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Assessment of AHS (Airborne Hyperspectral Scanner) sensor to map macroalgal communities on the Ría de vigo and Ría de Aldán coast (NW Spain)

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Abstract

Ría de Vigo and Ría de Aldán have high biological richness that is reflected in the number of environmental protection areas like the Atlantic Islands National Park and five places of community interest. Benthic algal communities play an important role in these ecosystems due to their ecological functions and support a great part of this biological richness. We tested by means of bio-optical modelling and Airborne Hyperspectral Scanner (AHS) images to what extent remote sensing could be used to map these communities in Ría de Vigo and Ría de Aldán (NW Spain). Reflectance spectra of dominating macroalgae groups were modelled for different water depths in order to estimate the separability of different bottom types based on their spectral signatures and the spectral characteristics of the AHS. Our results indicate that separation between three macroalgae groups (green, brown and red) as well as sand is possible when the bottoms are emerged during low tide. The spectra differences decrease rapidly with increasing water depth. Two types of classifications were carried out with the three AHS images: maximum likelihood and spectral angle mapper (SAM). Maximum likelihood showed positive results reaching overall accuracy percentages higher than 95 % and kappa coefficients higher than 0.90 for the bottom classes: shallow sand, deep sand, emerged rock, emerged macroalgae and submerged macroalgae. Sand and algae substrates were then separately analysed with SAM. These classifications showed positive results for differentiation between green and brown macroalgae until 5 m depth and high differences between all macroalgae and sandy substrate. However, differences between red and brown macroalgae are only detectable when the algae are emerged.

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References

  • Alberotanza L, Brando VE, Ravagnan G, Zandonella A (1999) Hyperspectral aerial images. A valuable tool for submerged vegetation recognition in the Orbetello Lagoons, Italy. Int J Remote Sens 20:523–533

    Google Scholar 

  • Alonso-Pérez F, Ysebaert T, Castro CG (2010) Effects of suspended mussel culture on benthic-pelagic coupling in a coastal upwelling system (Ría de Vigo, NW Iberian Peninsula). J Exp Mar Biol Ecol 382:96–107

    Google Scholar 

  • Andrefouet S, Payri C, Hochberg EJ, Hu C, Atkinson MJ, Muller-Karger FE (2004) Use of in situ and airborne reflectance for scaling-up spectral discrimination of coral reef macroalgae from species to communities. Mar Ecol Progr Ser 283:161–177

    Google Scholar 

  • Arst H, Erm A, Reinart A, Sipelgas L, Herlevi A (2002) Calculating irradiance penetration into water bodies from the measured beam attenuation coefficient, II: application of the improved model to different types of lakes. Nord Hydrol 33(2/3):227–240

    CAS  Google Scholar 

  • Bárbara I, and Cremades J (1993) Guía de las Algas del litoral gallego. 2ª Ed Ayuntamiento de A Coruña (Casa das Ciencias), (2ª ed. Revisada)

  • Beach KS, Borgeas HB, Nishimura NJ, Smith CM (1997) In vivo absorbance spectra and the ecophysiology of reef macroalgae. Coral Reefs 16:21–28

    Google Scholar 

  • Bertels L, Vanderstraete T, Van Coillie S, Knaeps E, Sterckx S, Goossens R, Deronde B (2008) Mapping coral reefs hyperspectral CASI data; a case study: Fordata, Tanimbar, Indonesia. Int J Remote Sen 29(8):2359–2391

    Google Scholar 

  • Brando VE, Dekker AG (2003) Satellite hyperspectral remote sensing for estimating estuarine and coastal water quality. IEEE Trans Geosci Remote Sens 41:1378–1387

    Google Scholar 

  • Buiteveld H, Hakvoort J H M, Donze M (1994) The optical properties of pure water. SPIE vol. 2258, Ocean optics XII, 174–183

  • Cacabelos E, Olabarria C, Incera M (2010) Effects of habitat structure and tidal height on epifaunal assemblages associated with macroalgae. Estuar Coast Shelf Sci 89:43–52

    Google Scholar 

  • Casal G, Kutser T, Domínguez-Gómez JA, Sánchez-Carnero N, Freire J (2011) Mapping benthic macroalgal communities in the coastal zone using CHRIS-PROBA mode 2 images. Estuar Coast Shelf Sci 94(3):281–290

    Google Scholar 

  • Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psycholo Meas 20(1):37–46

    Google Scholar 

  • Congalton RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens Environ 37:35–46

