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Water remote sensing
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<h2 id="overview">Overview</h2> <p>Water remote sensing instruments (sensors) allow scientists to record the color of a water body, which provides information on the presence and abundance of optically active natural water components (plankton, sediments, detritus, or dissolved substances). The water color spectrum as seen by a satellite sensor is defined as an apparent optical property (AOP) of the water. This means that the color of the water is influenced by the angular distribution of the light field and by the nature and quantity of the substances in the medium, in this case, water.<a class="footnote-ref" id="fnref:3" href="#fn:3"><sup>3</sup></a> Thus, the values of remote sensing reflectance, an AOP, will change with changes in the optical properties and concentrations of the optically active substances in the water. Properties and concentrations of substances in the water are known as the inherent optical properties or IOPs.<a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a> IOPs are independent from the angular distribution of light (the "light field") but they <i>are</i> dependent on the type and amount of substances that are present in the water.<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a> For instance, the diffuse <a href="/facts/Attenuation_coefficient/ppCIsSGw">attenuation coefficient</a> of downwelling irradiance, Kd (often used as an index of water clarity or <a href="/facts/Ocean_turbidity/CAmx1dEj">ocean turbidity</a>) is defined as an AOP (or quasi-AOP), while the <a href="/facts/Absorption_coefficient/ppCIsSGw">absorption coefficient</a> and the <a href="/facts/Scattering/nMou7lEH">scattering</a> coefficient of the water are defined as IOPs.<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a> There are two different approaches to determine the concentration of optically active water components by the study of spectra, distributions of light energy over a range of wavelengths or colors. The first approach consist of empirical algorithms based on statistical relationships. The second approach consists of analytical algorithms based on the inversion of calibrated bio-optical models.<a class="footnote-ref" id="fnref:7" href="#fn:7"><sup>7</sup></a><a class="footnote-ref" id="fnref:8" href="#fn:8"><sup>8</sup></a> Accurate calibration of the relationships and/or models used is an important condition for successful inversion on water remote sensing techniques and the determination of concentration of water quality parameters from observed spectral remote sensing data.<a class="footnote-ref" id="fnref:9" href="#fn:9"><sup>9</sup></a> Thus, these techniques depend on their ability to record these changes in the spectral signature of light backscattered from water surface and relate these recorded changes to water quality parameters via empirical or analytical approaches. Depending on the water constituents of interest and the sensor used, different parts of the spectrum will be analyzed.<a class="footnote-ref" id="fnref:10" href="#fn:10"><sup>10</sup></a> </p> <h2 id="history">History</h2> <p>The gradual development of understanding of the transparency of natural waters and of the reason of their clarity variability and coloration has been sketched from the times of Henry Hudson (1600) to those of Chandrasekhara Raman (1930).<a class="footnote-ref" id="fnref:11" href="#fn:11"><sup>11</sup></a> However, the development of water remote sensing techniques (by the use of satellite imaging, aircraft or close range optical devices) didn't start until the early 1970s. These first techniques measured the <a href="/facts/Electromagnetic_spectrum/24LARvFY">spectral</a> and thermal differences in the emitted energy from water surfaces. In general, empirical relationships were settled between the spectral properties and the water quality parameters of the water body.<a class="footnote-ref" id="fnref:12" href="#fn:12"><sup>12</sup></a> In 1974, Ritchie et al. (1974) <a class="footnote-ref" id="fnref:13" href="#fn:13"><sup>13</sup></a> developed an empirical approach to determine suspended sediments. This kind of empirical models are only able to use to determine water quality parameters of water bodies with similar conditions. In 1992 an analytical approach was used by Schiebe et al. (1992).<a class="footnote-ref" id="fnref:14" href="#fn:14"><sup>14</sup></a> This approach was based on the optical characteristics of water and water quality parameters to elaborate a physically based model of the relationship between the spectral and physical properties of the surface water studied. This physically based model was successfully applied in order to estimate suspended sediment concentrations.