联合星载光学和SAR影像的漳江口红树林与互花米草遥感监测

doi:10.11978/2019063

Abstract

Abstract:

Mangroves are an important type of coastal wetlands with ecological, environmental, economic, and cultural values. Spartina alterniflora is an invasive alien plant, threatening mangroves in China. The competition between Spartina alterniflora and mangroves is an important ecological issue along the southeast coast of China. Accurate monitoring of Spartina alterniflora and mangroves with remote sensing is of great significance for scientific protection of mangrove ecosystems. We propose a new method to monitor Spartina alterniflora and mangroves, integrating Sentinel-1 SAR and Sentinel-2 optical imagery. The Yunxiao National Nature Reserve of Mangroves, located in Zhangjiang Estuary, Fujian, China, is chosen as the study area. We select one Sentinel-2A image at low tide in 2016, 2017 and 2018 to obtain the spectral and texture information of vegetation and other objects. The new method comprises of three steps: 1) use rules related to NDVI, EVI, LSWI, and DEM to get the potential masks of Spartina alterniflora and mangroves; 2) use random forest classification method to distinguish Spartina alterniflora and mangroves further; and 3) use all Sentinel-1 A/B images in that year to get the estuarine yearlong seawater body, and use the criterion interaction with sea water to refine the detected Spartina alterniflora and mangroves. The random forest classifier is found suitable for mapping wetlands with overall accuracy of 98.53%, 96.52% and 98.71%, and Kappa coefficients of 0.980, 0.952 and 0.978 in 2016, 2017 and 2018, respectively. The total areas of the detected Spartina alterniflora and mangroves in the study region are 109.23 and 56.85 hm ²in 2016, 124.00 and 59.88 hm² in 2017, and 142.39 and 58.61 hm² in 2018, respectively, consistent with previous research results in terms of spatial distribution and magnitude of the area.

Key words: mangroves, Spartina alterniflora, remote sensing, hierarchical classification, random forest classification, Zhangjiang Estuary

CLC Number:

P735.52

Di DONG, Jisheng ZENG, Zheng WEI, Jinhui YAN. Integrating spaceborne optical and SAR imagery for monitoring mangroves and Spartina alterniflora in Zhangjiang Estuary[J].Journal of Tropical Oceanography, 2020, 39(2): 107-117.

Figures/Tables 11

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类别	红树林	互花米草	水	光滩	其他植被
2016年与2017年	40 (10.13)	38 (2.04)	12 (21.25)	22 (5.58)	17 (0.47)
2018年	40 (10.13)	55 (2.70)	12 (21.25)	22 (5.58)	22 (0.66)

年度	类别	红树林	互花米草	光滩	水	其他植被	制图精度/%	用户精度/%
2016年	红树林	418	0	0	0	0	100.00	100.00
	互花米草	0	99	3	0	0	97.06	100.00
	光滩	0	0	422	2	8	97.69	98.60
	水	0	0	0	318	1	99.69	98.76
	其他植被	0	0	3	2	17	77.27	65.39
2017年	红树林	418	0	0	0	0	99.76	99.76
	互花米草	0	90	1	9	2	94.74	94.74
	光滩	0	0	402	19	6	99.26	99.26
	水	0	5	0	319	0	91.93	91.93
	其他植被	1	0	2	0	19	70.37	70.37
2018年	红树林	486	0	0	0	1	99.80	100.00
	互花米草	0	76	5	0	0	93.83	98.70
	光滩	0	0	18	0	0	100.00	60.00
	水	0	0	0	628	2	99.68	100.00
	其他植被	0	1	7	0	18	69.23	85.71

类别	2014年	2015年	2016年	2017年	2018年
红树林	59.91 (李屹等, 2017)	62.19 (Chen et al, 2017)	60 (陈远丽等, 2019); 56.85 (本算法)	59.88 (本算法)	58.61 (本算法)
互花米草	—	116.11 (Liu et al, 2017)	117 (陈远丽等, 2019); 109.23 (本算法)	124.00 (本算法)	142.39 (本算法)

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Integrating spaceborne optical and SAR imagery for monitoring mangroves and Spartina alterniflora in Zhangjiang Estuary

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	2016年	2017年	2018年
总体精度/%	98.53	96.52	98.71
Kappa系数	0.980	0.952	0.978