Spectral reflectance is a reliable water-quality estimator for small, highly turbid wetlands

Wetlands Ecology and Management

Volumn 23, Issue 5, 2015, Pages 933-946

  Vinciková, Hana ^a   Hanuš, Jan ^b   Pechar, Libor ^a,c  

^a UNIVERSITY OF SOUTH BOHEMIA   (Czech Republic)

^b Global Change Research Centre AS CR   (Czech Republic)

^c ENKI ops   (Czech Republic)

Author keywords

Chlorophyll; Hyperspectral reflectance; Remote sensing; TSS; Turbid inland waters; Water quality

Indexed keywords

AIRBORNE SENSING; ALGORITHM; CHLOROPHYLL A; EUTROPHICATION; FIELD METHOD; LAKE ECOSYSTEM; MESOTROPHIC ENVIRONMENT; NEAR INFRARED; POND; SCANNER; SPECTRAL REFLECTANCE; SUSPENDED LOAD; TURBIDITY; WATER QUALITY; WAVELENGTH; WETLAND;

CZECH REPUBLIC; JIHOCESKY; TREBON BASIN;

EID: 84942365704     PISSN: 09234861     EISSN: 15729834     Source Type: Journal    
DOI: 10.1007/s11273-015-9431-5     Document Type: Article

References (43)

