World Environmental and Water Resources Congress 2020
Sediment Color Effects on the Estimation of Suspended Sediment Concentration from Digital Imagery
Publication: World Environmental and Water Resources Congress 2020: Emerging and Innovative Technologies and International Perspectives
ABSTRACT
This study investigates the use of digital cameras for remote sensing of suspended sediment concentration (SSC) in streams. The performance of the digital cameras in estimating SSC is assessed, and the effect of sediment color on the accuracy of this method is investigated, based upon laboratory experiments employing sediments of different colors. The results of this study indicate that: 1) red waveband reflectance values of the digital images indicates a strong positive linear relationship with the SSC within the range of 25–200 mg/l, while green and blue wavebands seem to be insensitive to the SSC variations; and 2) sediment color influences the reflectance properties of the water surface, resulting in higher reflectance of lighter color sediments than darker colored sediments. The correlation between the SSC and calculated reflectance values demonstrates that this method is suitable for mapping the SSC in complex river settings with a wide range of suspended sediment conditions.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Ayana, E. K., Worqlul, A. W., & Steenhuis, T. S. (2015). Evaluation of stream water quality data generated from00 MODIS images in modeling total suspended solid emission to a freshwater lake. Science of the Total Environment, 523, 170-177.
Carder, K. L., & Steward, R. G. (1985). A remote-sensing reflectance model of a red-tide dinoflagellate off west Florida 1. Limnology and Oceanography, 30(2), 286-298.
Congress, S. S., & Puppala, A. J. (2019, July). Novel methodology of using aerial close-range photogrammetry technology for monitoring the pavement construction projects. In International Airfield and Highway Pavements Conference (p. 11).
Curran, P.J., Novo, E.M.M., 1988. The relationship between suspended sediment concentration and remotely sensed spectral radiance: A review. J. Coast. Res. 4, 351–368.
Defersha, M. B., Melesse, A. M., & McClain, M. E. (2012). Watershed scale application of WEPP and EROSION 3D models for assessment of potential sediment source areas and runoff flux in the Mara River Basin, Kenya. Catena, 95, 63-72.
Doxaran, D., Froidefond, J.-M., Castaing, P., 2002. A reflectance band ratio used to estimate suspended matter concentrations in sediment-dominated coastal waters. Int. J. Remote Sens. 23, 5079–5085.
Doxaran, D., Froidefond, J. M., & Castaing, P. (2003). Remote-sensing reflectance of turbid sediment-dominated waters. Reduction of sediment type variations and changing illumination conditions effects by use of reflectance ratios. Applied Optics, 42(15), 2623-2634.
Espinoza-Villar, R., Martinez, J. M., Armijos, E., Espinoza, J. C., Filizola, N., Dos Santos, A., … & Vauchel, P. (2018). Spatio-temporal monitoring of suspended sediments in the Solimões River (2000–02014). Comptes Rendus Geoscience, 350(1-2), 4-12.
Fang, L., Chen, S., Wang, H., Qian, J., & Zhang, L. (2010). Detecting marine intrusion into rivers using EO-1 ALI satellite imagery: Modaomen Waterway, Pearl River Estuary, China. International Journal of Remote Sensing, 31(15), 4125-4146.
Forget, P., & Ouillon, S. (1998). Surface suspended matter off the Rhone river mouth from visible satellite imagery. Oceanologica acta, 21(6), 739-749.
Gebreslassie, H. G., Melesse, A. M., Bishop, K., & Gebremariam, A. G. (2019). Linear spectral unmixing algorithm for modelling suspended sediment concentration of flash floods, upper Tekeze River, Ethiopia. International Journal of Sediment Research.
Gholizadeh, M. H., Melesse, A. M., & Reddi, L. (2016). A comprehensive review on water quality parameters estimation using remote sensing techniques. Sensors, 16(8), 1298.
Gin, K. H., Koh, S. T., & Lin, I. I. (2003). Spectral irradiance profiles of suspended marine clay for the estimation of suspended sediment concentration in tropical waters. International Journal of Remote Sensing, 24(16), 3235-3245.
Goddijn-Murphy, L., Dailloux, D., White, M., & Bowers, D. (2009). Fundamentals of in situ digital camera methodology for water quality monitoring of coast and ocean. Sensors, 9(7), 5825-5843.
