bc34758f4dae
record_format	dspace
spelling	oai:doaj.org-article:9c923b7a670c4754b310bc34758f4dae2021-11-25T18:54:11ZHarbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm10.3390/rs132245542072-4292https://doaj.org/article/9c923b7a670c4754b310bc34758f4dae2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4554https://doaj.org/toc/2072-4292In this study, the harbor aquaculture area tested is Zhanjiang coast, and for the remote sensing data, we use images from the GaoFen-1 satellite. In order to achieve a superior extraction performance, we propose the use of an integration-enhanced gradient descent (IEGD) algorithm. The key idea of this algorithm is to add an integration gradient term on the basis of the gradient descent (GD) algorithm to obtain high-precision extraction of the harbor aquaculture area. To evaluate the extraction performance of the proposed IEGD algorithm, comparative experiments were performed using three supervised classification methods: the neural network method, the support vector machine method, and the maximum likelihood method. From the results extracted, we found that the overall accuracy and F-score of the proposed IEGD algorithm for the overall performance were <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.9538</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.9541</mn></mrow></semantics></math></inline-formula>, meaning that the IEGD algorithm outperformed the three comparison algorithms. Both the visualized and quantitative results demonstrate the high precision of the proposed IEGD algorithm aided with the CEM scheme for the harbor aquaculture area extraction. These results confirm the effectiveness and practicality of the proposed IEGD algorithm in harbor aquaculture area extraction from GF-1 satellite data. Added to that, the proposed IEGD algorithm can improve the extraction accuracy of large-scale images and be employed for the extraction of various aquaculture areas. Given that the IEGD algorithm is a type of supervised classification algorithm, it relies heavily on the spectral feature information of the aquaculture object. For this reason, if the spectral feature information of the region of interest is not selected properly, the extraction performance of the overall aquaculture area will be extremely reduced.Yafeng ZhongSiyuan LiaoGuo YuDongyang FuHaoen HuangMDPI AGarticleintegration-enhanced gradient descent algorithmharbor aquaculture area extractionGaoFen-1ScienceQENRemote Sensing, Vol 13, Iss 4554, p 4554 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	integration-enhanced gradient descent algorithm harbor aquaculture area extraction GaoFen-1 Science Q
spellingShingle	integration-enhanced gradient descent algorithm harbor aquaculture area extraction GaoFen-1 Science Q Yafeng Zhong Siyuan Liao Guo Yu Dongyang Fu Haoen Huang Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm
description	In this study, the harbor aquaculture area tested is Zhanjiang coast, and for the remote sensing data, we use images from the GaoFen-1 satellite. In order to achieve a superior extraction performance, we propose the use of an integration-enhanced gradient descent (IEGD) algorithm. The key idea of this algorithm is to add an integration gradient term on the basis of the gradient descent (GD) algorithm to obtain high-precision extraction of the harbor aquaculture area. To evaluate the extraction performance of the proposed IEGD algorithm, comparative experiments were performed using three supervised classification methods: the neural network method, the support vector machine method, and the maximum likelihood method. From the results extracted, we found that the overall accuracy and F-score of the proposed IEGD algorithm for the overall performance were <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.9538</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.9541</mn></mrow></semantics></math></inline-formula>, meaning that the IEGD algorithm outperformed the three comparison algorithms. Both the visualized and quantitative results demonstrate the high precision of the proposed IEGD algorithm aided with the CEM scheme for the harbor aquaculture area extraction. These results confirm the effectiveness and practicality of the proposed IEGD algorithm in harbor aquaculture area extraction from GF-1 satellite data. Added to that, the proposed IEGD algorithm can improve the extraction accuracy of large-scale images and be employed for the extraction of various aquaculture areas. Given that the IEGD algorithm is a type of supervised classification algorithm, it relies heavily on the spectral feature information of the aquaculture object. For this reason, if the spectral feature information of the region of interest is not selected properly, the extraction performance of the overall aquaculture area will be extremely reduced.
format	article
author	Yafeng Zhong Siyuan Liao Guo Yu Dongyang Fu Haoen Huang
author_facet	Yafeng Zhong Siyuan Liao Guo Yu Dongyang Fu Haoen Huang
author_sort	Yafeng Zhong
title	Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm
title_short	Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm
title_full	Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm
title_fullStr	Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm
title_full_unstemmed	Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm
title_sort	harbor aquaculture area extraction aided with an integration-enhanced gradient descent algorithm
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9c923b7a670c4754b310bc34758f4dae
work_keys_str_mv	AT yafengzhong harboraquacultureareaextractionaidedwithanintegrationenhancedgradientdescentalgorithm AT siyuanliao harboraquacultureareaextractionaidedwithanintegrationenhancedgradientdescentalgorithm AT guoyu harboraquacultureareaextractionaidedwithanintegrationenhancedgradientdescentalgorithm AT dongyangfu harboraquacultureareaextractionaidedwithanintegrationenhancedgradientdescentalgorithm AT haoenhuang harboraquacultureareaextractionaidedwithanintegrationenhancedgradientdescentalgorithm
_version_	1718410606052114432

Harbor Aquaculture Area Extraction Aided with an Integration-Enhanced Gradient Descent Algorithm

Ejemplares similares