Abstract
This chapter reviews the Remote Sensing (RS) technologies that are particularly appropriate for marine and coastal ecosystem research and management. RS techniques are used to perform analysis of water quality in coastal water bodies; to identify, characterize and analyze river plumes; to extract estuarine/coastal sandy bodies; to identify beach features/patterns; and to evaluate the changes and integrity (health) of the coastal lagoon habitats. For effective management of these ecosystems, it is essential to have satellite data available and complementary accurate information about the current state of the coastal regions, in addition to well-informed forecasts about its future state. In recent years, the use of space, air and ground-based RS strategies has allowed for the rapid data collection, Image processing (Pixel-Based and Object-Based Image Analysis (OBIA) classification) and dissemination of such information to reduce vulnerability to natural hazards, anthropic pressures, and to monitoring essential ecological processes, life support systems and biological diversity.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aagaard T, Black KP, Greenwood B (2002) Cross-shore suspended sediment transport in the surf zone: a field-based parameterization. Mar Geol 185(3/4):283–302
Aguirre-Gomez R (2000) Detection of total suspended sediments in the North Sea using AVHRR and ship data. Int J Remote Sens 21(8):1583–1596
Aplin P (2005) Remote sensing: ecology. Prog Phys Geogr 29(1):104–113. doi:10.1191/030913305pp437pr
Baatz M, Schäpe A (2000) Multiresolution segmentation – an optimization approach for high quality multi-scale image segmentation. In: Strobl J et al (eds) Angewandte Geographische Informationsverarbeitung, XII. Wichmann, Heidelberg, pp 12–23
Baatz M, Benz U, Dehghani S, Heynen M, Holtje A, Hofmann P, Lingenfelder I, Mimler M, Sohlbach M, Weber M, Willhauck G (2001) eCognition objectoriented image analysis, V.2.2 user guide. Definiens Imaging, Munchen
Baptista P, Bastos L, Bernardes C, Cunha T, Dias J (2008) Monitoring sandy shores morphologies by DGPS – a practical tool to generate digital elevation models. J Coastal Res 24(6):1516–1528
Bird E (2008) Coastal geomorphology: an introduction, 2nd edn. Wiley, England
Bishop Y, Fienberg S, Holland P (1975) Discrete multivariate analysis: theory and practice. MIT, Cambridge, MA
Blaschke T, Lang S (2006) Object based image analysis for automated information extraction – a synthesis. In: Abstracts of the measuring the earth II ASPRS fall conference, San Antonio, 6–10 Nov 2006
Blaschke T, Lang S, Hay GJ (2008) Object-based image analysis: spatial concepts for knowledge-driven remote sensing applications. Springer, Berlin
Bock M, Rossner G, Wissen M, Remm K, Langanke T, Lang S, Klug H, Blaschke T, Vrscaj B (2005a) Spatial indicators for nature conservation from European to local scale. Ecol Indic 5:322–338
Bock M, Xofis P, Mitchley J, Rossner G, Wissen M (2005b) Object oriented methods for habitat mapping at multiple scales – case studies from northern Germany and Wye Downs, UK. J Nat Conserv 13:75–89
Breiman L, Friedman JH, Olshen RA, Stone CI (1984) Classification and regression trees, Wadsworth statistics/probability series, 1st edn. Chapman and Hall/CRC, New York
Buiten HJ, Clevers JGPW (1990) Remote sensing, theorie en toepassingen van landobservatie (Remote sensing theory and applications of land observation). Pudoc, Wageningen
Bustamante J, Pacios F, Díaz-Delgado R, Aragonés D (2006) Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images. In: Proceedings of the first international symposium on GlobWetlands: looking at wetlands from space, SP-634, ESA/ESRIN, Frascati, 19–20 Oct 2006
Bustamante J, Díaz-Delgado R, Aragonés D, García Murillo P, Castellanos EM et al (2013) Proyecto HYDRA: aplicación de la teledetección al estudio de la dinámica hídrica y de la vegetación acuática en las marismas de Doñana. In: Fernández-Renau González-Anleo A, de Miguel Llanes E (eds) Teledetección: Sistemas Operacionales de Observación de la Tierra. XV Congreso de la Asociación Española de Teledetección (AET). Torrejón de Ardoz, Madrid, España, 22–24 Oct 2013
Canny J (1986) A computational approach to edge-detection. IEEE Trans Pattern Anal 8(6):679–698
Chavez PS Jr (1988) An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sens Environ 24:459–479
Chen J, D’Sa E, Cui T, Zhang X (2013) A semi-analytical total suspended sediment retrieval model in turbid coastal waters: a case study in Changjiang River Estuary. Opt Express 21(11):13018–13031