    Google Scholar 

  • Corbari C, Sobrino JA, Mancini M, Hidalgo V (2010) Land surface temperature representativeness in a heterogeneous area through a distributed energy-water balance model and remote sensing data. Hydrol Earth Syst Sci 14:2141–2151

    Google Scholar 

  • Cremades J, Bárbara I, Veiga J (2004) Intertidal vegetation and its commercial potential on the shores of Galicia. Thalassas 20(2):69–80

    Google Scholar 

  • Dekker AG, Peters SWM (1993) The use of the Thematic Mapper for the analysis of eutrophic lakes: a case study in The Netherlands. Int J Remote Sens 14:799–822

    Google Scholar 

  • Dekker AG, BrandoVE, Anstee JM, Pinnel N, Kutser T, Hoogenboom H J (2001) Imaging spectrometry of water. Imaging spectrometry: basic principles and prospective applications, vol. IV. Kluwer, Dordrecht, pp 307–359

  • Dekker AG, Byrne GT, Brando V E, Anstee JM (2003) Hyperspectral mapping of intertidal rock platform vegetation as a tool for adaptative management. CSIRO Land and water, remote sensing and spatial analysis, Canberra technical report 9/03

  • Dierssen HM, Zimmerman C, Leathers RA, Downes TV, Davis CO (2003) Ocean color remote sensing of seagrass and bathymetry in the Bahamas Banks by high-resolution airborne imagery. Limnol Oceanogr 48(1):444–455

    Google Scholar 

  • Domínguez Gómez JA, Chuvieco-Salinero E, Sastre Merlín A (2009) Monitoring transparency in inland wáter bodies using multispectral images. Int J Remote Sens 30(6):1567–1586

    Google Scholar 

  • Fargion GS, Mueller JL (2000) Ocean Optics proto-cols for satellite ocean color sensor validation, revision 2, NASA/TM-2000-209966

  • Fernández-Renau A, Gómez JA, de Miguel E (2005) The INTA AHS system. Sensors, systems, and next-generation satellites IX. In: Meynart R, Neeck SP, Shimoda H (eds) Proceedings of the SPIE, vol 5978, pp 471–478

  • Figueiras FG, Labarta U, Fernández Reiriz MJ (2002) Coastal upwelling, primary production and mussel growth in the Rías Baixas of Galicia. Hydrobiologia 484:121–131

    Google Scholar 

  • Filgueira R, Castro CG (2010) Study of the trophic web of San Simón Bay (Ría deVigo) by using stable isotopes. Cont Shelf Res 31:476–487

    Google Scholar 

  • Fyfe SK (2003) Spatial and temporal variation in spectral reflectance: are seagrass species spectrally distinct? Limnol Oceanogr 48 (1, part 2):464–479

  • Goetz AFH, Vane G, Solomon J, Rock BN (1985) Imaging spectrometry for Earth remote sensing. Science 228:1147–1153

    CAS  Google Scholar 

  • Gordon HR, Smith RC, Zaneveld JRV (1980) Introduction to ocean optics. Proc SPIE Soc Opt Eng 6:1–43

    Google Scholar 

  • Gotceitas V, Fraser S, Brown JA (1997) Use of eelgrass beds (Zostera marina) by juvenile Atlantic cod (Gadus morhua). Can J Fish Aquat Sci 54:1303–1319

    Google Scholar 

  • Haxo FT, Blinks LR (1950) Photosynhetic action spectra of marine algae. J Gen Physiol 20:389–422

    Google Scholar 

  • Hedley JD, Mumby PJ (2002) Biological and remote sensing perspectives of pigmentation in coral reef organisms. Adv Mar Biol 43:277–317

    Google Scholar 

  • Henning BD, Cogan BC, Bartsch I (2007) Hyperspectral remote sensing and analysis of intertidal zones: a contribution to monitor coastal biodiversity. In: Car A, Griesebner G, Strobl J (ed) Geospatial crossroads, GI Forum. Wichmann, Heidelberg, pp 62–73

  • Hunter PD, Gilvear DJ, Tyler AN, Willby NJ, Kelly A (2010) Mapping macrophytic vegetation in shallow lakes using the Compact Airborne Spectrographic Imager (CASI). Aquat Conserv Mar Freshwater Ecosyst 20:717–727

    Google Scholar 

  • Jensen JR, Narumalani S, Weatherbee O, Mackey HE (1991) Remote sensing offers an alternative for mapping wetlands. Geo Inf Syst 1:46–53

    Google Scholar 

  • Jiménez M, Díaz-Delgado R, Soriguer R, Fernández-Renau A, Prado E, Gutiérrez de la Cámara O (2005) Aproximación del AHS a la estimación de la diversidad biológica de las comunidades de matorral de la Reserva Biológica de Doñana. XI Congreso de la Asociación Española de Teledetección, 21–23 septiembre, Santa Cruz de Tenerife

