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RESEARCH ARTICLE: Near-Remote Sensing of Water Turbidity Using Small Unmanned Aircraft Systems

Published online by Cambridge University Press:  22 February 2016

Michael C. Vogt  and
Mark E. Vogt
Michael C. Vogt*
Affiliation:
CEO North American Robotics, Prior Lake, MN
Mark E. Vogt
Affiliation:
North American Robotics, Prior Lake, MN.
*
*Address correspondence to: Michael C. Vogt, Ph.D., CEO North American Robotics, PO Box 818, Prior Lake, MN 55372; (phone) 952/917-9366; (fax) 952/226-5575; (e-mail) [email protected].
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Abstract

This report describes the field demonstration of a near-remote sensing method to measure water turbidity over large areas, in a high-resolution, spatial context. Our interdisciplinary method used a novel multispectral imaging sensor deployed by a hand-launched small unmanned aircraft system (sUAS). The measurement of turbidity is a useful indicator of water quality. Current turbidity measurement tools, such as the Secchi disc, are labor-intensive and often limit coverage such that available samples are extrapolated unrealistically when representing large water resources. This handicaps computer models’ ability to predict run-off, and these models produce the best results if supplied with high-resolution, fine time-increment measurements. This first study of the method developed operated the sUAS below 200 m over the surface of a 9.3-ha lake, capturing visible and near-infrared imagery at resolutions of ~0.2 m/pixel and capturing spectral bands matching those captured by the Landsat 4-5 satellites. The study established the spectral sensitivity and spatial coverage of the instrumentation and correlated turbidity estimates against traditional Secchi disc readings taken across the lake. This study also differentiated turbidity contribution from suspended organics vs. suspended sediments. To manage glare, this new technique required strategically positioned sunlight, thus sharing some operational limitations with the Secchi disc method. Plans have been made to extend the technique to be suitable for deeper, clearer lakes. The technique represents an improved monitoring tool for environmental scientists, watershed managers, and civil engineers.

Environmental Practice 18: 18–31 (2016)

Type
Features
Information
Environmental Practice , Volume 18 , Issue 1 , March 2016 , pp. 18 - 31
Copyright
© National Association of Environmental Professionals 2016 