<a class="footnote-ref" id="fnref:15" href="#fn:15"><sup>15</sup></a><a class="footnote-ref" id="fnref:16" href="#fn:16"><sup>16</sup></a><a class="footnote-ref" id="fnref:17" href="#fn:17"><sup>17</sup></a><a class="footnote-ref" id="fnref:18" href="#fn:18"><sup>18</sup></a> </p> <h2 id="applications">Applications</h2> <p>By the use of optical close range devices (e.g. <a href="/facts/Spectrometers/IqRE8xaQ">spectrometers</a>, <a href="/facts/Radiometers/TUexhkgT">radiometers</a>), airplanes or helicopters (airborne remote sensing) and satellites (space-borne remote sensing), the light energy radiating from water bodies is measured. For instance, algorithms are used to retrieve parameters such as <a href="/facts/Chlorophyll-a/j6JUP1oS">chlorophyll-a</a>(Chl-a) and Suspended Particulate Matter (SPM) concentration, the absorption by <a href="/facts/Colored_dissolved_organic_matter/D1kE1rMn">colored dissolved organic matter</a> at 440 nm (aCDOM) and <a href="/facts/Secchi_depth/cazzJ1sX">secchi depth</a>.<a class="footnote-ref" id="fnref:19" href="#fn:19"><sup>19</sup></a> The measurement of these values will give an idea about the water quality of the water body being studied. A very high concentration of green pigments like chlorophyll might indicate the presence of an algal bloom, for example, due to eutrophication processes. Thus, the chlorophyll concentration could be used as a proxy or indicator for the trophic condition of a water body. In the same manner, other optical quality parameters such as suspended particles or Suspended Particulate matter (SPM), Colored Dissolved Organic Matter (CDOM), Transparency (Kd), and chlorophyll-a (Chl-a) can be used to monitor water quality.<a class="footnote-ref" id="fnref:20" href="#fn:20"><sup>20</sup></a> </p><h2 id="see-also">See also</h2> <ul><li><a href="/facts/Ocean_color/Jcae25cJ">Ocean color</a></li> <li><a href="/facts/Ocean_optics/Pq8cajWg">Ocean optics</a></li></ul> <h2 id="external-links">External links</h2> <ul><li><a href="http://www.eulakes.eu/servizi/notizie/notizie_homepage.aspx/">EULAKES project, water quality by remote sensing technique</a></li> <li><a href="http://www.coastcolour.org/">CoastColour project: remote sensing of the coastal zone</a></li> <li><a href="http://www.brockmann-consult.de/revamp/">Revamp project: Regional Validation of MERIS Chlorophyll products in North Sea Coastal Waters</a></li> <li><a href="http://www.geo.mtu.edu/great_lakes/lakersi/cgi-bin/rsi_kitie/template1.html/">The Great Lakes Web Site: Michigan Tech's Large Lakes Remote Sensing program</a></li> <li><a href="http://www.coastwatch.msu.edu/">CoastWatch project</a></li> <li><a href="http://www.ioccg.org/">International Ocean Colour Coordinating Group</a></li> <li><a href="http://www.esa.int/Our_Activities/Observing_the_Earth/">ESA European Space Agency activities: Observing the Earth</a></li> <li><a href="https://oceancolor.gsfc.nasa.gov/">Ocean Color Web</a></li> <li><a href="http://www.sciencedirect.com/science/article/pii/S004896971100444X/">Assessing remotely sensed chlorophyll-a for the implementation of the Water Framework Directive in European perialpine lakes</a></li></ul> <h2 id="references">References</h2> <ol> <li id="fn:1"><p>Laanen, M.L. (2007)."Yellow Matters- Improving the remote sensing of Coloured Dissolved Organic Matter in inland freshwaters Archived 2018-11-13 at the Wayback Machine" Ph.D. Thesis. Vrije Universiteit Amsterdam: The NL. <a href="http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun" target="_blank">http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li> <li id="fn:2"><p>Laanen, M.L. (2007)."Yellow Matters- Improving the remote sensing of Coloured Dissolved Organic Matter in inland freshwaters Archived 2018-11-13 at the Wayback Machine" Ph.D. Thesis. Vrije Universiteit Amsterdam: The NL. <a href="http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun" target="_blank">http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li> <li id="fn:3"><p>IOCCG (2000). Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex Waters. Sathyendranath, S. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 3, IOCCG, Dartmouth, Canada. <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li> <li id="fn:4"><p>Laanen, M.L. (2007)."Yellow Matters- Improving the remote sensing of Coloured Dissolved Organic Matter in inland freshwaters Archived 2018-11-13 at the Wayback Machine" Ph.D. Thesis. Vrije Universiteit Amsterdam: The NL. <a href="http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun" target="_blank">http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li> <li id="fn:5"><p>IOCCG (2000). Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex Waters. Sathyendranath, S. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 3, IOCCG, Dartmouth, Canada. <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li> <li id="fn:6"><p>IOCCG (2000). Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex Waters. Sathyendranath, S. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 3, IOCCG, Dartmouth, Canada. <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li> <li id="fn:7"><p>Laanen, M.L. (2007)."Yellow Matters- Improving the remote sensing of Coloured Dissolved Organic Matter in inland freshwaters Archived 2018-11-13 at the Wayback Machine" Ph.D. Thesis. Vrije Universiteit Amsterdam: The NL. <a href="http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun" target="_blank">http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun</a> <a href="#fnref:7" class="footnote-back-ref">↩</a></p></li> <li id="fn:8"><p>IOCCG (2000). Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex Waters. Sathyendranath, S. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 3, IOCCG, Dartmouth, Canada. <a href="#fnref:8" class="footnote-back-ref">↩</a></p></li> <li id="fn:9"><p>Laanen, M.L. (2007)."Yellow Matters- Improving the remote sensing of Coloured Dissolved Organic Matter in inland freshwaters Archived 2018-11-13 at the Wayback Machine" Ph.D. Thesis. Vrije Universiteit Amsterdam: The NL. <a href="http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun" target="_blank">http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun</a> <a href="#fnref:9" class="footnote-back-ref">↩</a></p></li> <li id="fn:10"><p>Ritchie, J.C; Zimba, P.V.; Everitt, J.H. (2003), “Remote Sensing Techniques to Assess Water Quality”, American Society for Photogrammetry Engineering and Remote Sensing, 69:695-704. <a href="#fnref:10" class="footnote-back-ref">↩</a></p></li> <li id="fn:11"><p>Marcel, R., Wernand & Winfried W.C.Gieskes (2012), "Ocean Optics from 1600 (Hudson) to 1930 (Raman) Shifting interpretation of natural water colouring", Paris, France: Union des oceanographes de France (published 1 January 2012) <a href="#fnref:11" class="footnote-back-ref">↩</a></p></li> <li id="fn:12"><p>Ritchie, J.C; Zimba, P.V.; Everitt, J.H. (2003), “Remote Sensing Techniques to Assess Water Quality”, American Society for Photogrammetry Engineering and Remote Sensing, 69:695-704. <a href="#fnref:12" class="footnote-back-ref">↩</a></p></li> <li id="fn:13"><p>Ritchie, J.C.; McHenry, J.R.; Schiebe, F.R.; Wilson, R.B.(1974),“The relationship of reflected solar radiation and the concentration of sediment in the surface water of reservoirs”,Remote Sensing of Earth Resources Vol. III (F. Shahrokhi, editor),The University of Tennessee Space Institute, Tullahoma, Tennessee,3:57–72 <a href="#fnref:13" class="footnote-back-ref">↩</a></p></li> <li id="fn:14"><p>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 <a href="#fnref:14" class="footnote-back-ref">↩</a></p></li> <li id="fn:15"><p>Ritchie, J.C; Zimba, P.V.; Everitt, J.H. (2003), “Remote Sensing Techniques to Assess Water Quality”, American Society for Photogrammetry Engineering and Remote Sensing, 69:695-704. <a href="#fnref:15" class="footnote-back-ref">↩</a></p></li> <li id="fn:16"><p>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 <a href="#fnref:16" class="footnote-back-ref">↩</a></p></li> <li id="fn:17"><p>Harrington, J.A., Jr., Schiebe, F.R.; Nix, J.F. (1992). “Remote sensing of Lake Chicot, Arkansas: Monitoring suspended sediments, turbidity and secchi depth with Landsat MSS”, Remote Sensing of Environment, 39(1):15–27 <a href="#fnref:17" class="footnote-back-ref">↩</a></p></li> <li id="fn:18"><p>"Water quality forecasting: social media learning machines". Retrieved 24 August 2021. <a href="http://www.waterforecast.net" target="_blank">http://www.waterforecast.net</a> <a href="#fnref:18" class="footnote-back-ref">↩</a></p></li> <li id="fn:19"><p>Laanen, M.L. (2007)."Yellow Matters- Improving the remote sensing of Coloured Dissolved Organic Matter in inland freshwaters Archived 2018-11-13 at the Wayback Machine" Ph.D. Thesis. Vrije Universiteit Amsterdam: The NL. <a href="http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun" target="_blank">http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun</a> <a href="#fnref:19" class="footnote-back-ref">↩</a></p></li> <li id="fn:20"><p>Laanen, M.L. (2007)."Yellow Matters- Improving the remote sensing of Coloured Dissolved Organic Matter in inland freshwaters Archived 2018-11-13 at the Wayback Machine" Ph.D. Thesis. Vrije Universiteit Amsterdam: The NL. <a href="http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun" target="_blank">http://dare.ubvu.vu.nl/bitstream/handle/1871/10799/8066.pdf?sequence=5Jun</a> <a href="#fnref:20" class="footnote-back-ref">↩</a></p></li> </ol>