Islam, M. R., Yamaguchi, Y., & Ogawa, K. (2001). Suspended sediment in the Ganges and Brahmaputra Rivers in Bangladesh: observation from TM and AVHRR data. Hydrological Processes, 15(3), 493-509.
Islam, M. A., Gao, J., Ahmad, W., Neil, D., & Bell, P. (2003). Image calibration to like-values in mapping shallow water quality from multitemporal data. Photogrammetric Engineering & Remote Sensing, 69(5), 567-575.
Karabulut, M., & Ceylan, N. (2005). The spectral reflectance responses of water with different levels of suspended sediment in the presence of algae. Turkish Journal of Engineering and Environmental Sciences, 29(6), 351-360.
Leeuw, T., & Boss, E. (2018). The hydrocolor app: Above water measurements of remote sensing reflectance and turbidity using a smartphone camera. Sensors, 18(1), 256.
Liu, X. (2008). Airborne LiDAR for DEM generation: some critical issues. Progress in Physical Geography, 32(1), 31-49.
Lodhi, M. A., Rundquist, D. C., Han, L., & Kuzila, M. S. (1997). The potential for remote sensing of loess soils suspended in surface waters. JAWRA Journal of the American Water Resources Association, 33(1), 111-117.
Ma, R., & Dai, J. (2005). Investigation of chlorophyll-a and total suspended matter concentrations using Landsat ETM and field spectral measurement in Taihu Lake, China. International Journal of Remote Sensing, 26(13), 2779-2795.
Maalim, F. K., Melesse, A. M., Belmont, P., & Gran, K. B. (2013). Modeling the impact of land use changes on runoff and sediment yield in the Le Sueur watershed, Minnesota using GeoWEPP. Catena, 107, 35-45.
Mcqueen, A. D., & Suedel, B. C. (2018). Estimating turbidity near a dredge operation using a weather balloon-mounted camera. Western Dredging Association Dredging Summit & Expo '18.
Miller, R. L., & McKee, B. A. (2004). Using MODIS Terra 250 m imagery to map concentrations of total suspended matter in coastal waters. Remote sensing of Environment, 93(1-2), 259-266.
Moges, M. A., Zemale, F. A., Alemu, M. L., Ayele, G. K., Dagnew, D. C., Tilahun, S. A., & Steenhuis, T. S. (2016). Sediment concentration rating curves for a monsoonal climate: upper Blue Nile. Soil, 2(3), 337-349.
Park, E., & Latrubesse, E. M. (2014). Modeling suspended sediment distribution patterns of the Amazon River using MODIS data. Remote Sensing of Environment, 147, 232-242.
Pereira, L. S., Andes, L. C., Cox, A. L., & Ghulam, A. (2018). Measuring Suspended-Sediment Concentration and Turbidity in the Middle Mississippi and Lower Missouri Rivers Using Landsat Data. JAWRA Journal of the American Water Resources Association, 54(2), 440-450.
Pavelsky, T.M., Smith, L.C., 2009. Remote sensing of suspended sediment concentration, flow velocity, and lake recharge in the Peace-Athabasca Delta, Canada. Water Resour. Res. 45, 1–16.
Qu, L. (2014). Remote sensing suspended sediment concentration in the Yellow River. Retrieved from http://digitalcommons.uconn.edu/dissertations/383.
Ritchie, J.C., Schiebe, F.R., Mchenry, J.R., 1976. Remote sensing of suspended sediments in surface waters. Photogrammetric Engineering and Remote Sensing, 42(12), 1539-1545.
Ritchie, J. C., Cooper, C. M., & Yongqing, J. (1987). Using Landsat multispectral scanner data to estimate suspended sediments in Moon Lake, Mississippi. Remote Sensing of Environment, 23(1), 65-81.
Ritchie, J. C., & Cooper, C. M. (1991). An Algorithm for estimating surface suspended sediment concentrations with LANDSAT MSS digital data. JAWRA Journal of the American Water Resources Association, 27(3), 373-379.
Ritchie, G. L., Sullivan, D. G., Perry, C. D., Hook, J. E., & Bednarz, C. W. (2008). Preparation of a low-cost digital camera system for remote sensing. Applied Engineering in Agriculture, 24(6), 885-894.
Ritchie, J.C., Zimba, P. V., Everitt, J.H., 2013. Remote sensing techniques to assess water quality. Photogramm. Eng. Remote Sens. 69, 695–704.
