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Remote Sensing for Land & Resources    2018, Vol. 30 Issue (4) : 176-181     DOI: 10.6046/gtzyyg.2018.04.26
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Information extraction of the Ebinur Lake artemia based on object - oriented method
Wei LI1,2, Weinan LIU1, Yueping JIA1, Hongyang LIU1, Yong TANG1,2()
1. Institute of Marine Science and Technology and the Environment, Dalian Ocean University, Dalian 116023, China
2. The Nearshore Environmental Science and Technology Key Laboratory of Liaoning Province Colleges and Universities, Dalian 116023, China
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Abstract  

With the Ebinur Lake as the research area and the ZY-3 multi-spectral image as the data source, the authors preprocessed the data by such means as ortho-rectification, radiometric calibration and atmospheric correction. The authors analyzed the spectral characteristics of different water bodies, found interpretation signs for artemia information extraction, and built the oriented-object artemia information extraction model by the spectral, texture and shape information. The classification results were validated using the confusion matrix, with the overall classification accuracy being 91.74% and Kappa coefficient being 0.89. In addition, classification accuracy between object-oriented method and pixel based method was analyzed and compared for the artemia water of different densities. The classification accuracies of object-oriented method for high density, medium density and potential regions were 95.08%, 92.30% and 91.26%, respectively, whereas those of pixel based method were 90.16%, 87.18% and 86.40%, respectively. The results show that the object-oriented method is more effective than the pixel based method. The object-oriented method greatly avoids the phenomenon of “salt and pepper” and can distinguish the artemia densities. The study can provide the effective method for monitoring the distribution and intensity of artemia and has great significance for scientific and reasonable artemia fishing.
Keywords object-oriented      artemia and artemia cyst      multi-scale segmentation      interpretation signs     
:  X87P96  
Corresponding Authors: Yong TANG     E-mail: tang@dlou.edu.cn
Issue Date: 07 December 2018
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Wei LI
Weinan LIU
Yueping JIA
Hongyang LIU
Yong TANG
Cite this article:   
Wei LI,Weinan LIU,Yueping JIA, et al. Information extraction of the Ebinur Lake artemia based on object - oriented method[J]. Remote Sensing for Land & Resources, 2018, 30(4): 176-181.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.04.26     OR     https://www.gtzyyg.com/EN/Y2018/V30/I4/176
Fig.1  ZY-3 image with true color composition in Ebinur Lake
载荷 波段 光谱范
围/nm		 空间分辨
率/m		 幅宽/
km		 重访周
期/d
多光谱相机 B1 450~520 5.8 51 5
B2 520~590
B3 630~690
B4 770~890
Tab.1  Multi-spectral parameters of ZY-3 payload
Fig.2  Spectral characteristic curves of different water
Fig.3  Histogram of RIartemia
对象层
(尺度)		 父对象 子对象 阈值参数
第1层
(40)		 — 湖区 NDWI≥0.1
浅滩 NDWI<0.1
第2层
(10)		 湖区 高亮度水体 Br≥0.2
高密度覆盖区域 RIartemia≥1,L/W>4.5
中密度覆盖区域 1>RIartemia≥0.93,L/W>4.5
潜在区域 0.93>RIartemia≥0.9
Tab.2  Classification rules
Fig.4  Information extraction results by object-oriented method
Fig.5  Information extraction results by pixel based method
预测类别 参考类别
高密度覆盖区域 中密度覆盖区域 潜在区域 湖区 浅滩 总数 用户精度/%
高密度覆盖区域 58 2 0 0 0 60 96.67
中密度覆盖区域 3 72 1 0 0 76 94.74
潜在区域 0 4 94 6 3 107 87.85
湖区 0 0 5 77 1 83 92.77
浅滩 0 0 3 2 32 37 86.49
总数 61 78 103 85 36 363
生产者精度/% 95.08 92.30 91.26 90.59 88.89
Tab.3  Object-oriented classification accuracy
预测类别 参考类别
高密度覆盖区域 中密度覆盖区域 潜在区域 湖区 浅滩 总数 用户精度/%
高密度覆盖区域 55 4 0 1 0 60 91.67
中密度覆盖区域 5 68 5 0 0 78 87.18
潜在区域 1 3 89 11 5 109 81.68
湖区 0 0 7 68 0 75 90.67
浅滩 0 3 2 5 31 41 75.61
总数 61 78 103 85 36 363
生产者精度/% 90.16 87.18 86.40 80 86.11
Tab.4  Pixel based classification accuracy
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