Suspended sediment is an important environmental parameter for monitoring water quality, water movement, and land use. Quantitative suspended sediment determinations were made from analysis of aircraft remotely sensed multispectral digital data. A statistical analysis and derived regression equation were used to determine and plot quantitative suspended sediment concentration contours in the tidal James River, Virginia, on May 28, 1974. From the analysis, a single band, Band 8 (0.70-0.74 microns), was adequate for determining suspended sediment concentrations. A correlation coefficient of 0.89 was obtained with a mean inaccuracy of 23.5 percent for suspended sediment concentrations up to about 50 mg/l. Other water quality parameters - secchi disc depth and chlorophyll - also had high correlations with the remotely sensed data. Particle size distribution had only a fair correlation with the remotely sensed data

Johnson, R. W.

English

NASA Technical Reports Server

QUANTITATIVE SUSPENDED SEDIMENT MAPPING USING M-11
AIRCRAFT REMOTELY SENSED MULTISPECTRAL DATA
By Robert W. Johnson, NASA Langley Research Center, Hampton, Virginia
ABSTRACT
Suspended sediment is an important environmental parameter for monitoring water
quality, water movement, and land use. Quantitative suspended sediment determinations
have been made from analysis of aircraft remotely sensed multispectral digital data. A
statistical analysis and derived regression equation were used to determine and plot
quantitative suspended sediment concentration contours in the tidal James River, Virginia,
on May 28, 1974. From the analysis, a single band, Band 8 (0.70-0.74 microns), was ade-
quate for determining suspended sediment concentrations. A correlation coefficient of
0.89 was obtained with a mean inaccuracy of 23.5 percent for suspended sediment concentra-
tions up to about 50 mg/&. Other water quality parameters - secchi disc depth and chloro-
phyll - also had high correlations with the remotely sensed data. Particle size distribu-
tions had only a fair correlation with the remotely sensed data.
INTRODUCTION
Suspended sediment is an important environmental parameter for monitoring water
quality, water movement, and land use in river water sheds and filling rates in reservoirs.
Uncontrolled sediment runoff reduces the depth of the photic zone and therefore the volume
of water in which photosynthesis (oxygen production) can take place. Suspended sediment
has also been recognized as a natural tracer that may be used to measure flow and distri-
butions in a water body, thereby providing information on pollutant concentrations and
dispersions. In addition, high sediment loads may be indicative of harmful erosion of
nearby land areas and/or high filling rates in reservoir systems.
Williamson and Grabau (ref. 1) and Klemas, et al. (ref. 2) analyzed LANDSAT multi-
spectral scanner data and determined suspended sediment concentration categories in the
areas of water analyzed. A typical water category had sediment concentrations from 15 to
25 mg/&. Johnson (ref. 3) applied a continuous function analysis to develop a regression
equation to determine sediment concentrations for each pixel. By this latter procedure it
was possible to determine and plot quantitative suspended sediment concentration contours
as shown in figure 1, which is taken from reference 3.
It is the purpose of this investigation to apply the methodology of reference 3 to
aircraft multispectral scanner data to quantitatively determine suspended sediment concen-
trations in a turbid tidal river system. In addition, other water quality parameters such
as chlorophyll, secchi disc depth and particles will be investigated for correlations among
themselves and with the digital multispectral scanner data.
EXPERIMENTAL METHOD
Remotely sensed data were collected in conjunction with ground truth measurements over
the Norfolk and James River, Virginia, areas on May 28, 1974. Remotely sensed data were
collected from about 1015 to 1135 hours e.d.t. by a Bendix Modular Multispectral Scanner
(M2S) from a flight altitude of 8000 feet (2.4 km). Ground.truth measurements were made
from seven boats at three sites; Norfolk, Hopewell, and Hog Island. Three boats were
located at each of the first two sites, Norfolk and Hopewell, and one boat was used at Hog
Island. In situ measurements were made and water samples taken for subsequent laboratory
2087
https://ntrs.nasa.gov/search.jsp?R=19760010496 2020-03-22T16:15:36+00:00Z
determinations at 20-minute intervals from about 0935 to 1235 hours e.d.t. A wide range
of water parameters were measured. This investigation will consider suspended sediment,
secchi disc depth, chlorophyll, and particle size distributions.
Remotely sensed data were collected by an 11-band (10 bands in the visible and near IR
and one thermal band) multispectral scanner (Bendix M2S). Bandwidths and frequencies are
listed in table I, along with spatial coverage information at the flight altitude. Pixel
size and resolution are about 25 feet (7 m). Multispectral scanner imagery in Band 5
(0.58-0.62y) over the test areas is shown in figure 2.
Digital data in the visible and near IR frequencies were analyzed using statistical
