Research on automatic extraction method for coastal aquaculture area using Landsat8 data

doi:10.6046/gtzyyg.2018.03.14

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Abstract

During coastal resource monitoring, it is an effective way to extract aquaculture region using remote sensing data, whereas the water color in coastal region is complexly influenced by the distribution difference of chlorophyll-a and total suspended sediment concentration. And it would be difficult to accurately extract the aquaculture region with complex background using traditional methods. In view of the above problem, the authors proposed an algorithm for automatic coastal aquaculture area extraction combined with spectral and spatial information of aquaculture. Firstly, orthogonal subspace projection-weighted constrained energy minization method (OWCEM) was used to enhance the information of coastal aquaculture area. Secondly, by using the spatial texture information of the coastal aquaculture area, standard deviation adaptive segmentation (SDAS) method was used to automatically extract the cultivation area. In order to verify the accuracy of the proposed algorithm, the authors selected Sanggou Bay in Shandong and Sanduao Bay in Fujian as test regions and conducted the area extraction using Landsat8 data. The experimental results show that the proposed method can rapidly and accurately identify the distribution of coastal aquaculture area in complex background color and can reach about 93% accuracy rate with a low missing rate. The method could provide a new and effective means for automatic extraction of offshore aquaculture area.

Keywords coastal aquaculture region extraction standard deviation adaptive segmentation(SDAS) complex background orthogonal subspace projection-weighted constrained energy minization(OWCEM)

TP751.1

Corresponding Authors: Fu CHEN E-mail: chenfu@radi.ac.cn

Issue Date: 10 September 2018

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	Yitian WU
	Fu CHEN
	Yong MA
	Jianbo LIU
	Xinpeng LI

Cite this article:

Yitian WU,Fu CHEN,Yong MA, et al. Research on automatic extraction method for coastal aquaculture area using Landsat8 data[J]. Remote Sensing for Land & Resources, 2018, 30(3): 96-105.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.03.14 OR https://www.gtzyyg.com/EN/Y2018/V30/I3/96

Fig.1 Sketch map for coverage of experimental areas

Fig.2 Different cultivation models of aquaculture areas

Fig.3 Flow char of extraction method(OWCEM-SDAS) for aquaculture areas

特征信息	特征指数			数学表达式
光谱特征	MNDWI			$MNDWI = (ban d 3 - ban d 6) / (ban d 3 + ban d 6)$
	AWEInsh(归一化)			$AWEInsh = 4 (ban d 3 - ban d 6) - (0.25 ban d 5 + 2.75 ban d 7) ban d 3 + ban d 5 + ban d 6 + ban d 7$
	AWEIsh(归一化)			$AWEIsh = ban d 2 + 2.5 ban d 3 - 1.5 (ban d 5 + ban d 6) - 0.25 ban d 7 ban d 2 + ban d 3 + ban d 5 + ban d 6 + ban d 7$
	CHL			$CHL = 8.48 ban d 4 / ban d 1$
	TSM			$TSM = 0.028 ban d 2 + 0.019 ban d 3 - 5.31 ban d 3 / ban d 2 + 0.537$
特征信息		特征指数	数学表达式
相关性特征		SAD	$SAD = co s - 1 (x T y ‖ x ‖ ‖ y ‖)$
		corr	$corr = x - x - T y - y - ‖ x - x - ‖ ‖ y - y - ‖$
		s	$s = ‖ x - y ‖$
		SID	$SID = D (x ‖ y) + D (y ‖ x)$		$D x ‖ y = ∑ l = 1 L p l ln p l / q l D y ‖ x = ∑ l = 1 L q l ln q l / p l$ $p l = x l / ∑ j = 1 L x j q l = y l / ∑ j = 1 L y j$

Tab.1 Feature indexes included in band expansion

Fig.4 Flow chart of OWCEM algorithm

Fig.5 Aquacultutre area extraction result in Sanggou Bay, Shandong

Fig.6 Aquacultutre area extraction result in Sanduao Bay, Fujian

Fig.7 Vertification samples of test regions distributed in reference images

Tab.2 Confusion matrix of aquaculture area extraction result in Sanggou Bay, Shandong

Tab.3 Confusion matrix of aquaculture area extraction result in Sanduao Bay, Fujian

Tab.4 comparison of extraction accuracy using obeject-oritented method and proposed method(%)

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