Review: Remote sensing of aquatic vegetation to comply with the needs of the Water Framework Directive

References

• Alčantara, E. Barbosa, C., Stecha, J., Novo, E., Shimabukuro, Y. 2009. Improving the spectral unmixing algorithm to map water turbidity distributions. Environ. Modeling Softw. 24: 1051-1061.
   Google Scholar
• Alföldi, T.T., Munday, J.C. 1978. Water quality analysis by digital chromaticity mapping of Landsat data. Can. J. Remote Sensing 4: 108-126.
   Google Scholar
• AQEM 2002. Manual for the application of the AQEM system a comprehensive method to assess European streams using benthic macro invertebrates, developed for the purpose of the Water Framework Directive. AQEM Consortium, Contract No: -EVK1-CT1999-00027 http://www.aqem.de'>www.aqem.de
   Google Scholar
• Babichenko, S., Poryvkina, L. Arikese, V., Kaitala, S., Kuosa, H. 2003. Remote sensing of phytoplankton using laser-induced fluorescence. Remote Sens. Environ. 45: 43-50.
   Google Scholar
• Berestovski, I.F., Gitelson, A.A., Szabó, G., Szilágyi, F. 1984. Remote sensing measurements in Hungarian and Soviet test areas). Isledovanye Zemly iz Kosmosa [Investigations of Earth from Space] 5: 107-112 (in Russian).
   Google Scholar
• Bostater, C.R. Jr. 2004. Hyperspectral remote sensing protocol development for submerged aquatic vegetation in shallow waters. Proceedings of SPIE Volume: 5233, Issue: May 2010, Publisher: Spie, pp. 199-215., ISSN: 0277786X
   Google Scholar
• Braga, C.Z.F, Setzer, A.W. 1993. Water quality assessment with simultaneous Landsat-5 TM data at Guanabara Bay, Rio de Janeiro, Brazil. Remote Sens. Environ. 45: 95-106.
   Google Scholar
• Bukata, R.P., Jerome, J.H., Bruton, J.E. 1981. Optical water quality model of Lake Ontario: 1. Determination of the optical cross sections of organic and inorganic particulates in Lake Ontario. Appl. Optics 20.
   Google Scholar
• Bukata, R.P., Bruton, J.E., Jerome, J.H. 1988. Particulate concentrations in Lake St. Claire as recorded by a shipborne multispectral optical monitoring system. Remote Sens. Environ. 25: 201-229.
   Google Scholar
• Burenkov, V.I., Gurevich, I.J., Kopelevich, O.V., Shifrin, K.S. 1979. Spectral characteristics of reflected radiance and its investigation from high altitude. In: Optichestie metody izuchenia okeanos iv vnutzenih vodojmov [Optical methods for investigation of oceans and inland waters]. Nauka, Novosybirsk. (in Russian)
   Google Scholar
• Büttner, G. 2004. Environmental status evaluation by remote sensing, informatical relations. Környezetállapot értékelés Program Munkacsoport tanulmányok 2003-2004 [Environmental Status Assessment Working Group studies 2003-2004], pp. 1-16. Manuscript, http://www.kep.taki.iif.hu/file/Buttner_ http://www.kep.taki.iif.hu/file/Buttner_
   Google Scholar
• Büttner, G., Vörös, L. 1980. Investigation of Hungarian lakes by using Landsat digital data. Földfelszíni és Meteorológiai Megfigyelések a Világurbol [Land cover and meteorológical investigations from Space], Hungarian Society of Natural Sciences, Budapest (in Hungarian).
   Google Scholar
• Büttner, G., Bíró, M., Maucha, M., Petrik, O. 2000. Land cover mapping at scale 1:50.000 in Hungary: lessons learnt from the European CORINE programme. In: A decade of Trans-European remote sensing cooperation, 20th EARSeL Symp., 14-16 June, 2000, pp. 25-31.
   Google Scholar
• Chen, Q., Zhang, Y., Ekroos, A., Hallikainen, M. 2004. The role of remote sensing technology in the EU Water Framework Directive (WFD). Environm. Sci. Policy 7: 267-276.