  • John DM (1971) The distribution and net productivity of sublittoral populations of attached macrophytic algae in an estuary on the Atlantic coast of Spain. Mar Biol 11:90–97

    Google Scholar 

  • Juanes J A, Guinda X, Puente A, Revilla JA (2008) Macroalgae, a suitable indicator of the ecological status of coastal rocky communities in the NE Atlantic. Ecological indicators, pp 351–359

  • Jupp DLB, Kirk JTO, Harris GP (1994) Detection, identification and mapping cyanobacteria-using remote sensing to measure the optical quality of turbird inland waters. Aust J Mar Freshw Res 45:501–828

    Google Scholar 

  • Kirk JTO (1984) Dependence of relationship between inherent and apparent optical properties of water on solar altitude. Limnol Oceanogr 29:350–356

    Google Scholar 

  • Kruse FA, Leftkoff AB, Boardman JB, Heidebrecht KB, Sahpiro AT, Barloon PJ, Goetz AFH (1993) The spectral image processing system (SIPS)—interactive visualisation and analysis of imaging spectrometer data. Remote Sens Environ 44:145–163

    Google Scholar 

  • Kutser T (2004) Quantitative detection of chlorophyll in cyanobacterial blooms by satellite remote sensing. Limnol Oceanogr 49:2179–2189

    Google Scholar 

  • Kutser T, Dekker AG, Skirving W (2003) Modelling spectral discrimination of great barrier reef benthic communities by remote sensing instruments. Limnol Oceanogr 48(1, part 2):497–510

    Google Scholar 

  • Kutser T, Miller I, Jupp DLB (2006a) Mapping coral reef benthic substrates using hyperspectral space-borne images and spectral libraries. Estuar Coast Shelf Sci 70:449–460

    Google Scholar 

  • Kutser T, Vahtmäe E, Metsamaa L (2006b) Spectral library of macroalgae and benthic substrates in Estonian coastal waters. Proc Estonian Acad Sci Biol Ecol 55:329–340

    Google Scholar 

  • Kutser T, Vahtmäe E, Praks J (2009) A sun glint correction method for hyperspectral imagery containing areas with non-negligible water leaving NIR signal. Remote Sens Environ 113:2267–2274

    Google Scholar 

  • Landis J, Koch G (1997) The measurement of observer agreement for categorical data. Biometrics 33:159–174

    Google Scholar 

  • Lee ZP, Du KP, Arnone R (2005) A model for the diffuse attenuation coefficient of downwelling irradiance. J Geophys Res 110:C02016. doi:10.1029/2004JC002275

    Google Scholar 

  • León I, Méndez G, Rubio B (2004) Fases biogeoquímicas del fe y grado de piritización en sedimentos de la Ría de Pontevedra (NO España): Implicaciones del cultivo del mejillón en bateas. Ciencias Marinas 30(004):585–602

    Google Scholar 

  • Liu CC, Carder KL, Miller RL, Ivey JE (2002) Fast and accurate model of underwater scalar irradiance. Appl Opt 41:4962–4974

    CAS  Google Scholar 

  • Lønborg C, Álvarez-Salgado XA, Davidson K, Martínez-García M, Teira E (2010) Assessing the microbial bioavailability and degradation rate constants of dissolved organic matter by fluorescence spectroscopy in the coastal upwelling system of the Ría de Vigo. Mar Chem 119:121–129

    Google Scholar 

  • Lorentsen SH, Gremillet D, Nymoen GH (2004) Annual variation in diet of breeding great cormorants: does it reflect varying recruitment of Gadoids? Waterbirds 27:161–169

    Google Scholar 

  • Lubin D, Li W, Dustan P, Mazel CH, Stamnes K (2001) Spectral signatures of coral reefs: features from space. Remote Sens Environ 75:127–137

    Google Scholar 

  • Madsen JD, Chambers PA, James WF, Koch EW, Westlake DF (2001) The interaction between water movement, sediment dynamics and submerged macrophytes. Hydrobiology 444(1–3):71–84

    Google Scholar 

  • Maritorena S, Morel A, Gentil B (1994) Diffuse reflectance of oceanic shallow waters. Influence of water depth and bottom albedo. Limnol Oceanogr 39(7):1689–1703

    Google Scholar 

  • Mehrtens C, Kaschell T, Tardeck F, Graser N, Borowy C, Bartsch I (2009) Differentiation of brown seaweeds by hyperspectral airborne remote sensing and field spectrometry in a rocky intertidal. In: 6th EARSeL SIG IS workshop