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References

Brezonik, P.L., Olmanson, L.G., Bauer, M.E., and Kloiber, S.M.. 2007. Measuring Water Clarity and Quality in Minnesota Lakes and Rivers: A Census-Based Approach Using Remote-Sensing Techniques. Water Resources Center, University of Minnesota, Minneapolis, MN.Google Scholar
Cole, G.A. 1994. Textbook of Limnology, 4th edition. Waveland Press Inc., Long Grove, IL, 412 pp.Google Scholar
Compton, J., and Hamilton., J. 2007. Color Filter Array 2.0. Kodak, Rochester, NY. Available at http://johncompton.pluggedin.kodak.com/default.asp?item=624876 (accessed February 25, 2011).Google Scholar
Centre for Remote Imaging, Sensing & Processing (CRISP). 2001. Interpreting Optical Remote Sensing Images. Centre for Remote Imaging, Sensing & Processing, National University of Singapore, Singapore. Available at http://www.crisp.nus.edu.sg/~research/tutorial/opt_int.htm (accessed January 22, 2015).Google Scholar
D’Luna, L.J., Parulski, K.A., Maslyn, D.C., Hadley, M.A., Kenney, T.J., Hibbard, R.H., Guidash, R.M., Lee, P.P., and Anagnostopoulos, C.N. 1989. A Digital Video Signal Post-Processor for Color Image Sensors. In Proceedings of the IEEE Custom Integrated Circuits Conference, 1989. Institute of Electrical and Electronics Engineers (IEEE), New York, NY, 24.2/1–24.2/4.Google Scholar
Deering, D.W. 1978. Rangeland Reflectance Characteristics Measured by Aircraft and Spacecraft Sensors (unpublished PhD dissertation). Texas A&M University, College Station, TX, 338 pp.Google Scholar
GoPro, Inc. 2014. GoPro Support. GoPro, Inc., San Mateo, CA. Available at http://gopro.com/support (accessed March, 12, 2015).Google Scholar
International Organization for Standardization (ISO). 1999. ISO 7027:1999 – Water Quality – Determination of Turbidity. ISO, Geneva, Switzerland. Available at http://www.iso.org/iso/catalogue_detail.htm?csnumber=30123 (accessed December 28, 2014).Google Scholar
Kolari Vision. 2013. Kolari Vision Homepage. Kolari Vision, Raritan, NJ. Available at http://kolarivision.com (accessed January 24, 2015).Google Scholar
Liew, S.C. 2001. Principles of Remote Sensing. Center for Remote Imaging, Sensing, and Processing (CRISP), National University of Singapore, Singapore, Available http://www.crisp.nus.edu.sg/~research/tutorial/rsmain.htm (accessed September 18, 2014).Google Scholar
Mann, A.G., Tam, C.C., Higgins, C.D., and Lodrigues, L.C.. 2007. The Association Between Drinking Water Turbidity and Gastrointestinal Illness: A Systematic Review. BMC Public Health 7(256):1–7.CrossRefGoogle ScholarPubMed
Myneni, R.B., Hall, F.G., Sellers, P.J., and Marshak, A.L.. 1995. The Interpretation of Spectral Vegetation Indexes. IEEE Transactions on Geoscience and Remote Sensing 33(2):481–486.Google Scholar
National Aeronautics and Space Administration (NASA). 2012. Measuring Vegetation (NDVI & EVI) – Normalized Difference Vegetation Index (NDVI). Earth Observatory, NASA, Washington, DC. Available at http://earthobservatory.nasa.gov/Features/MeasuringVegetation/measuring_vegetation_2.php (accessed September 23, 2014).Google Scholar
National Aeronautics and Space Administration (NASA). 2013. Landsat 7 Science Data Users Handbook. NASA Landsat7 Portal. NASA, Washington, DC. Available at http://landsathandbook.gsfc.nasa.gov (accessed September 11, 2014).Google Scholar
Olmanson, L.G., Kloiber, S.M., Brezonik, P.L., and Bauer, M.E.. 2000. Use of Satellite Imagery for Water Clarity Assessment of Minnesota’s 10,000 Lakes. University of Minnesota, Minneapolis, MN. Available at http://water.umn.edu/Documents/presentation1.pdf.Google Scholar
Sellers, P.J. 1985. Canopy Reflectance, Photosynthesis, and Transpiration. International Journal of Remote Sensing 6(8):1355–1372.Google Scholar
Shakopee Mdewakanton Sioux Community (SMSC). 2014. Water Quality Assessment Report 2014. SMSC Environmental Management Report. SMSC Department of Land & Natural Resources, 40 pp. Available at http://www.smscland.org/pdf/2014WQReport.pdf.Google Scholar
Shakopee Mdewakanton Sioux Community (SMSC), Prior Lake-Spring Lake Watershed District (PLSLWD), and the City of Prior Lake. 2013, October. A Subwatershed Assessment, Water Quality Management and BMP Retrofit Analysis for the Arctic Lake Subwatershed. PLSLWD, Prior Lake, MN, 49 pp. Available at http://www.plslwd.org/wp-content/uploads/2013/10/Arctic_Final_Report_20131003.pdf.Google Scholar
Sony Corporation. 2015. Sony Electronics. Sony Corporation, Tokyo, Japan. Available at http://www.sony.com/all-electronics (accessed June 2, 2015).Google Scholar
Tetracam Inc. 2015. Tetracam Products. Tetracam Inc., Chatsworth, CA. Available at http://www.tetracam.com/Products1.htm.Google Scholar
Tucci, A. 2013. Spring Lake Alum Treatment. Prior Lake-Spring Lake Watershed District, Prior Lake, MN. Available at http://www.plslwd.org/2013/02/spring-lake-alum-treatment.Google Scholar
Tucker, C.J. 1979. Red and Photographic Infrared Linear Combinations for Monitoring Vegetation. Remote Sensing of Environment 8(2):127–150.Google Scholar
United States Environmental Protection Agency (US EPA). 1993, August. Method 180.1: Determination of Turbidity by Nephelometry; Revision 2.0. Environmental Monitoring Systems Laboratory, Office of Research and Development, Cincinnati, OH. Available at http://www.xenco.com/content/pdf/tech/epa/180_1.pdf.Google Scholar
Wake, L.V., and Brady, R.F.. 1993. March. Formulating Infrared Coatings for Defense Applications. MRL Research Report MRL-RR-1-93. DSTO Materials Research Laboratory, Maribyrnong, Victoria, Australia. Available at http://www.dtic.mil/dtic/tr/fulltext/u2/a267555.pdf.Google Scholar