regression techniques to develop an equation for quantitatively determining suspended
sediment concentrations. In the analysis, suspended sediment concentration (mg/£) is the
dependent variable and the 10 bands of remotely sensed data (mw/cm^-ster) are the inde-
pendent variables. Correlation among the M2S bands and with suspended sediment is
generally high except for widely separated bands, as shown in the linear correlation matrix,
table II. Individual band correlations'with suspended sediment are high for Bands 4
through 9 which cover a frequency range from 0.54 to 0.86)j, with Band 8 (0.70-0.74y) the
highest with a correlation coefficient of 0.89.
To develop a better assessment of the data set, a stepwise regression analysis (SRA)
technique was applied to the data. In an SRA the program will determine the one independ-
ent variable (radiance) that provides the best statistical correlation with the dependent
variable (suspended sediment concentration), then in successive steps determines a second
variable to be added that improves the multiple correlation and so on until all of the
independent variables have been included in the correlation. The first step provides
information on the best single band. Additional steps provide a measure of the improvement
as successive information (bands) are added.
. Results of the analysis are shown below.
Independent Std. error Regression
variable Regression of estimate correlation
Step added variables mg/& coefficient
1 R8 ! R8 4.76 0.888
2 Rl R8, Rl 4.68 .896
3 R6 R8, Rl, R6 4.58 .903
10 RIO All 4.31 .927
9
where RN is radiance (raw/cm -ster) from the M2S in Band N (i.e., R8 is the radiance in
Band 8). Standard error of estimate is the statistical standard deviation in mg/£. Regres-
sion correlation coefficient is a measure of the relative responses, of the variables with a
maximum value of unity, • -
To test the assumed linear regression equation, residuals (deviations from the fitted
regression line).were plotted as a function of sediment concentration, figure 3. Since
the variation of residuals occurred approximately randomly the linear equation appears to
be adequate. Johnson (ref. 3) arid McCauley and Yarger (re-f. 4) have previously indicated
linear response of suspended sediment concentrations with radiance in this range of values.
A one-parameter (Band; 8) Degression equation was used for the determination of sus-
pended sediment since the addition of other variables (M2S bands) does not make a signif-
icant imprpvemeiit (based on reduction in sum of squares^for 95-percent confidence level^
e.g., p. 455,-ref. 5) for this particular data set. The resultant equation for a single .>-•
band regression, is ; , , .' ..-
• / - • ' . • . " " . " • " . : ' " _ "
-" ' • 2088 . .. :' ! ••'-...:".' :.- / . •.'••:.;•; ',- • X
Suspended sediment concentration (mg/£) = -88.80 + 600.00R8
Estimated mean inaccuracy using the above equation is about 23.5 percent (standard error
of estimate 4.76 mg/& and an average sediment concentration of 20.22 mg/£). Sediment
concentrations range up to about 50 mg/&. Suspended sediment concentrations, Band 8
response, and the fitted regression line are shown in figure 4.
Quantitative values of suspended sediment concentrations may be used to determine and
plot contours of equal concentrations in the study area. Contours in the upper James River
near Hopewell are shown in figure 5. Comparison with the same area in figure 2 indicates
the same suspended sediment characteristics; however, the contour plots provide quantita-
tive values of suspended sediment concentrations, rather than relative (or qualitative)
measures.
In addition to suspended sediment concentrations, ground truth measurements included
other water quality parameters: chlorophyll a_, secchi disc, and particle size distribu-
tions. The latter were determined from the Langley computerized particulate counter
(Millipore TTMC). Correlations among these parameters are shown in a correlation matrix
(table III). Poor correlations were obtained for very small particles (less than 1 micron).
Relatively good correlations with suspended sediment were obtained for small to medium
size (1.0 to 4.0)j) and for total particles. This correlation is not as good as might be
expected under the good conditions for sediment resuspension - shallow water areas on each
side of the channel, fresh water outflow combined with ebb tide over the data collection
period, and a 15- to 20-knot wind blowing down the river. A high correlation (negative
sign indicates inverse relationship) was obtained between secchi disc depth and suspended
sediment concentration as expected. The high correlation between chlorophyll a_ and sus-
pended sedimen,t concentrations, in addition to the essentially parallel response to sus-
pended sediment concentrations in the particle distributions, indicates that this may be
a parallel correlation with particles; however, the analysis technique provides separa-
tion of chlorophyll in this particular set of data. Day-to-day correlations of chloro-
phyll that did not show a high correlation as grouped data have been previously observed