  • Mélin F, Zibordi G (2005) Aerosol variability in the Po Valley analyzed from automated optical measurements. Geophys Res Lett 32(L03810):1–4

    Google Scholar 

  • Mishra DR, Narumalani S, Rundquist D, Lawson M (2005) Characterizing the vertical diffuse attenuation coefficient for downwelling irradiance in coastal waters: Implications for water penetration by high resolution satellite data. ISPRS J Photogr Rem Sens 60:48–64

    Google Scholar 

  • Mobley CD (1999) Estimation of remote sensing reflectance from above-surface measurements. Appl Opt 38:7442–7455

    CAS  Google Scholar 

  • Mohammed AI, Fredriksen S (2004) Production, respiration and exudation of dissolved organic matter by the kelp Laminaria hyperborea along the west coast of Norway. J Mar Biol Assoc UK 84:887–894

    Google Scholar 

  • Montero P, Gómez-Gesteira M, Taboada JJ, Ruiz-Villarreal M, Santos AP, Neves RR, Prego R, Pérez-Villar V (1999) On residual circulation of the Ria of Vigo, using a 3-D baroclinic model. Bol Inst Esp Oceanogr 15(1–4):31–38

    Google Scholar 

  • Morel A, Antoine D, Gentili B (2002) Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle phase function. Appl Opt 41:6289–6306

    CAS  Google Scholar 

  • Myers S, Miller RL (2005) Optical airborne remote sensing. In: Miller S, Del Castillo CE, McKee BA (eds) Remote sensing of coastal aquatic environments. Springer, Dordrecht, pp 51–67

    Google Scholar 

  • Nogueira E, Pérez FF, Ríos AF (1997) Seasonal patterns and long-terms trends in an estuarine upwelling ecosystem (Ría de Vigo, NW Spain). Estuar Coast Shelf Sci 44:285–300

    CAS  Google Scholar 

  • Nombela MA, Vilas F (1987) Medios y submedios en el sector intermareal de la ensenada de San Simón. Ría de Vigo (Pontevedra): secuencias sedimentarias características. Acta Geológica Hispánica 21–22:223–231

    Google Scholar 

  • Olabarria C, Rodil IF, Incera M, Troncoso JS (2009) Limited impact of Sargassum muticum on native algal assemblages from rocky intertidal shores. Mar Environ Res 67:153–158

    CAS  Google Scholar 

  • Pe’eri S, Morrison JR, Short F, Mathieson A, Brook A, Trowbridge P (2008) Macroalgae and eelgrass mapping in Great Bay Estuary using AISA hyperspectral imagery. A final report to The New Hampshire Estuaries Project

  • Phinn S, Roelfsema C, Dekker A, Brando V, Anstee J (2008) Mapping seagrass species, cover and biomass in shallow waters: An assessment of satellite multispectral and airborne hyperspectral imaging systems in Moreton Bay (Australia). Remote Sens Environ 112:3413–3425

    Google Scholar 

  • Pierson DC, Strömbeck N (2000) A modelling approach to evaluate preliminary remote sensing algorithms: Use of water quality data from Swedish Great Lakes. Geophysica 36(1–2):177–202

    Google Scholar 

  • Pinnel N, Heege T, Zimmermann S (2004) Spectral discrimination of submerged macrophytes in lakes using hyperspectal remote sensing data. In: SPIE Proceedings of Ocean Optics XVII, Fremantle, Australia

  • Preisendorfer RW (1976) Hydrologic optics, vol 1, Introduction. National Technical Information Service, Springfield, VA

  • Reinart A, Paavel B, Pierson D, Strömbek N (2004) Inherent and apparent optical properties of Lake Pepsi, Estonia. Boreal Environ Res 9:429–445

    Google Scholar 

  • Rejas JG, Prado E, Jiménez M, Fernández-Renau A, Gómez JA, de Miguel E (2005) Caracterización del sensor hiperespectal AHS para la georreferenciación directa de imágenes a partir de un sistema inercial GPS/IMU. International Congress 6th Geomatic week, Barcelona

  • Richards JA (1999) Remote sensing and digital iamge analysis: an introduction, 2nd edn. Springer, Berlin, p 363

  • Richter R (2004) Atmospheric/topographic correction for airborne imagery. ATCOR-4 user guide version 3.1. DLR, Wessling, Germany

  • Schott JR (1997) Remote sensing: the image chain approach. University Press, New York, p 497