   Google Scholar
• Chormansky, J., Okruszko, T., Ignar, S., Batelaan, O., Rebel., K.T., Wassen, M.J. 2011. Flood mapping with remote sensing and hydrochemistry: a new method for distinguish the origin of flood water during floods. Ecol. Eng. 37: 1334-1349.
   Google Scholar
• CIS WG 2.7 2003. Monitoring under the Water Framework Directive. Common Implementation Strategy, Guidance Document No 7 on monitoring, Luxembourg: Office for Official Publications of the European Communities, ISBN 92-894-5127-0, ISSN 1725-1087.
   Google Scholar
• CWA 1972. Federal Pollution Control Amendments of 1972 (acronym: Clean Water Act), enacted by the 92nd United States Congress.
   Google Scholar
• Dömötörfy Z., Pomogyi P. 1996. Methods of mapping of macro vegetation in Kis-Balaton Water Protection System. Proc. of the 58th Hydrobiological Conference, Ecological status of Lake Balaton and its watershed. October 2-4, 1996, pp. 48-49 (in Hungarian).
   Google Scholar
• Dömötörfy, Zs., Reeder, D., Pomogyi, P. 2003. Changes in the macro-vegetation of the Kis-Balaton wetlands over the last two centuries: a GIS perspective. Hydrobiologia 506: 671-679.
   Google Scholar
• ECOSTAT 2003. Overall approach on ecological classification of ecological status and ecological potential: Final version. CIS Working Group 2/a, Report, 53 pp.
   Google Scholar
• Gitelson, A.A., Szilágyi, F. 1988. Radiomodels for eutrophic and mesotrophic water bodies. Isledovanye Zemly iz Kosmosa [Investigations of Earth from Space] 6: 72-80 (in Russian).
   Google Scholar
• Gitelson, A., Szilágyi, F. 1991. Aerospace monitoring of water quality. In: Geoscience and Remote Sensing Symposium, 1991. IGARSS '91. Remote sensing: global monitoring for earth management. Vol. 1, pp. 75-78. DOI: 10.1109/IGARSS.1991.577669.
   Google Scholar
• Gitelson, A.A., Nikanorov, A.M., Szabó, G., Szilágyi, F. 1986. Étude de la qualité des eaux de surface par télédetection. In: Lerner, D., ed. Monitoring to detect changes in water quality series IAHS Publication, No. 157: 111-123 (in French)
   Google Scholar
• Gitelson, A.A., Szilágyi, F., Garbuzov, G.P. 1990. Estimation of chlorophyll-a concentration of surface waters by remote sensing. Vízügyi Közl. [Publications in Water Management] 72: 142-153. (in Hungarian)
   Google Scholar
• Gitelson, A., Garbuzov, G., Szilágyi, F., Mittenzwei, -K-H., Karnieli, A. 1993a. Quantitative remote sensing methods for real-time monitoring inland water quality. Int. J. Remote Sens. 14: 1269-1295.
   Google Scholar
• Gitelson, A.A., Szilágyi, F., Mittenzwei, -K-H. 1993b. Improving quantitative remote sensing for monitoring of inland water quality. Water Res. 27: 1185-1194.
   Google Scholar
• Gitelson, A.A., Schalles, J.F., Hladik, C.M. 2007. Remote chlorophyll-a retrieval in turbid, productive estuaries: Chesapeake Bay case study. Remote Sens. Environ. 109: 464-472.
   Google Scholar
• Gitelson, A.A., Dall'Olmo, G., Moses, W., Rundquist, D.C., Barrow, T., Fisher, T.R., Gurlin, D., Holz, J. 2008. A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: validation. Remote Sens. Environ. 112: 3582-3593.
   Google Scholar
• Gohin, F., Salquin, B., Oger-Jeannereth, H., Lozac'h, L., Lampert, L., Lefebre, A., Riou, P., Bruchon, F. 2008. Towards a better assessment of the ecological status of coastal waters using satellite-derived chlorophyll-a concentrations. Remote Sens. Environ. 112: 3329-3340.
   Google Scholar
• Gordon, H.R. 1973. Simple calculation of the diffusive reflectance of the ocean. Appl. Optics, 12.
   Google Scholar
• Gordon, H.R., Mueller, J.L., Hovis, W.A. 1980. Phytoplankton pigments from the Nimbus-7 Coastal Zone Color Scanner: comparisons with surface measurements. Science 210: 63-66.