Chen J, Cui T, Qiu Z, Lin C (2014) A three-band semi-analytical model for deriving total suspended sediment concentration from HJ-1A/CCD data in turbid coastal waters. ISPRS J Photogramm 93:1–13
Chowdhury PR, Deshmukh B, Goswami AK, Prasad SS (2011) Neural network based dunal landform mapping from multispectral images using texture features. IEEE J Sel Top Appl 4(1):171–184
Correia MJ, Costa JL, Chainho P, Félix PM, Chaves ML, Medeiros JP, Silva G, Azeda C, Tavares P, Costa A, Costa AM, Bernardo J, Cabral HN, Costa MJ, Cancela da Fonseca L (2012) Inter-annual variations of macrobenthic communities over three decades in a land-locked coastal lagoon (Santo André, SW Portugal). Estuar Coast Shelf Sci 110:168–175. doi:10.1016/j.ecss.2012.04.028
Cracknell AP (1999) Remote sensing techniques in estuaries and coastal zones – an update. Int J Remote Sens 19(3):485–496
Daya-Sabar BS, Ghandi G, Prakasa-Rao BS (1995) Applications of mathematical morphology in surface water body studies. Int J Remote Sens 16:1495–1502
Diaz Varela RA, Ramil Rego P, Calvo Iglesias S, Muñoz Sobrino C (2008) Automatic habitat classification methods based on satellite images: a practical assessment in the NW Iberia coastal mountains. Environ Monit Assess 144:229–250
Digital Globe (2010) The benefits of the eight spectral bands of WorldView-2 (White paper “WP-8SPEC Rev 01/13”). Digital Globe, Colorado
Doeffer R, Fischer J, Stössel M, Brockman C (1989) Analysis of Thematic Mapper data for studying the suspended matter distribution in the coastal area of the German bight (North Sea). Remote Sens Environ 28:61–73
Doxaran D, Froidefond JM, Lavender S, Castaing P (2002) Spectral signature of highly turbid waters: application with SPOT data to quantify suspended particulate matter concentrations. Remote Sens Environ 81(1):149–161
Druon JN, Schrimpf W, Dobricic S, Stips A (2004) Comparative assessment of large-scale marine eutrophication: North Sea area and Adriatic Sea as case studies. Mar Ecol-Prog Ser 272:1–23
Dzwonkowski B, Yan XH (2005) Tracking of a Chesapeake Bay estuarine outflow plume with satellite-based ocean color data. Cont Shelf Res 25:1942–1958
Evans D (2006) The habitats of the European union habitats directive. Biol Environ 106B(3):167–173. doi:10.3318/BIOE.2006.106.3.167
FAO (2014) The state of world fisheries and aquaculture, opportunities and challenges 2014. FAO Report, Rome
Fernández-Nóvoa D, Mendes R, deCastro M, Dias JM, Sánchez-Arcilla A, Gómez-Gesteira M (2015) Analysis of the influence of river discharge and wind on the Ebro turbid plume using MODIS-Aqua and MODIS-Terra data. J Mar Syst 142:40–46
Filippi AM, Jensen JR (2006) Fuzzy learning vector quantization for hyperspectral coastal vegetation classification. Remote Sens Environ 100(4):512–530
Foody GM (2002) Status of land cover classification accuracy assessment. Remote Sens Environ 80(1):185–201. doi:10.1016/S0034-4257(01)00295-4
Forget P, Ouillon S (1998) Surface suspend matter off the Rhone river mouth from visible satellite imagery. Oceanol Acta 21(6):739–749
Förster M, Frick A, Walentowski H, Kleinschmit B (2008) Approaches to utilising QuickBird data for the monitoring of NATURA 2000 habitats. Community Ecol 9:155–168
Freitas MC, Andrade C, Ferreira T, Cruces A, Araújo MF (2007) Wet dune slacks, sea-level and coastal evolution in the southwestern Portuguese façade. J Coastal Res SI 50:231–236
Frick A, Weyer G, Kenneweg H, Kleinschmit B (2005) A knowledge based approach to vegetation monitoring with Quickbird imagery. In: Proceedings of the ISPRS workshop 2005: high-resolution earth imaging for geospatial information, Hannover, 17–20 May 2005
Frihy OE, Dewidar KM, Nasr SM, El Raey MM (1998) Change detection of the northeastern Nile Delta of Egypt: shoreline changes, Spit evolution, margin changes of Manzala lagoon and its islands. Int J Remote Sens 19(10):1901–1912
Gan TY, Kalinga OA, Ohgushi K, Araki H (2004) Retrieving seawater turbidity from Landsat TM data by regressions and an artificial neural network. Int J Remote Sens 25(21):4593–4615
Gao Y, Mas JF (2008) A comparison of the performance of pixel-based and object-based classifications over images with various spatial resolutions. In: Hay GJ, Blaschke T, Marceau D (eds) GEOBIA 2008 – Pixels, objects, intelligence, GEOgraphic object based image analysis for the 21st century, Calgary, Alberta, Canada, 5–8 Aug 2008. ISPRS Archives, vol XXXVIII-4/C1, p 6
Godin DG, Huan L, Fraser RN, Rundquist DC, Stebbins WA (1993) Analysis of suspended solids in water using remotely sensed high resolution derivative spectra. Photogramm Eng Remote S 9(4):505–510
