on a regional basis, their adoption and use by resource managers should increase
significantly. The increased use of remote sensing will greatly improve the management of our water resources and should ultimately lead to better remote sensing
systems for monitoring these important natural resources.
Acknowledgments We gratefully acknowledge the support from the University of Minnesota
Agricultural Experiment Station, project MIN-042-056, and the “U-Spatial” project. P.L.B.
received support from a Professional Development for Retirees grant from the University of
Minnesota Office of the Vice President for Research and Retirees Association.
References
1. 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(9),
W09515. doi:10.1029/2011WR011005
2. O’Reilly JE, Maritorena S, Mitchell BG, Siegel DA, Carder KL, Garver SA, Kahru M,
McClain C (1998) Ocean color chlorophyll algorithms for SeaWiFS. J Geophys Res 103:
24937–24953
3. Franz BA, Bailey SW, Eplee RE, Feldman GC, Kwiatkowska E, McClain C, Meister G, Patt
FS, Werdell PJ (2005) The Continuity of ocean color measurements from SeaWiFS to MODIS.
In: Butler JJ (ed) Earth observing systems: X. Proceedings SPIE, vol 5882, The International
Society for Optical Engineering, pp 49–60
4. Kutser T, Pierson DC, Kallio KY, Reinart A, Sobek S (2005) Mapping lake CDOM by satellite
remote sensing. Remote Sens Environ 94:535–540
5. GEO (2007) Inland and nearshore coastal water quality remote sensing. In: Bauer M,
Dekker A, DiGiacomo P, Greb S, Gitelson A, Herlevi A, Kutser T (eds) GEO Group on
Earth Observation Workshop Final Report, 27–29 March 2007, Geneva, p 32
6. Gitelson AA, Gurlin D, Moses WJ, Barrow T (2009) A bio-optical algorithm for the remote
estimation of the chlorophyll a concentration in case 2 waters. Environ Res Lett 4(4):5. doi:10.
1088/1748-9326/4/4/045003
7. Moore GF, Aiken J, Lavender SJ (1999) The atmospheric correction of water colour and the
quantitative retrieval of suspended particulate matter in Case II waters: application to MERIS.
Int J Remote Sens 20(9):1713–1733
8. Bukata RP (2013) Retrospection and introspection on remote sensing of inland water quality:
“Like De ´j a Vu all over again”. J Great Lakes Res 39(Suppl):2–5
9. Mobley CD (1994) Optical properties of water. In: Bass M (ed) Handbook of optics. McGrawHill, New York, p 1152
10. Devred E, Turpie KR, Moses W, Klemas VV, Moisan T, Babin M, Toro-Farmer G, Forget
MH, Jo YH (2013) Future retrievals of water column bio-optical properties using the
Hyperspectral Infrared Imager (HyspIRI). Remote Sens 5:6812–6837. doi:10.3390/rs5126812
11. Kutser T, Herlevi A, Kallio K, Arst H (2001) A hyperspectral model for interpretation of
passive optical remote sensing data from turbid lakes. Sci Total Environ 268:47–58
12. Carlson RE (1977) A trophic state index for lakes. Limnol Oceanogr 22:361–369
13. Brezonik PL (1978) Effect of organic color and turbidity on Secchi disk transparency. J Fish
Res Board Can 35:1410–1416
14. Preisendorfer RW (1986) Secchi disk science: visual optics of natural waters. Limnol Oceanogr
31:909–926
15. Austin RW, Petzold T (1981) The determination of the diffuse attenuation coefficient of
sea water using the Coastal Zone Color Scanner. Oceanogr Space 13:239–256
Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and. . .
135
significantly. The increased use of remote sensing will greatly improve the management of our water resources and should ultimately lead to better remote sensing
systems for monitoring these important natural resources.
Acknowledgments We gratefully acknowledge the support from the University of Minnesota
Agricultural Experiment Station, project MIN-042-056, and the “U-Spatial” project. P.L.B.
received support from a Professional Development for Retirees grant from the University of
Minnesota Office of the Vice President for Research and Retirees Association.
References
1. 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(9),
W09515. doi:10.1029/2011WR011005
2. O’Reilly JE, Maritorena S, Mitchell BG, Siegel DA, Carder KL, Garver SA, Kahru M,
McClain C (1998) Ocean color chlorophyll algorithms for SeaWiFS. J Geophys Res 103:
24937–24953
3. Franz BA, Bailey SW, Eplee RE, Feldman GC, Kwiatkowska E, McClain C, Meister G, Patt
FS, Werdell PJ (2005) The Continuity of ocean color measurements from SeaWiFS to MODIS.
In: Butler JJ (ed) Earth observing systems: X. Proceedings SPIE, vol 5882, The International
Society for Optical Engineering, pp 49–60
4. Kutser T, Pierson DC, Kallio KY, Reinart A, Sobek S (2005) Mapping lake CDOM by satellite
remote sensing. Remote Sens Environ 94:535–540
5. GEO (2007) Inland and nearshore coastal water quality remote sensing. In: Bauer M,
Dekker A, DiGiacomo P, Greb S, Gitelson A, Herlevi A, Kutser T (eds) GEO Group on
Earth Observation Workshop Final Report, 27–29 March 2007, Geneva, p 32
6. Gitelson AA, Gurlin D, Moses WJ, Barrow T (2009) A bio-optical algorithm for the remote
estimation of the chlorophyll a concentration in case 2 waters. Environ Res Lett 4(4):5. doi:10.
1088/1748-9326/4/4/045003
7. Moore GF, Aiken J, Lavender SJ (1999) The atmospheric correction of water colour and the
quantitative retrieval of suspended particulate matter in Case II waters: application to MERIS.
Int J Remote Sens 20(9):1713–1733
8. Bukata RP (2013) Retrospection and introspection on remote sensing of inland water quality:
“Like De ´j a Vu all over again”. J Great Lakes Res 39(Suppl):2–5
9. Mobley CD (1994) Optical properties of water. In: Bass M (ed) Handbook of optics. McGrawHill, New York, p 1152
10. Devred E, Turpie KR, Moses W, Klemas VV, Moisan T, Babin M, Toro-Farmer G, Forget
MH, Jo YH (2013) Future retrievals of water column bio-optical properties using the
Hyperspectral Infrared Imager (HyspIRI). Remote Sens 5:6812–6837. doi:10.3390/rs5126812
11. Kutser T, Herlevi A, Kallio K, Arst H (2001) A hyperspectral model for interpretation of
passive optical remote sensing data from turbid lakes. Sci Total Environ 268:47–58
12. Carlson RE (1977) A trophic state index for lakes. Limnol Oceanogr 22:361–369
13. Brezonik PL (1978) Effect of organic color and turbidity on Secchi disk transparency. J Fish
Res Board Can 35:1410–1416
14. Preisendorfer RW (1986) Secchi disk science: visual optics of natural waters. Limnol Oceanogr
31:909–926
15. Austin RW, Petzold T (1981) The determination of the diffuse attenuation coefficient of
sea water using the Coastal Zone Color Scanner. Oceanogr Space 13:239–256
Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and. . .
135