气候变化领域集成服务门户(CCPortal): Remote sensing estimation of the biomass of floating Ulva prolifera and analysis of the main factors driving the interannual variability of the biomass in the Yellow Sea

CCPortal

DOI	10.1016/j.marpolbul.2019.01.037
	Remote sensing estimation of the biomass of floating Ulva prolifera and analysis of the main factors driving the interannual variability of the biomass in the Yellow Sea
	Xiao Y.; Zhang J.; Cui T.; Gong J.; Liu R.; Chen X.; Liang X.
发表日期	2019
ISSN	0025326X
起始页码	330
结束页码	340
卷号	140
英文摘要	Since 2007, green tide blooms with Ulva prolifera as the dominant species have occurred every summer in the Yellow Sea. Biomass is a critical parameter used to describe the severity of green tide blooms. In this study, we analyzed the relationships between several indices (normalized difference vegetation index (NDVI), floating algae index (FAI), ratio vegetation index (RVI), enhanced vegetation index (EVI), ocean surface algal bloom index (OSABI), Korea Ocean Satellite Center (KOSC) approach) and the biomass per unit area of Ulva prolifera by using the in situ measurements from a water tank experiment. EVI, NDVI, and FAI showed strong exponential relationships with Ulva prolifera biomass per unit area. In order to apply the relationships to satellite remote sensing data, the impacts of the atmosphere (different aerosol optical depth at 550 nm) and mixed pixels to the relationships were analyzed. The results show that atmosphere has little effect on the relationship between EVI and Ulva prolifera biomass per unit area with R2 = 0.94 and APD (the average percentage deviation) = 19.55% when EVI is calculated from Rrc (Rayleigh-corrected reflectance), and R2 = 0.95 and APD = 17.53% when EVI is calculated from Rtoa (top-of-atmosphere reflectance). Due to the low sensitivity to the atmosphere, the EVI relationship can be directly utilized in the top-of-atmosphere (TOA) reflectance without atmospheric correction. In addition, the EVI was slightly affected by mixed pixels with the APD only increased by ~10%. The EVI relationship was then applied to a long MODIS image time series to obtain the maximal total biomass of floating Ulva prolifera in the Yellow Sea from 2007 to 2016. The results showed that the maximum and minimum total biomass occurred in 2016 (~1.17 million tons) and 2012 (~0.074 million tons), respectively. The main factors that caused the inter-annual biomass variability were analyzed. The total amount of nutrients from Sheyang River which was the largest river on the northern coast of Jiangsu Province, and Porphyra cultivation in the Radial Sand Ridges of Jiangsu Province had both strong correlation with Ulva prolifera total biomass. © 2019 Elsevier Ltd
英文关键词	Atmosphere effect; Biomass; EVI; Ocean color; Remote sensing; Ulva prolifera
语种	英语
scopus关键词	Pixels; Reflection; Remote sensing; Vegetation; Water tanks; Enhanced vegetation index; Interannual variability; Normalized difference vegetation index; Ocean color; Ratio vegetation indices; Remote sensing estimations; Satellite remote sensing data; Ulva prolifera; Biomass; algal bloom; annual variation; atmosphere; biomass; in situ measurement; ocean color; pixel; remote sensing; vegetation index; aerosol; algal bloom; article; atmosphere; biomass; Korea; nonhuman; nutrient; optical depth; Porphyra; remote sensing; river; sea; seashore; time series analysis; vegetation; Yellow Sea; biomass; environmental monitoring; eutrophication; growth, development and aging; procedures; sea; season; South Korea; Ulva; China; Jiangsu; Jiangsu; Pacific Ocean; Sheyang Estuary; Yellow Sea; algae; Porphyra; Ulva prolifera; Biomass; Environmental Monitoring; Eutrophication; Oceans and Seas; Remote Sensing Technology; Republic of Korea; Seasons; Ulva
来源期刊	Marine Pollution Bulletin
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/150090
作者单位	First Institute of Oceangraphy, Ministry of Natural Resources, Qingdao, Shandong 266061, China; College of Information Science & Engineering, Ocean University of China, Qingdao, Shandong 266100, China
推荐引用方式 GB/T 7714	Xiao Y.,Zhang J.,Cui T.,et al. Remote sensing estimation of the biomass of floating Ulva prolifera and analysis of the main factors driving the interannual variability of the biomass in the Yellow Sea[J],2019,140.
APA	Xiao Y..,Zhang J..,Cui T..,Gong J..,Liu R..,...&Liang X..(2019).Remote sensing estimation of the biomass of floating Ulva prolifera and analysis of the main factors driving the interannual variability of the biomass in the Yellow Sea.Marine Pollution Bulletin,140.
MLA	Xiao Y.,et al."Remote sensing estimation of the biomass of floating Ulva prolifera and analysis of the main factors driving the interannual variability of the biomass in the Yellow Sea".Marine Pollution Bulletin 140(2019).