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Impact of Coastal Infrastructure on Ocean Colour Remote Sensing: a Case Study in Jiaozhou Bay, China

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Impact of Coastal Infrastructure on Ocean Colour Remote Sensing: a Case Study in Jiaozhou Bay, China remote sensing Communication Impact of Coastal Infrastructure on Ocean Colour Remote Sensing: A Case Study in Jiaozhou Bay, China Yuan Yuan 1,2,* , Isabel Jalón-Rojas 1,2 and Xiao Hua Wang 1,2 1 School of Science, The University of New South Wales, Canberra ACT 2600, Australia; [email protected] (I.J.-R.); [email protected] (X.H.W.) 2 The Sino-Australian Research Centre for Coastal Management, The University of New South Wales, Canberra ACT 2600, Australia * Correspondence: [email protected]; Tel.: +61-0416341127 Received: 15 March 2019; Accepted: 8 April 2019; Published: 19 April 2019 Abstract: Spatial and temporal ocean colour data are increasingly accessible through remote sensing, which is a key tool for evaluating coastal biogeochemical and physical processes, and for monitoring water quality. Coastal infrastructure such as cross-sea bridges may impact ocean colour remote sensing due to the different spectral characteristics of asphalt and the seawater surface. However, this potential impact is typically ignored during data post-processing. In this study, we use Jiaozhou Bay (East China) and its cross-bay bridge to examine the impact of coastal infrastructure on water-quality remote-sensing products, in particular on chlorophyll-a concentration and total suspended sediment. The values of these products in the bridge area were significantly different to those in the adjacent water. Analysis of the remote-sensing reflectance and application of the Normalised Difference Water Index demonstrate that this phenomenon is caused by contamination of the signal by bridge pixels. The Moderate Resolution Imaging Spectroradiometer (MODIS) products helped estimate the pixel scale that could be influenced by contamination. Furthermore, we found similar pixel contamination at Hangzhou Bay Bridge, suggesting that the impact of large coastal infrastructure on ocean colour data is common, and must therefore be considered in data post-processing. Keywords: coastal infrastructure; remote sensing; data quality; Jiaozhou Bay; GOCI; chlorophyll-a; total suspended sediment 1. Introduction Ocean colour measurements contribute significantly to coastal ecosystem restoration, monitoring of dredging and dumping, fisheries management and a wide variety of research on water quality and coastal biogeochemical and physical processes. Among the ocean colour variables available from remote-sensing data, chlorophyll-a concentration (chl-a), total suspended sediment (TSS) and coloured dissolved organic matter (CDOM) are usually of concern in water quality assessment [1,2]; chl-a, primary productivity and red tide index are more important in studies on biogeochemical processes [3,4]; TSS and the diffuse attenuation coefficient at 490 nm (Kd490) may be included in evaluation of physical processes [5,6]. The Geostationary Ocean Colour Imager (GOCI) was the first geostationary ocean colour sensor, launched by South Korea in June 2010. GOCI covers 2500 km 2500 km of the northeast Asian region, × with a spatial resolution of 500 m and a temporal resolution of 1 h. GOCI retrieves remote-sensing reflectance, chl-a and TSS. The values of these parameters have been validated by in situ data along the Korean coast, showing a relatively good agreement for remote-sensing reflectance (Rrs) except band 1 [7,8], but not satisfactory for chl-a using the ocean chlorophyll 2 algorithm (OC2) [8]. Remote Sens. 2019, 11, 946; doi:10.3390/rs11080946 www.mdpi.com/journal/remotesensing Remote Sens. 2019, 11, 946 2 of 9 Remote Sens. 2019, 11, x FOR PEER REVIEW 2 of 9 CoastalCoastal infrastructureinfrastructure for for urban urban development development has dramaticallyhas dramatically increased increased over the over last fewthe decades.last few Cross-seadecades. Cross-sea bridges connect bridges coasts connect and coasts can extend and can tens exte ofnd kilometres tens of kilometres over coastal over waters. coastal The waters. Jiaozhou The BayJiaozhou (JZB) Bay Bridge, (JZB) the Bridge, Hangzhou the Hangzhou Bay Bridge Bay and Bridge the newlyand the built newly Hong built Kong–Zhuhai–Macau Hong Kong–Zhuhai–Macau Bridge areBridge examples are examples of bridges of crossing bridges regionalcrossing seas. regional The spectralseas. The characteristics spectral characteristics of road-bridge of surfacesroad-bridge are disurfacesfferent fromare different the sea surface,from the which sea surface, may result which in errorsmay result in some in errors ocean in colour some products. ocean colour For terrestrialproducts. remoteFor terrestrial sensing, remote many esensing,fforts have many been efforts made have to improve been made the algorithms