Gonçalves H, Teodoro AC, Almeida H (2012) Identification, characterization and analysis of the Douro river plume from MERIS data. IEEE J Sel Top Appl 5(5):1553–1563
Gonzalez RC, Woods RE (2008) Digital image processing, 3rd edn. Prentice Hall, Upper Saddle River
Groom G, Mücher CA, Ihse M, Wrbka T (2006) Remote sensing in landscape ecology: experiences and perspectives in a European context. Landsc Ecol 21:391–408. doi:10.1007/s10980-004-3164-9
Gross JE, Goetz SJ, Cihlar J (2009) Application of remote sensing to parks and protected area monitoring: introduction to the special issue. Remote Sens Environ 113(7):1343–1345. doi:10.1016/j.rse.2008.12.013
Guneroglu A, Karsli F, Dihkan M (2013) Automatic detection of coastal plumes using Landsat TM/ETM+ images. Int J Remote Sens 34(13):4702–4714. doi:10.1080/01431161.2013.782116
Gutierres F (2014) Structure and dynamics of habitats and landscape of Sado Estuary and Comporta/Galé Natura 2000 Sites – A contribution to sustainable land management and ecological restoration. Ph.D. dissertation, Institute of Geography and Territorial Planning, University of Lisbon
Gutierres F, Reis E, Neto C, Costa JC, Godinho-Ferreira P (2013) Integrating remote sensing in Natura 2000 habitat monitoring. In: Taveira Pinto F (ed) Proceedings of the 4rd international seminar “Os Recursos Hídricos, o Mar e o Litoral”, Porto, 2013. APRH, pp 54–63. ISBN:978-989-8509-09-3
Haest B, Thoonen G, Vanden Borre J, Spanhove T, Delalieux S, Bertels L, Kooistra L, Mücher CA, Scheunders P (2010) An object-based approach to quantity and quality assessment of heathland habitats in the framework of natura 2000 using hyperspectral airborne ahs images. In: Addink EA, Van Coillie FMB (eds) GEOBIA 2010: geographic object-based image analysis, Ghent, 29 Jun–2 Jul 2010. ISPRS Archives, vol XXXVIII-4/C7, p 6
Hall O, Hay GJ, Bouchard A, Marceau DJ (2004) Detecting dominant landscape objects through multiple scales: an integration of object-specific methods and watershed segmentation. Landsc Ecol 19(1):59–76. doi:10.1023/B:LAND.0000018371.43447.1f
Harris L, Nel R, Schoeman D (2011) Mapping beach morphodynamics remotely: a novel application tested on south African sandy shores. Estuar Coast Shelf Sci 92(1):78–89. doi:10.1016/j.ecss.2010.12.013
Hay G, Castilla G (2006) Object-based image analysis: strengths, weaknesses, opportunities and threats (SWOT). In: Lang S, Blaschke T, Schöpfer E (eds) Bridging remote sensing and GIS. 1st international conference on object-based image analysis (OBIA 2006), Salzburg University, Austria, 4–5 Jul 2006. ISPRS Archives, vol XXXVI-4/C42, p 3
Hay GJ, Castilla G (2008) Geographic object-based image analysis (GEOBIA): a new name for a new discipline. In: Lang S, Hay G, Blaschke T (eds) Object based image analysis. Springer, Berlin, pp 75–89
Hay GJ, Blaschke T, Marceau DJ, Bouchard A (2003) A comparison of three image-object methods for the multiscale analysis of landscape structure. ISPRS J Photogramm 57(5–6):327–345
Haykin S (1999) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall, Upper Saddle River
Hellweger FL, Schlosser P, Lall U, Weissel JK (2004) Use of satellite imagery for water quality studies in New York Harbor. Estuar Coast Shelf Sci 61(3):437–448. doi:10.1016/j.ecss.2004.06.019
Hendiarti N, Siegel H, Ohde T (2004) Investigation of different coastal processes in Indonesian waters using SeaWiFS data. Deep-Sea Res PT II 31(1–3):85–97. doi:10.1016/j.dsr2.2003.10.003
Hu CM, Muller-Karger FE, Biggs DC, Carder KL, Nababan B, Nadeau D, Vanderbloemen J (2003) Comparison of ship and satellite bio-optical measurements on the continental margin of the NE Gulf of Mexico. Int J Remote Sens 24(13):2597–2612. doi:10.1080/0143116031000067007
Islam MR, Yamaguchi Y, Ogawa K (2001) Suspended sediment in the Ganges and Brahmaputra Rivers in Bangladesh: observation from TM and AVHRR data. Hydrol Process 15(3):493–509. doi:10.1002/hyp.165
Jiang L, Yan X-H, Klemas V (2009) Remote sensing for the identification of coastal plumes: case studies of Delaware Bay. Int J Remote Sens 30(8):2033–2048. doi:10.1080/01431160802549211
Jin H, Mountrakis G (2013) Integration of urban growth modelling products with image-based urban change analysis. Int J Remote Sens 34(15):5468–5486. doi:10.1080/01431161.2013.791760
Kandus P, Karszenbaum H, Frulla L (1999) Land cover classification system for the lower delta of the Parana river (Argentina): its relationship with landsat thematic mapper spectral classes. J Coastal Res 15(4):909–926