by Bowker and Witte (ref. 6) in their analysis of LANDSAT data from the Chesapeake Bay. •
Further analysis of the chlorophyll _a data was obtained by taking chlorophyll as the
dependent variable and multispectral responses as the independent variables, as was done
for suspended sediment. Again, the stepwise regression approach was followed. Results
of the analysis were • ' *
Independent
variable
added
Regression
variables
Std. error
of estimate,
mg/M
Regression
correlation
coefficient
1
2
3
4
5
10
R8 -R8 2.64
R2 R8,R2 1.88
R4 R8,R2,R4 1.70
R9 R8,R2,R4,R9 1.62
R5 R8,R2,R4,R9,R5 1.60
0
0
0
R4 ' All 1.56
0.89
.95
.96
.96
.97.
.97
where the statistical parameters are the same as previously defined.
The mean inaccuracy of chlorophyll determinations from the regression equation (for
3
a mean chlorophyll concentration of 6.9 mg/M ) varies from about 36 percent for a one-
parameter equation to about 22 percent for a regression equation of three variables. It is
2089
interesting that the two most significant variables, R8 and R2, are essentially the same
as for the sediment correlation (R8 and Rl for sediment), thus, it appears, as noted above,
that the correlation of chlorophyll with multispectral response is related to the particle
response.
CONCLUDING REMARKS
Multispectral scanner digital data have been analyzed to develop a regression equation
for determining suspended sediment concentrations. A linear equation using one band,
Band 8 (0.70-0.74p) , appears to be adequate "for in-scene analysis for this particular data
set although addition of other bands marginally improves the correlation -coefficient and
in most cases mean inaccuracy is less. Mean error associated with application of the
regression equation to determining suspended sediment concentration contours is 23.5 per-
cent for sediment concentrations up to about 50 mg/£. Variations of equal or greater mag-
nitude might be expected from measurement and spatial inaccuracies due to ground truth
measurement and/or spectral inaccuracies due to particle composition and size distributions.
Analysis of additional water quality parameters - chlorophyll a_, secchi disc depth, and
particle size distributions - indicates the multispectral scanner data are "suspended sedi-
ment dominated," thus it is difficult to analyze for other materials. A high correlation
was obtained between chlorophyll a_ and multispectral scanner data; this appears
to be due to particles that contain chlorophyll, rather than chlorophyll per se and the
specific relationship is probably limited to this set of data.
Additional remotely sensed data in conjunction with"ground truth from a number of
environmentally different areas will be required to further define the accuracy of and
conditions under which regression equations for quantitative analysis of digital-multi-
spectral data may be applied.
REFERENCES
1. Williamson, A. N., and W. E. Grabau. Sediment Concentration Mapping in Tidal Estuaries.
Third Earth Resources Technology Satellite-1 Symposium, Washington, D.C., December 10-14,
1973.
2. Klemas, V., M. Otley, W. Philpot, C. Wethet and R. Rogers. Correlation of Coastal Water
Turbidity and Circulation with ERTS-1 and Skylab Imagery. Presented at the Ninth
International Symposium on Remote Sensing of Environment, Univ. of Michigan, Ann Arbor,
Michigan, April 15-19, 1974.
3. Johnson, Robert W. Quantitative Sediment Mapping from Remotely Sensed Multispectral
data. Presented at the Fourth Annual Remote Sensing of Earth Resources Conference,
March 24-26, 1975, Tullahoma, Tennessee.
4. McCauley, James, and Harold Yarger. Kansas Water Quality Using ERTS-1. Presented at
the Fourth Annual Remote Sensing of Earth Resources Conference, March 24-26, 1975,
Tullahoma, Tennessee.
5. Snedecor, George W., and William G. Cochran. Statistical Methods. Sixth Edition, The
Iowa State University Press, Ames, Iowa, 1967.
6. Bowker, David E., and William Witte. Evaluation of ERTS MSS Digital Data for Monitor-
ing Water in the Lower Chesapeake Bay Area. Presented at the Fourth Annual Remote
Sensing of Earth Resources Conference, March 24-26, 1975, Tullahoma, Tennessee.
2090
Table I. Multispectral Scanner (M2S) Bahdwidths and Frequencies, and
Spatial Coverage at 8000-Foot (2.4 km) Altitude.
MAY 28,1974
SPECTRAL
RANGE
BANDS
FIELD OF VIEW
WIDTH. M
LENGTH, M
RESOLUTION, M
380-1060 nm
+ THERMAL
BAND RANGE
1
2
3
4
5
6
7
8
9
10
THERMAL
380
440
495
540
580
620
660
700
760
970
8000
- 440 nm
- 490 nm
- 535 nm
- 580 nm
- 620 nm
- 660 nm
- 700 nm
- 740 nm
- 860 nm
- 1060 nm
- 13 000 nm
SPATIAL
6800
CONTINUOUS
7
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Figure 1. Suspended sediment weight contours for Potomac River,
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2096
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Figure 4. Suspended sediment concentrations, M2S Band 8 radiances and
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2097
Figure 5. Quantitative suspended sediment contours in the upper James
River near Hopewell, May 28, 1974.
2098


Quantitative suspended sediment mapping using aircraft remotely sensed multispectral data

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