to improve to the detect algorithms and classify to detect different and typesclassify of different land cover types (e.g., of trees, land grass,cover blocks)(e.g., trees, in hyperspectral grass, blocks) imaging in hyperspectral data [9]. Theimaging different data spectral[9]. The responsesdifferent spectral of each responses material enable of each extraction material enable of one extraction expected landof one cover, expected with land others cover, discarded. with others For example,discarded. when For vegetationexample, when is expected, vegetation the water,is expe soil,cted, biomass-burning the water, soil, smokebiomass-burning and other landsmoke covers and shouldother land be excluded covers [should10]. For be the excluded oceans, although [10]. Fo cross-sear the oceans, bridges although exist worldwide, cross-sea bridge bridges impacts exist onworldwide, ocean colour bridge remote impacts sensing on areocean typically colour ignoredremote insensing data post-processingare typically ignored and discussion. in data post- For example,processing Gao and et discussion. al. [11] validated For example, their sediment Gao et al. model [11] validated for JZB using their the sediment GOCI TSS model product for JZB without using payingthe GOCI attention TSS product to potential without bridge paying contamination. attention to Hangzhou potential bridge Bay Bridge contamination. was also not Hangzhou considered Bay in aBridge GOCI-based was also assessment not considered of the diurnalin a GOCI-based variation inassessment chl-a and of TSS the [12 diurnal], nor in variation mapping in the chl-a suspended and TSS particulate[12], nor inmatter mapping [13 ].the suspended particulate matter [13]. InIn thisthis short short communication, communication, a case a case study study of the of impact the impact of Jiaozhou of Jiaozhou Bay Bridge Bay on Bridge GOCI on products GOCI isproducts described is described to illustrate, to illustrate, for the first for the time, first the time bridge, the bridge effects effects on ocean on ocean colour colour remote remote sensing. sensing. The oceanThe ocean environment environment of Jiaozhou of Jiaozhou Bay isBay first is describedfirst described in Section in Section2, and 2, theand GOCI the GOCI products products and theand methodologythe methodology used used in this in this short short communication communication in Section in Section3. Finally, 3. Finally, the potentialthe potential contamination contamination by coastalby coastal infrastructure infrastructure of GOCI of GOCI products products is discussed is discussed in Section in Section4. 4. 2.2. StudyStudy AreaArea LocatedLocated onon thethe coastcoast ofof thethe YellowYellow SeaSea (Eastern(Eastern China,China, FigureFigure1 1a),a), Jiaozhou Jiaozhou Bay Bay (JZB) (JZB) is is included included inin thethe GOCIGOCI targettarget area.area. ThisThis shallowshallow semi-enclosedsemi-enclosed baybay isis surroundedsurrounded byby QingdaoQingdao CityCity (Figure(Figure1 1b),b), andand isis 3333 kmkm long long and and 28 28 km km wide. wide. The The average average water wate depthr depth is is 7 m,7 m, with with the the greatest greatest depth depth of 64of m64 inm thein the middle middle channel. channel. Figure 1. (a) Location of Jiaozhou Bay (JZB) on the Yellow Sea coast. (b) Satellite image of JZB from GoogleFigure 1. Earth (a) Location (provided of byJiaozhou DigitalGlobal); Bay (JZB) the on black the Yellow line shows Sea coast. the JZB (b) Bridge.Satellite ( cimage) The normalisedof JZB from diGooglefference Earth water (provided index distribution by DigitalGlobal) for JZB (derived; the black from line the shows Geostationary the JZB Bridge. Ocean ( Colourc) The normalised Imager). difference water index distribution for JZB (derived from the Geostationary Ocean Colour Imager). JZB is a typical eutrophic ecosystem characterized by high nitrogen and phosphorus concentrations. MonthlyJZB meanis a chl-atypical fluctuated eutrophic between ecosystem 0.99 and charac 18.67terizedµg/L from by Marchhigh 2005nitrogen to February and phosphorus 2006, with theconcentrations. maximum values Monthly and largestmean chl-a fluctuations fluctuated in August between [14 ].0.99 Chlorophyll-a and 18.67 μ concentrationg/L from March is higher 2005 into theFebruary northeast 2006, and with northwest the maximum of the bay, values with a and gradual larges decreaset fluctuations towards in the August south [15[14].]. TheChlorophyll-a circulation inconcentration JZB is dominated is higher by tidal in the currents, northeast with and a minimum northwest speed of the of bay, 0.15 with m/s [16a gradual]. The maximum decrease currentstowards occurthe south at the [15]. entrance The circulation of the bay, in with JZB ais magnitude dominated of by 1.7 tidal m/s currents, [16]. Tides with are a semidiurnal; minimum speed among of the0.15 tidal m/s constituents,[16].
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