Kennedy RE, Townsend PA, Gross JE, Cohen WB, Bolstad P, Wang YQ, Adams P (2009) Remote sensing change detection tools for natural resource managers: understanding concepts and tradeoffs in the design of landscape monitoring projects. Remote Sens Environ 113(7):1382–1396. doi:10.1016/j.rse.2008.07.018
Keramitsoglou I, Kontoes C, Sifakis N, Mitchley J, Xofis P (2005) Kernel based re-classification of earth observation data for fine scale habitat mapping. J Nat Conserv 13(2–3):91–99. doi:10.1016/j.jnc.2005.02.004
Kerr JT, Ostrovsky M (2003) From space to species: ecological applications of remote sensing. Trends Ecol Evol 18(6):299–305. doi:10.1016/S0169-5347(03)00071-5
Klemas V (2011) Remote sensing techniques for studying coastal ecosystems: an overview. J Coastal Res 27(1):2–17, doi:http://dx.doi.org/10.2112/JCOASTRES-D-10-00103.1
Kutser T, Metsamaa L, Strömbeck N, Vahtmäe E (2006) Monitoring cyanobacterial blooms by satellite remote sensing. Estuar Coast Shelf Sci 67(1–2):303–312. doi:10.1016/j.ecss.2005.11.024
Lang S (2008) Object-based image analysis for remote sensing applications: modeling reality – dealing with complexity. In: Lang S, Hay G, Blaschke T (eds) Object based image analysis. Springer, Berlin, pp 3–27
Lang S, Blaschke T (2003) Hierarchical object representation – comparative multi-scale mapping of anthropogenic and natural features. In: Ebner H, Heipke C, Mayer H, Pakzad K (eds) IC II/IV, WG III/4, III/5, III/6 photogrammetric image analysis, Munich, 17–19 Sept 2003. ISPRS Archives, vol XXXIV-3/W8, p 6
Lechner AM, Stein A, Jones SD, Ferwerda JG (2009) Remote sensing of small and linear features: quantifying the effects of patch size and length, grid position and detectability on land cover mapping. Remote Sens Environ 113(10):2194–2204. doi:10.1016/j.rse.2009.06.002
Lengyel S, Déri E, Varga Z, Horváth R, Tóthmérész B, Henry PY, Kobler A, Kutnar L, Babij V, Seliškar A, Christia C, Papastergiadou E, Gruber B, Henle K (2008) Habitat monitoring in Europe: a description of current practices. Biodivers Conserv 17(14):3327–3339. doi:10.1007/s10531-008-9395-3
Liew SC, Saengtuksin B, Kwoh LK (2011) Mapping water quality of coastal and inland waters using high resolution WorldView-2 satellite imagery. In: Proceedings of the 34th international symposium on remote sensing of environment, Sydney, 10–15 Apr 2011
Lillesand TM, Kiefer RW, Chipman JW (2008) Remote sensing and image interpretation, 6th edn. Wiley, Hoboken
Lim JS (1990) Two-dimensional signal and image processing. Prentice Hall, Upper Saddle River
Lira J (2006) Segmentation and morphology of open water bodies from multispectral images. Int J Remote Sens 27(18):4015–4038. doi:10.1080/01431160600702384
Lira J, Morales A, Zamora F (1997) Study of sediment distribution in the area of the Panuco river plume by means of remote sensing. Int J Remote Sens 18(1):171–182. doi:10.1080/014311697219349
Malthus TJ, Mumby PJ (2003) Remote sensing of the coastal zone: an overview and priorities for future research. Int J Remote Sens 24(13):2805–2815. doi:10.1080/0143116031000066954
Mas JF (2004) Mapping land use/cover in a tropical coastal area using satellite sensor data, GIS and artificial neural networks. Estuar Coast Shelf Sci 59(2):219–223. doi:10.1016/j.ecss.2003.08.011
McCarthy MJ, Halls JN (2014) Habitat mapping and change assessment of coastal environments: an examination of WorldView-2, QuickBird, and IKONOS satellite imagery and airborne LiDAR for mapping barrier island habitats. ISPRS Int J Geo-Inf 3(1):297–325. doi:10.3390/ijgi3010297
McFeeters SK (1996) The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int J Remote Sens 17(7):1425–1432. doi:10.1080/01431169608948714
Mehner H, Cutler M, Fairbairn D, Thompson G (2004) Remote sensing of upland vegetation: the potential of high spatial resolution satellite sensors. Global Ecol Biogeogr 13:359–369. doi:10.1111/j.1466-822X.2004.00096.x
Mendes R, Vaz N, Fernández-Nóvoa D, da Silva JCB, de Castro M, Gómez-Gesteira M, Dias JM (2014) Observation of a turbid plume using MODIS imagery: the case of Douro estuary (Portugal). Remote Sens Environ 154:127–138. doi:10.1016/j.rse.2014.08.003
Mertes LAK, Warrick JA (2001) Measuring flood output from 110 coastal watersheds in California with field measurements and SeaWiFS. Geology 29(7):659–662. doi:10.1130/0091-7613(2001)029<0659:MFOFCW>2.0.CO;2
Miller RL, Mckee BA (2004) Using MODIS Terra 250 m imagery to map concentration of total suspended matter in coastal waters. Remote Sens Environ 93(1–2):259–266. doi:10.1016/j.rse.2004.07.012
Mücher CA (2009) Geo-spatial modeling and monitoring of European landscapes and habitats using remote sensing and field surveys. Ph.D. dissertation, Wageningen University