   Google Scholar
• Hunter, P.D., Tyler, A.N., Carvalho, L., Codd, G.A., Maberly, S.T. 2010. Hyperspectral remote sensing of cyanobacterial pigment as indicators for cell populations and toxin sin eutrophic lakes. Remote Sens. Environ. 114: 2705-2718.
   Google Scholar
• László, B., Szilágyi, F., Szilágyi, E., Heltai, G. 2007. Implementation of the EU Water Framework Directive in monitoring of small water bodies in Hungary, I. Establishment of surveillance monitoring system for physical and chemical characteristics for small mountain water courses. Microchem. J. 85: 65-71.
   Google Scholar
• Lathrop, R.G., Lillesand, T.M. 1986. Use of Thematic Mapper data to assess water quality in Green Bay and central Lake Michigan. American Society for Photogrammetry and Remote Sensing 52: 671-680.
   Google Scholar
• LEB, 2003. Aquatic vegetation mapping using hyperspectral remote sensing. Landscape Ecology Branch, Environmental Sciences Division, Water Resources Division, US Geological Survey. Environ. Monit. Assess., pp. 383-392.
   Google Scholar
• Lindell, T., Pierson, D., Premazzi, G., Zilioli, E. 1999. Manual for monitoring European lakes using remote sensing techniques. EUR18665, EN, Official Publication of the European Communities, Luxenbourg, 161 pp.
   Google Scholar
• McKee, D., Cunningham, A., Dudek, A. 2007. Optical water type discrimination and tuning remote sensing band-ratio algorithms: application to retrieval of chlorophyll and Kd(490) in the Irish and Celtic Seas. Estuar Coast. Shelf Sci. 73: 827-834.
   Google Scholar
• Morel, A., Gentili, B. 2009. A simple band ratio technique to quantify the colored dissolved and detrital organic material from ocean color remotely sensed data. Remote Sens. Environ. 113: 998-1011.
   Google Scholar
• Moses, W.J., Gitelson, A.A., Berdnikov, S., Saprygin, V., Povazhnyi, V. 2012. Operational MERIS-based NIR-red algorithms for estimating chlorophyll-a concentrations in coastal waters—the Azov Sea case study. Remote Sens. Environ. 121: 118-124.
   Google Scholar
• Moss, B. 2008. The Water Framework Directive: total environment or political compromise? Sci. Total Environ. 400: 32-41.
   Google Scholar
• Odermatt, D., Giardino, C., Heege, T. 2010. Chlorophyll retrieval with MERIS Case-2-Regional in perialpine lakes. Remote Sens. Environ. 114: 607-617.
   Google Scholar
• Pomogyi, P. 2006. Changes of macrovegetation of Kis-Balaton—historical perspectives. Hidrol. Közl. [Publications in Hydrology] 86: 91-93. (In Hungarian).
   Google Scholar
• Rosenquist, A., Milne, A., Lucas, R., Imhoff, M., Dobson, C. 2003. A review of remote sensing technology in support of the Kyoto Protocol. Environm. Sci. Policy 6: 441-455.
   Google Scholar
• Ruiz-Verdú, A., Simis, S.G.H., de Hoyos, C., Gons, H.J., Peña-Martínez, R. 2008. An evaluation of algorithms for the remote sensing of cyanobacterial biomass. Remote Sens. Environ. 112: 3996-4008.
   Google Scholar
• Scanlan, C.M., Foden, J., Wells, E., Best, M.A. 2007. The monitoring of the opportunistic macro algal blooms for the water framework directive. Mar. Poll. Bull. 55: 162-171.
   Google Scholar
• Shifrin, K.S. 1983. Optics of the ocean. Vol. 1: Physical optics. Science, Moscow (in Russian).
   Google Scholar
• Smith, A.Y., Addington, J.D. 1978. Water quality monitoring of Lake Mead: a practical look at the difficulties encountered in the application of remotely sensed data to analysis of temporal change (manuscript). Presented to the 5th. Canadian Symposium on Remote Sensing, Victoria.