  • Shaffer S (2003) Preferential use of nearshore kelp habitats by juvenile salmon and forage fish. In: Proceedings of the Georgia Basin/Puget sound research conference

  • Silva TSF, Costa MPF, Melack JM, Novo EMLM (2008) Remote sensing of aquatic vegetation: theory and applications. Environ Monit Assess 140:131–145

    Google Scholar 

  • Smith CM, Alberte RS (1994) Characterization of in vivo absorption features of chlorophyte, phaeophyte and rhodophyte algal species. Mar Biol 118:511–521

    Google Scholar 

  • Stephens FC, Louchard EM, Reid RP, Maffione RA (2003) Effects of microalgal communities on reflectance spectra of carbonate sediments in subtidal optically shallow marine environments. Limnol Oceanogr 48(1, part 2):535–546

    Google Scholar 

  • Szekielda KH, Marmorino GO, Bowles JH, Gillis D (2010) High spatial resolution spectrometry of rafting macroalgae (Sargassum). J Appl Remote Sens 4:043529

    Google Scholar 

  • Theriault C, Scheibling R, Hatcher B, Jones W (2006) Mapping the distribution of an invasive marine alga (Codium fragile spp. tomentosoides) in optically shadow coastal waters using the compact airborne hyperspectral imager (CASI). Can J Remote Sens 32(5):315–329

    Google Scholar 

  • Tyler JE (1960) Radiance distribution as a function of depth in an underwater environment. Bull Scripps Inst Oceanogr 7:363–411

    Google Scholar 

  • Vahtmäe E, Kuster T, Martin G, Kotta J (2006) Feasibility of hyperspectral remote sensing for mapping macroalgal cover in turbid coastal waters- a Baltic Sea case study. Remote Sens Environ 101:342–351

    Google Scholar 

  • Vasquez JA (2008) Production, use and fate of Chilean brown seaweeds: resources for a sustainable fishery. J Appl Phycol 20:7–17

    Google Scholar 

  • Vea J, Ask E (2011) Creating a sustainable commercial harvest of Laminaria hyperborea, in Norway. J Appl Phycol 23:489–494

    Google Scholar 

  • Veiga-Villar AJ (1999) Caracterización de la flora y vegetación bentónica marina intermareal y de su riqueza en recursos explotables en las Rías Baixas gallegas (NO Península Ibérica). Departamento de Biología Animal, Biología Vegetal y Ecología. A Coruña, Universidad de A Coruña

  • Wettle M, Brando VE, Dekker AG (2004) A methodology for retrieval of environmental noise equivalent spectra applied to four Hyperion scenes of the same tropical coral reef. Remote Sens Environ 93:188–190

    Google Scholar 

  • Xu F, Dawson RW, Tao S, Cao J, Li B (2001) A method for lake ecosystem health assessment: an Ecological Modeling Method (EMM) and its application. Hydrobiologia 443:159–175

    Google Scholar 

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Acknowledgments

This research was supported by the Spanish Government through the Spanish Ministry of Environment and Rural and Marine Affairs (SARGAL PROJECT 030/SGTB/2007/1.4), the Galician government through the INCITE program (PROJECT 07MDS010CT) and by the European Regional Development Fund (ERDF). This research was also partially support by a pre-doctoral grant of María Barbeito Program (Xunta de Galicia) and a research grant of Diputación de A Coruña. The authors would like to thank CETMAR (Centro Tecnolóxico do Mar) for its help with field work and INTA for its support in the flight campaign and AHS images pre-processing. The authors also thank the anonymous reviewers for their helpful comments and suggestions.

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  1. Grupo de Recursos Marinos y Pesquerías, Facultad de Ciencias, Universidad de A Coruña, Rúa da Fraga 10, 15008, A Coruña, Spain

    G. Casal, N. Sánchez-Carnero & J. Freire

  2. Centro de Estudios Hidrográficos (CEDEX), Paseo Bajo de la Virgen del Puerto 3, 28005, Madrid, Spain

    J. A. Domínguez-Gómez

  3. Estonian Marine Institute, University of Tartu, Mäealuse 14, Tallinn, 12618, Estonia

    T. Kutser

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  1. G. Casal
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Correspondence to G. Casal.

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Communicated by F. Bulleri.

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Casal, G., Sánchez-Carnero, N., Domínguez-Gómez, J.A. et al. Assessment of AHS (Airborne Hyperspectral Scanner) sensor to map macroalgal communities on the Ría de vigo and Ría de Aldán coast (NW Spain). Mar Biol 159, 1997–2013 (2012). https://doi.org/10.1007/s00227-012-1987-5

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