Mücher CA, Kooistra L, Vermeulen M, Haest B, Spanhove T, Delalieux S, Vanden Borre J, Schmidt A (2010) Object identification and characterization with hyperspectral imagery to identify structure and function of NATURA 2000 habitats. In: Proceedings of the Geobia conference, Ghent, 30 June–2 July 2010
Mujabar PS, Chandrasekar N (2012) Dynamics of coastal landform features along the southern Tamil Nadu of India by using remote sensing and geographic information system. Geocarto Int 27(4):347–370. doi:10.1080/10106049.2011.638988
Mumby PJ, Edwards AJ (2002) Mapping marine environments with IKONOS imagery: enhanced spatial resolution can deliver greater thematic accuracy. Remote Sens Environ 82(2–3):248–257. doi:10.1016/S0034-4257(02)00041-X
Myint SW, Walker ND (2002) Quantification of surface suspended sediments along a river dominated coast with NOAA AVHRR and SeaWiFS measurements: Louisiana, USA. Int J Remote Sens 23(16):3229–3249. doi:10.1080/01431160110104700
Nagendra H (2001) Using remote sensing to assess biodiversity. Int J Remote Sens 22(12):2377–2400. doi:10.1080/01431160117096
Nechad B, Ruddick KG, Park Y (2010) Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters. Remote Sens Environ 114(4):854–866. doi:10.1016/j.rse.2009.11.022
Nezlin NP, DiGiacomo PM, Stein ED, Ackerman D (2005) Storm water runoff plumes observed by SeaWiFS radiometer in the Southern California Bight. Remote Sens Environ 98(4):494–510. doi:10.1016/j.rse.2005.08.008
O’Hara CG, King JS, Cartwright JH, King RL (2003) Multitemporal land use and land cover classification of urbanized areas within sensitive coastal environments. IEEE Trans Geosci Remote Sens 41(9):2005–2014. doi:10.1109/TGRS.2003.816573
Oliveira FSC, Kampel M, Amaral S (2008) Multitemporal assessment of the geomorphologic evolution of the Restinga of Marambaia, Rio de Janeiro, Brazil. Int J Remote Sens 29(19):5585–5594. doi:10.1080/01431160802061696
Ondrusek M, Stengel E, Kinkade CS, Vogel RL, Keegstra P, Hunter C, Kim C (2012) The development of a new optical total suspended matter algorithm for the Chesapeake Bay. Remote Sens Environ 119:243–254. doi:10.1016/j.rse.2011.12.018
Otero MP, Siegel DA (2004) Spatial and temporal characteristics of sediment plumes and phytoplankton blooms in the Santa Barbara Channel. Deep Sea Res Part 2 Top Stud Oceanogr 51(10–11):1129–1149. doi:10.1016/j.dsr2.2004.04.004
Otero P, Ruiz-Villarreal M, Peliz A (2008) Variability of river plumes off Northwest Iberia in response to wind events. J Mar Syst 72(1–4):238–255. doi:10.1016/j.jmarsys.2007.05.016
Otero P, Ruiz-Villarreal M, Peliz A (2009) River plume fronts off NW Iberia from satellite observations and model data. ICES J Mar Sci 66(9):1853–1864. doi:10.1093/icesjms/fsp156
Otsu N (1979) A threshold selection method from gray-level histogram. IEEE T Syst Man Cybern 9(1):62–66
Ouillon S, Forget P, Froidefond J-M, Naudin J-J (1997) Estimating suspended matter concentrations from SPOT data and from field measurements in the Rhône River Plume. Mar Technol Soc J 31(2):15–20
Ouillon S, Douillet P, Petrenko A, Neveux J, Dupouy C, Froidefond J-M, Andréfouët S, Muñoz-Caravaca A (2008) Optical algorithms at satellite wavelengths for total suspended matter in tropical coastal waters. Sensors 8(7):4165–4185. doi:10.3390/s8074165
Pais-Barbosa J, Veloso-Gomes F, Taveira-Pinto F (2009) Portuguese northwest beach classification using aerial photographs and GIS tools. J Coastal Res SI 56:1552–1556
Pal NR, Pal SK (1993) A review on image segmentation techniques. Pattern Recognit 26(9):1277–1294. doi:10.1016/0031-3203(93)90135-J
Rahman MR, Saha SK (2008) Multi-resolution segmentation for object-based classification and accuracy assessment of land use/land cover classification using remotely sensed data. J Indian Soc Remote Sens 36(2):189–201. doi:10.1007/s12524-008-0020-4
R Core Team (2013) R: a language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/. Accessed 20 July 2015
Ripley B, Venables W (2014) Nnnet: feed-forward neural networks and multinomial loglinear models. R package version 7.3–8. In: CRAN repository. Available via http://cran.r-project.org/web/packages/nnet/nnet.pdf. Accessed 19 Feb 2014
Ritchie JC, McHenry JR, Schiebe FR, Wilson RB (1974) The relationship of reflected solar radiation and the concentration of sediment in the surface water of reservoirs. In: Ritchie JC (ed) Remote sensing of earth resources, vol III. University of Tennessee Space Institute, Tullahoma, pp 57–72