   Google Scholar
• Smith, S.E., Büttner, G., Szilágyi, F., Horváth, L., Aufmuth, J. 2000. Environmental impacts of river diversion: Gabcikovo Barrage system. J. Water Resour. Plan. Manag. 126: 138-145.
   Google Scholar
• Strobl, R.O., Robillard, P.D. 2008. Network design for water quality monitoring of surface waters. Rev. J. Environ. Manag. 87: 639-648.
   Google Scholar
• Strömbeck, N., Pierson, D. 2001. The effects of variability in the inherent optical properties on estimations of chlorophyll a by remote sensing in Swedish freshwaters. Sci. Total Environ. 268: 123-137.
   Google Scholar
• Szabó, G., Szilágyi, F. 1984. Application of LANDSAT imagery in water quality control of Lake Balaton. Vízügyi Közl. [Publications in Water Management] 66: 401-416 (in Hungarian).
   Google Scholar
• Szabó, G., Szilágyi, F., Büttner, G., Remetei-Fülöpp, G. 1985. Anwendung der LANDSAT-satellitaufnahmen bei der Forschung von seichten Seen; Möglichkeiten zur Untersuchung des Neusiedlersees (Usefulness of LANDSAT data for water quality investigation of Lake Neusiedler). BFB-Bericht 55: 9-17 (in German).
   Google Scholar
• Szilágyi, F., Szilágyi, E., László, B., Licskó I. 2005: Implementation of Water Framework Directive: surveillance monitoring of acidified waters. Proceedings of 21st ICP Water Conference, Tallinn, Estonia, 17-19 October, 2005, pp. 59-65.
   Google Scholar
• Szilágyi, F. 2007. Water Framework Directive and Hydrobiology. In: Szilágyi, F., Orbán, V., eds. Applied Hydrobiology, MAVÍZ, Budapest, pp. 407-455 (in Hungarian).
   Google Scholar
• Tormos, T., Kosuth, P., Durrieu, S., Villeneuve, B., Wasson, J.G. 2011. Improving the quantification of land cover pressure on stream ecological status at the riparian scale using High Spatial Resolution Imagery. Phys Chem. Earth 36: 549-559.
   Google Scholar
• Varga, G., Michels, G., Szilágyi, F., Tubákos, É., Bozó, P., Vadász, V. 1989. Investigation by Landsat MSS and TM images used for water quality monitoring at Lake Balaton In: Proceedings of 3rd Hungarian Conference on Satellite Remote Sensing, OMSZ, Budapest, pp. 424-438.
   Google Scholar
• VKKI 2010. Prospectus on the river basin management plan of Hungary. Central Directorate for Water and Environmental Protection, Budapest http://www.vizeink.hu'>www.vizeink.hu
   Google Scholar
• WFD, 2000. Directive of the European Parlament and of the Council 2000/60/EC, Establishing a framework for community action in the field of water policy. European Union, Luxembourgh PE-CONS 3639/1/00 REV 1.
   Google Scholar
• William, D.J., Rybicki, N.B., Lombana, A.V., O'Brien, T.M., Gomez, R.B. 2003. Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing. Environ. Monit. Assess. 81: 383-392.
   Google Scholar
• Xie, Y, Sha, Z., Yu, M. 2008. Remote sensing imagery in vegetation mapping: a review. J. Plant Ecol. 1: 9-23.
   Google Scholar
• Yacobi, Y.Z., Moses, W.J., Kaganovsky, S., Sulimani, B., Leavitt, B.C., Gitelson, A.A. 2011. NIR-red reflectance-based algorithms for chlorophyll-a estimation in mesotrophic inland and coastal waters: Lake Kinneret case study. Water Res. 45: 2428-2436.
   Google Scholar
• Zhang, Y., Pulliainen, J., Koponen, S., Hallikainen, M. 2002. Application of an empirical neural network to surface water quality estimation in the Gulf of Finland using combined optical data and microwave data. Remote Sens. Environ. 81: 327-336.
   Google Scholar
• Zhang, Y., Pulliainen, J., Koponen, S., Hallikainen, M. 2003. Water quality retrievals from combined Landsat TM data and ERS-2 SAR data in the Gulf of Finland. IEEE Trans. Geosci. Remote Sens. 41: 622-629.
   Google Scholar