1. Abd-Elrahman A, Croxton M, Pande-Chettri R et al (2011) In situ estimation of water quality parameters in freshwater aquaculture ponds using hyperspectral imaging system. ISPRS J Photogramm Remote Sens 66:463–472. doi:10.1016/j.isprsjprs.2011.02.005
2. Arenz RF, Lewis WM, Saunders JF (1996) Determination of chlorophyll and dissolved organic carbon from reflectance data for Colorado reservoirs. Int J Remote Sens 17:1547–1565. doi:10.1080/01431169608948723
3. Arst H (2003) Optical properties and remote sensing of multicomponental water bodies. Springer-Praxis book in marine science and coastal management. Springer, Berlin
4. Bhatti AM, Rundquist D, Schalles J et al (2009) A comparison between above-water surface and subsurface spectral reflectances collected over inland waters. Geocarto Int 24:133–141. doi:10.1080/10106040802460707
5. Brook A, Ben Dor E (2011) Supervised vicarious calibration (SVC) of hyperspectral remote-sensing data. Remote Sens Environ 115:1543–1555. doi:10.1016/j.rse.2011.02.013
6. Chipman JW, Olmanson LG, Gitelson AA (2009) Remote sensing methods for lake management: a guide for resource managers and decision-makers. Developed by the North American Lake Management Society in collaboration with Dartmouth College, University of Minnesota, and University of Nebraska for the United States environmental protection agency
7. Dekker AG (1993) Detection of optical water quality parameters for eutrophic waters by high resolution remote sensing. Ph.D Thesis, Vrije universiteit. Amsterdam
8. Doxaran D, Cherukuru RCN, Lavender SJ (2005) Use of reflectance band ratios to estimate suspended and dissolved matter concentrations in estuarine waters. Int J Remote Sens 26:1763–1769. doi:10.1080/01431160512331314092
9. Geomatica Algorithm Reference (2003) PCI Geomatics. 50 West Wilmot Street Richmond Hill, Ontario
10. Gitelson A (1992) The peak near 700 nm on radiance spectra of algae and water: relationships of its magnitude and position with chlorophyll concentration. Int J Remote Sens 13:3367–3373. doi:10.1080/01431169208904125
11. Gitelson A, Yacobi Y (2004) Monitoring quality of productive aquatic ecosystem: requirements for satellite sensors. BALWOIS 2004, Ohrid, FY Republic of Macedonia
12. Gitelson A, Szilagyi F, Mittenzwey K-H (1993) Improving quantitative remote sensing for monitoring of inland water quality. Water Res 27(7):1185–1194
13. Gordon HR, Morel A (1983) Remote assessment of ocean color for interpretation of satellite visible imagery: a review. Springer-Verlag, New York
14. Gurlin D, Gitelson AA, Moses WJ (2011) Remote estimation of chl-a concentration in turbid productive waters—return to a simple two-band NIR-red model? Remote Sens Environ 115:3479–3490. doi:10.1016/j.rse.2011.08.011
15. Hanuš J, Malenovský Z, Homolová L, Kaplan V, Lukeš P, Cudlín P (2008) Potentials of the VNIR Airborne Hyperspectral System AISA Eagle. GIS Ostrav 2008:27–30
16. Igamberdiev RM, Grenzdoerffer G, Bill R et al (2011) Determination of chlorophyll content of small water bodies (kettle holes) using hyperspectral airborne data. Int J Appl Earth Obs Geoinf 13:912–921. doi:10.1016/j.jag.2011.04.001
17. Jeník J, Květ J, Papáčková L (2002) Freshwater wetlands and their sustainable future: a case study of the Třeboň Basin Biosphere Reserve, Czech Republic. UNESCO, Paris
18. Kallio K, Kutser T, Hannonen T, Koponen S, Pulliainen J, Vepsäläinen J, Pyhälahti T (2001) Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons. Sci Total Environ 268:59–77
19. Kroupa M, Drbal K (1990) Chemistry of waters in flooded sand pits and its development. In: Krupauer V, Bican J, Drbal K (eds) Extracted ecosystem of Třeboň Biosphere Reserve. Academia Praha, Praha-Staré Město, pp 49–62
20. Le CF, Li YM, Zha Y et al (2011) Remote estimation of chlorophyll a in optically complex waters based on optical classification. Remote Sens Environ 115:725–737. doi:10.1016/j.rse.2010.10.014
21. Liu Y, Islam MA, Gao J (2003) Quantification of shallow water quality parameters by means of remote sensing. Prog Phys Geogr 27:24–43. doi:10.1191/0309133303pp357ra
22. Menken KD, Brezonik PL, Bauer ME (2006) Influence of chlorophyll and colored dissolved organic matter (CDOM) on Lake Reflectance Spectra: implications for Measuring Lake Properties by Remote Sensing. Lake Reserv Manag 22:179–190. doi:10.1080/07438140609353895
23. Mittenzwey K-H, Ullrich S, Gitelson AA, Kondratiev KY (1992) Determination of chlorophyll a of inland waters on the basis of spectral reflectance. Limnol Oceanogr 37:147–149. doi:10.4319/lo.1992.37.1.0147
24. Morel A, Prieur L (1977) Analysis of variations in ocean color. Limnol Oceanogr 22:709–722. doi:10.4319/lo.1977.22.4.0709
25. Moses WJ, Gitelson AA, Berdnikov S et al (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. doi:10.1016/j.rse.2012.01.024
26. 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 114:854–866. doi:10.1016/j.rse.2009.11.022
27. Olmanson LG, Brezonik PL, Bauer ME (2011) Evaluation of medium to low resolution satellite imagery for regional lake water quality assessments. Water Resour Res 47:W09515. doi:10.1029/2011WR011005
28. Ouillon S, Douillet P, Petrenko A et al (2008) Optical algorithms at satellite wavelengths for total suspended matter in tropical coastal waters. Sensors 8:4165–4185. doi:10.3390/s8074165
29. Pechar L (1987) Use of an acetone: methanol mixture for the extraction and spectrophotometric determination of chlorophyll-a in phytoplankton. Algol Stud Archiv für Hydrobiol Suppl Vol 46:99–117
30. Pechar L, Přikryl I, Faina R (2002) Hydrobiological evaluation of Třeboň fishponds since the end of 19th century. In: Květ J, Jeník J, Soukupová L (eds.) Freshwater wetlands and their sustainable future: a case study of the třeboň basin biosphere reserve, Czech Republic. Man and the Biosphere Series 28, UNESCO & The Parthenon Paris, pp 31–62
31. Randolph K, Wilson J, Tedesco L et al (2008) Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments, chlorophyll a and phycocyanin. Remote Sens Environ 112:4009–4019. doi:10.1016/j.rse.2008.06.002
32. Richter R (2007) Atmospheric/topographic correction for airborne imagery, ATCOR-4 user guide, version 4.2, deutsches zentrum fuer luft- und raumfahrt e. v. (dlr) and rese applications schläpfer, p 125
33. Rundquist DC, Schalles JF, Peake JS (1995) The response of volume reflectance to manipulated algal concentrations above bright and dark bottoms at various depths in an experimental pool. Geocarto Int 10:5–14. doi:10.1080/10106049509354508
34. Schaepman-Strub G, Schaepman ME, Painter TH et al (2006) Reflectance quantities in optical remote sensing definitions and case studies. Remote Sens Environ 103:27–42. doi:10.1016/j.rse.2006.03.002
35. Schalles JF, Rundquist DC, Schiebe FR (2001) The influence of suspended clays on phytoplankton reflectance signatures and the remote estimation of chlorophyll. Verh Int Ver Limnol 27:3619–3625
36. Schläpfer D, Odermatt D (2006) MODO -modtran4 for remote sensing applications. ReSe Applications Schläpfer, Wil, p 78
37. Shi K, Li Y, Li L et al (2013) Remote chlorophyll-a estimates for inland waters based on a cluster-based classification. Sci Total Environ 444:1–15. doi:10.1016/j.scitotenv.2012.11.058
38. Sokoletsky LG, Lunetta RS, Wetz MS, Paerl HW (2011) MERIS retrieval of water quality components in the turbid albemarle-pamlico sound estuary, USA. Remote Sens 3:684–707. doi:10.3390/rs3040684
39. Sterckx S, Knaeps E, Bollen M et al (2007) Retrieval of suspended sediment from advanced hyperspectral sensor data in the Scheldt estuary at different stages in the tidal cycle. Mar Geod 30:97–108. doi:10.1080/01490410701296341
40. Sudduth KA, Jang G-S, Lerch RN, Sadler EJ (2005) Estimating water quality with airborne and ground-based hyperspectral sensing. ASAE Paper No. 052006. St. Joseph, Mich.: ASAE
41. WFD 2000/60/EC: Directive 2000/60/EC of the European parliament and of the council establishing a framework for the community action in the field of water policy
42. Yacobi YZ, Moses WJ, Kaganovsky S et al (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. doi:10.1016/j.watres.2011.02.002
43. Zimba PV, Gitelson A (2006) Remote estimation of chlorophyll concentration in hyper-eutrophic aquatic systems: model tuning and accuracy optimization. Aquaculture 256:272–286. doi:10.1016/j.aquaculture.2006.02.038