Rodríguez-Guzmán V, Gilbes-Santaella F (2009) Using MODIS 250 m Imagery to Estimate Total Suspended Sediment in a Tropical Open Bay. International Journal of Systems Applications, Engineering & Development 1(3): 36–44
Rodríguez-Martín R, Rodríguez-Santalla I (2013) Detection of submerged sand bars in the Ebro Delta using ASTER images. In: Huang H et al (eds) New frontiers in engineering geology and the environment, vol 9. Springer, Berlin, pp 103–106
Roy DP, Wulder MA, Loveland TR, Woodcock CE, Allen RG, Anderson MC, Helder D, Irons JR, Johnson DM, Kennedy R, Scambos TA, Schaaf CB, Schott JR, Sheng Y, Vermote EF, Belward AS, Bindschadler R, Cohen WB, Gao F, Hipple JD, Hostert P, Huntington J, Justice CO, Kilic A, Kovalskyy V, Lee ZP, Lymburner L, Masek JG, McCorkel J, Shuai Y, Trezza R, Vogelmann J, Wynne RH, Zhu Z (2014) Landsat-8: science and product vision for terrestrial global change research. Remote Sens Environ 145:154–172. doi:10.1016/j.rse.2014.02.001
Ruddick K, De Cauwer V, Park Y, Becu G, De Blauwe J-P, De Vreker E, Deschamps P-Y, Knockaert M, Nechad B, Pollentier A, Roose P, Saudemont D, Van Tuyckom D (2003) Preliminary validation of meris water products for Belgian coastal waters. In: Proceedings of Envisat validation workshop, ESA SP-531, Frascati, Mar 2003
Rudorff ND, Kampel M, de Rezende CE (2011) Spectral mapping of the Paraíba do Sul River plume (Brazil) using multitemporal Landsat images. J Appl Remote Sens 5(1):053550. doi:10.1117/1.3630220
Sanjeevi S (1996) Morphology of dunes of the Coromandel coast of Tamil Nadu: a satellite data based approach for coastal landuse planning. Landsc Urban Plan 34(3–4):189–195. doi:10.1016/0169-2046(95)00233-2
Saran S, Sterk G, Kumar S (2009) Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watershed. J Appl Remote Sens 3(1):033551. doi:10.1117/1.3253618
Satellite Imaging Corporation (2015) Satellite sensors. Available via http://www.satimagingcorp.com/satellite-sensors/. Accessed 05 July 2015
Schiewe J (2002) Segmentation of high-resolution remotely sensed data – concepts, applications and problems. In: Armenakis C, Lee YC (eds) Joint ISPRS commission IV symposium: geospatial theory, processing and applications, Ottawa, 9–12 July 2002. ISPRS Archives, vol XXXIV part 4, p 6
Schiller H, Doerffer R (2005) Improved determination of coastal water constituent concentration from MERIS data. IEEE Trans Geosci Remote Sens 43(7):1585–1591. doi:10.1109/TGRS.2005.848410
Shi W, Wang M (2009) Satellite observations of flood-driven Mississippi River plume in the spring of 2008. Geophys Res Lett 36(7):L07607. doi:10.1029/2009GL037210
Short AD (1991) Macro-meso tidal beach morphodynamics: an overview. J Coastal Res 7(2):417–436
Short AD (1999) Beach and shoreface morphodynamics. Wiley, England
Short AD (2006) Australian beach systems – nature and distribution. J Coastal Res 22(1):11–27, doi:http://dx.doi.org/10.2112/05A-0002.1
Short AD (2012) Beach morphodynamics in Australia 1970s–2010. Geogr Res 50(2):141–153. doi:10.1111/j.1745-5871.2012.00760.x
Shridhar DJ, Alvarinho JL (2013) Very high-resolution satellite data for improved land cover extraction of Larsemann Hills, Eastern Antarctica. J Appl Remote Sens 7(1):073460. doi:10.1117/1.JRS.7.073460
Silveira M, Heleno S (2009) Separation between water and land in SAR images using region-based level sets. IEEE Geosci Remote Sens 6(3):471–475. doi:10.1109/LGRS.2009.2017283
Son YB, Gardner WD, Richardson MJ, Ishizaka J, Ryu JH, Kim S-H, Lee SH (2012) Tracing offshore low-salinity plumes in the Northeastern Gulf of Mexico during the summer season by use of multispectral remote-sensing data. J Oceanogr 68(5):743–760. doi:10.1007/s10872-012-0131-y
Song XF, Duan Z, Jiang XG (2012) Comparison of artificial neural networks and support vector machine classifiers for land cover classification in Northern China using a SPOT-5 HRG image. Int J Remote Sens 33(10):3301–3320. doi:10.1080/01431161.2011.568531
Sousa A, García-Murillo P (2003) Changes in the Wetlands of Andalusia (Doñana Natural Park, SW Spain) at the end of the Little Ice Age. Clim Change 58(1–2):193–217. doi:10.1023/A:1023421202961
Sousa A, García-Murillo P, Sahin S, Morales J, García-Barrón L (2010) Wetland place names as indicators of manifestations of recent climate change in SW Spain (Doñana Natural Park). Clim Change 100(3–4):525–557. doi:10.1007/s10584-009-9794-9
Sousa A, Morales J, García-Barrón L, García-Murillo P (2013) Changes in the Erica ciliaris Loefl. ex L. peat bogs of southwestern Europe from the 17th to the 20th centuries AD. The Holocene 23(2):255–269. doi:10.1177/0959683612455545