Schiebe, F. R., Harrington Jr, J. A., & Ritchie, J. C. (1992). Remote sensing of suspended sediments: the Lake Chicot, Arkansas project. International Journal of Remote Sensing, 13(8), 1487-1509.
Sterckx, S., Knaeps, E., Bollen, M., Trouw, K., & Houthuys, R. (2007). Retrieval of suspended sediment from advanced hyperspectral sensor data in the Scheldt estuary at different stages in the tidal cycle. Marine Geodesy, 30(1-2), 97-108.
Subramanian, V. (1979). Chemical and suspended-sediment characteristics of rivers of India. Journal of Hydrology, 44(1-2), 37-55.
Ranjan Tripathy, B., Seenipandi, K., Sajjad, H., Joshi, P. K., Singh Chaudhary, B., & Kumar, P. (2018). Monitoring of seasonally variability and movement of suspended sediment concentration along Thiruvananthapuram coast using OLI sensor. Ocean Science Discussions, 2018, 1-16.
Robert, E., Grippa, M., Kergoat, L., Pinet, S., Gal, L., Cochonneau, G., & Martinez, J. M. (2016). Monitoring water turbidity and surface suspended sediment concentration of the Bagre Reservoir (Burkina Faso) using MODIS and field reflectance data. International Journal of Applied Earth Observation and Geoinformation, 52, 243-251.
Li, J., Tian, L., Song, Q., Huang, J., Li, W., Wei, A., 2019. A near-infrared band-based algorithm for suspended sediment estimation for turbid waters using the experimental Tiangong 2 moderate resolution wide-wavelength imager. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 12, 774–787.
Liew, S. C., Lu, X. X., Chen, P., & Zhou, Y. (2003, November). Remote sensing estimation of suspended sediment concentrations in highly turbid inland river waters: an example from the Lower Jinsha Tributary, Yunnan, China. In International Symposium on Remote Sensing of Environment. HI: Hawaii.
Tolk, B. L., Han, L., & Rundquist, D. C. (2000). The impact of bottom brightness on spectral reflectance of s0uspended sediments. International Journal of Remote Sensing, 21(11), 2259-2268.
Mobley, C.D., 1999. Estimation of the remote-sensing reflectance from above-surface measurements. Appl. Opt. 38, 7442–55.
Umar, M., Rhoads, B.L., Greenberg, J.A., 2018a. Use of multispectral satellite remote sensing to assess mixing of suspended sediment downstream of large river confluences. J. Hydrol., 556, 325–338.
Villar, R. E., Martinez, J. M., Guyot, J. L., Fraizy, P., Armijos, E., Crave, A., ... & Lavado, W. (2012). The integration of field measurements and satellite observations to determine river solid loads in poorly monitored basins. Journal of Hydrology, 444, 221-228.
Warrick, J. A., Mertes, L. A. K., Siegel, D. A., & Mackenzie, C. (2004). Estimating suspended sediment concentrations in turbid coastal waters of the Santa Barbara Channel with SeaWiFS. International Journal of Remote Sensing, 25(10), 1995-2002.
Wang, F., Zhou, B., Liu, X., Zhou, G., & Zhao, K. (2012). Remote-sensing inversion model of surface water suspended sediment concentration based on in situ measured spectrum in Hangzhou Bay, China. Environmental Earth Sciences, 67(6), 1669-1677.
Yepez, S., Laraque, A., Martinez, J. M., De Sa, J., Carrera, J. M., Castellanos, B., ... & Lopez, J. L. (2018). Retrieval of suspended sediment concentrations using Landsat-8 OLI satellite images in the Orinoco River (Venezuela). Comptes Rendus Geoscience, 350(1-2), 20-30.
Yesuf, H. M., Assen, M., Alamirew, T., & Melesse, A. M. (2015). Modeling of sediment yield in Maybar gauged watershed using SWAT, northeast Ethiopia. Catena, 127, 191-205.
Information & Authors
Information
Published In
World Environmental and Water Resources Congress 2020: Emerging and Innovative Technologies and International Perspectives
Pages: 40 - 50
Editors: Sajjad Ahmad, Ph.D., and Regan Murray, Ph.D.
ISBN (Online): 978-0-7844-8294-0
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: May 14, 2020
Published in print: May 14, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.