Story M, Congalton RG (1986) Accuracy assessment: a user’s perspective. Photogramm Eng Remote Sens 52(3):397–399
Tang S, Larouche P, Niemi A, Michel C (2013) Regional algorithms for remote-sensing estimates of total suspended matter in the Beaufort Sea. Int J Remote Sens 34(19):6562–6576. doi:10.1080/01431161.2013.804222
Teodoro AC (2015) Applicability of data mining algorithms in the identification of beach features/patterns on high-resolution satellite data. J Appl Remote Sens 9(1):095095. doi:10.1117/1.JRS.9.095095
Teodoro A, Almeida H (2011) Spatio-temporal variability analysis of the Douro River plume through MERIS data for one hydrological year. In: Neale MU, Maltese A (eds) Proceeding of the conference on remote sensing for agriculture, ecosystems, and hydrology XIII/18th international symposium on remote sensing, vol 8174, 10.1117/12.897519, 81741N, Prague, 19–21 Sept 2011
Teodoro AC, Gonçalves H (2011) Extraction of estuarine/coastal environmental bodies from satellite data through image segmentation techniques. In: Pei-Gee Ho (ed) Image segmentation. InTech, pp 435–458. ISBN: 978-953-307-228-9. doi:10.5772/14672
Teodoro AC, Gonçalves H (2012) A semi-automatic approach for the extraction of sandy bodies (Sand Spits) from IKONOS-2 data. IEEE J Sel Top Appl 5(2):634–642. doi:10.1109/JSTARS.2011.2181339
Teodoro AC, Veloso-Gomes F (2007) Quantification of the total suspended matter concentration around the sea breaking zone from in situ measurements and terra/aster data. Mar Georesour Geotechnol 25(2):67–80. doi:10.1080/10641190701334164
Teodoro AC, Marçal ARS, Veloso-Gomes F (2007a) Correlation analysis of water wave reflectance and local TSM concentrations in the breaking zone, using remote sensing techniques. J Coastal Res 23(6):1491–1497, doi:http://dx.doi.org/10.2112/05-0482.1
Teodoro AC, Veloso-Gomes F, Gonçalves H (2007b) Retrieving TSM concentration from multispectral satellite data by multiple regression and artificial neural networks. IEEE T Geosci Remote 45(5):1342–1350. doi:10.1109/TGRS.2007.893566
Teodoro AC, Veloso-Gomes F, Gonçalves H (2008) Statistical techniques for correlating total suspended matter concentration with seawater reflectance using multispectral satellite data. J Coastal Res 24(4A):40–49, doi:http://dx.doi.org/10.2112/06-0770.1
Teodoro AC, Gonçalves H, Veloso-Gomes F, Gonçalves JA (2009a) Modelling of the Douro river plume size, obtained through image segmentation of MERIS data. IEEE Geosci Remote Sens 6(1):87–91. doi:10.1109/LGRS.2008.2008446
Teodoro AC, Pais-Barbosa J, Veloso-Gomes F, Taveira-Pinto F (2009b) Beach hydromorphological classification through image classification techniques applied to remotely sensed data. Michel U, Civco DL (eds) Remote sensing for environmental monitoring, GIS applications, and geology IX. Proceedings of SPIE, vol 7478, 747827, Berlin, 31Aug 2009
Teodoro AC, Pais-Barbosa J, Veloso-Gomes F, Taveira-Pinto F (2009c) Evolution of beach hydromorphological behaviour and classification using image classification techniques. J Coastal Res SI 56(2):1607–1611
Teodoro AC, Gonçalves H, Pais-Barbosa J, Veloso-Gomes F, Taveira-Pinto F (2010) Identification of beach features/patterns through artificial neural networks techniques using IKONOS data. In: Wagner W, Székely B (eds) ISPRS TC VII symposium – 100 years ISPRS, Vienna, 5–7 Jul 2010. ISPRS Archives, vol XXXVIII, Part 7B, pp 574–579
Teodoro AC, Pais-Barbosa J, Gonçalves H, Veloso-Gomes F, Taveira-Pinto F (2011a) Extraction of Cabedelo sand spit area (Douro estuary) from satellite images through image processing techniques. J Coastal Res SI 64:1740–1744
Teodoro AC, Pais-Barbosa J, Gonçalves H, Veloso-Gomes F, Taveira-Pinto F (2011b) Identification of beach features/patterns through image classification techniques applied to remotely sensed data. Int J Remote Sens 32(22):7399–7422. doi:10.1080/01431161.2010.523729
Teodoro AC, Pais-Barbosa J, Gonçalves H, Veloso-Gomes F, Taveira-Pinto F (2011c) Beach hydromorphological analysis through remote sensing. J Coastal Res SI 61:44–51, doi:http://dx.doi.org/10.2112/SI61-001.55
Teodoro AC, Ferreira D, Gonçalves H (2013) The use of decision trees in the classification of beach forms/patterns on IKONOS-2 data. In: Michel U, Civco DL, Schulz K, Ehlers M, Nikolakopoulos KG (eds) Earth resources and environmental remote sensing/GIS applications IV. Proceedings of SPIE, vol 8893, SPIE, Bellingham, WA 2013, 88930N, Dresden, 23–25 Sept 2013
Therneau TM, Atkinson EJ (1997) An introduction to recursive partitioning using the rpart routines. Technical report 61, section of biostatistics, Mayo Clinic, Rochester
Turner W, Spector S, Gardiner N, Fladeland M, Sterling E, Steininger M (2003) Remote sensing for biodiversity science and conservation. Trends Ecol Evol 18(6):306–314. doi:10.1016/S0169-5347(03)00070-3
Urbański J (2009) Object based thematic mapping of coastal waters using MODIS satellite imagery. In: Proceedings of the 33rd international symposium on remote sensing of environment (ISRSE), Stresa, 4–8 May 2009
Vahtmäe E, Kutser T (2013) Classifying the Baltic Sea shallow water habitats using image-based and spectral library methods. Remote Sens 5(5):2451–2474. doi:10.3390/rs5052451
Valente AS, da Silva JCB (2009) On the observability of the fortnightly cycle of the Tagus estuary turbid plume using MODIS ocean colour images. J Mar Syst 75(1):131–137. doi:10.1016/j.jmarsys.2008.08.008
Vanden Borre J, Paelinckx D, Mücher CA, Kooistra L, Haest B, De Blust G, Schmidt AM (2011) Integrating remote sensing in Natura 2000 habitat monitoring: prospects on the way forward. J Nat Conserv 19(2):116–125. doi:10.1016/j.jnc.2010.07.003
Vanhellemont Q, Ruddick K (2014) Turbid wakes associated with offshore wind turbines observed with Landsat 8. Remote Sens Environ 145:105–115. doi:10.1016/j.rse.2014.01.009
Vantrepotte V, Loisel H, Mériaux X, Neukermans G, Dessailly D, Jamet C, Gensac E, Gardel A (2011) Seasonal and inter-annual (2002–2010) variability of the suspended particulate matter as retrieved from satellite ocean color sensor over the French Guiana coastal waters. J Coastal Res SI 64:1750–1754
Wang J (2009) Satellite remote sensing of suspended sediment concentrations in Turbid Rivers. Ph.D. dissertation, National University of Singapore
Wang YY, Li J (2008) Feature-selection ability of the decision-tree algorithm and the impact of feature-selection/extraction on decision-tree results based on hyperspectral data. Int J Remote Sens 29(10):2993–3010. doi:10.1080/01431160701442070
Warrick JA, Mertes LAK, Washburn L, Siegel DA (2004) Dispersal forcing of southern California river plumes, based on field and remote sensing observations. Geo-Mar Lett 24(1):46–52. doi:10.1007/s00367-003-0163-9
Warrick JA, DiGiacomo PM, Weisberg SB, Nezlin NP, Mengel M, Jones BH, Ohlmann JC, Washburn L, Terrill EJ, Farnsworth KL (2007) River plume patterns and dynamics within the Southern California Bight. Cont Shelf Res 27(19):2427–2448. doi:10.1016/j.csr.2007.06.015
Wassermann PD (1989) Neural computing theory and practice. Van Nostrand Reinhold Co, New York
Weih RC, Riggan ND (2010) Object-based classification vs. pixel-based classification: comparitive importance of multi-resolution imagery. In: Addink EA, Van Coillie FMB (eds) GEOBIA 2010: geographic object-based image analysis, Ghent, 29 June–2 July 2010. ISPRS Archives, vol XXXVIII-4/C7, p 6
Yang X (2009) Remote sensing and geospatial technologies for coastal ecosystem assessment and management. Springer, Berlin
Zhou W, Wang S, Zhou Y, Troy A (2006) Mapping the concentrations of total suspended matter in Lake Taihu, China, using Landsat-5 TM data. Int J Remote Sens 27(6):1177–1191. doi:10.1080/01431160500353825
Zhu W, Tian YQ, Yu Q, Becker BL (2013) Using Hyperion imagery to monitor the spatial and temporal distribution of colored dissolved organic matter in estuarine and coastal regions. Remote Sens Environ 134:342–354. doi:10.1016/j.rse.2013.03.009
Zhu W, Yu Q, Tian YQ, Becker BL, Zheng T, Carrick HJ (2014) An assessment of remote sensing algorithms for colored dissolved organic matter in complex freshwater environments. Remote Sens Environ 140:766–778. doi:10.1016/j.rse.2013.10.015
Acknowledgements
The authors wish to thank the General Directorate for the Territory (DGT) for supporting the research under the FIGGIE Program.
The GeoEye Foundation and Digital Globe for explicitly permitting use free-of-charge the satellite images.
The European Space Agency (ESA) for providing the MERIS data and IKONOS-2 images.
Finally, we should like to thank very much all those who have helped draft this chapter.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Gutierres, F., Teodoro, A.C., Reis, E., Neto, C., Costa, J.C. (2016). Remote Sensing Technologies for the Assessment of Marine and Coastal Ecosystems. In: Finkl, C., Makowski, C. (eds) Seafloor Mapping along Continental Shelves. Coastal Research Library, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-25121-9_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-25121-9_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25119-6
Online ISBN: 978-3-319-25121-9
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)