U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2009–5162

Table Rock Lake Water-Clarity Assessment 

Using Landsat Thematic Mapper Satellite Data
Cover illustration. Landsat satellite image from the Table Rock 

Lake area, southwestern Missouri and northwestern Arkansas.
Table Rock Lake Water-Clarity Assessment

Using Landsat Thematic Mapper Satellite 

Data 

By Gary W. Krizanich and Michael P. Finn

Scientific Investigations Report 2009–5162

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2009

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Suggested citation:

Krizanich, G. W., and Finn, M. P., 2009, Table Rock Lake water-clarity assessment using landsat thematic mapper 

satellite data: U.S. Geological Survey Scientific Investigations Report 2009-5162, 9 p.
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Purpose and Scope ..............................................................................................................................1

Background............................................................................................................................................1

Study Area..............................................................................................................................................3

Methods...........................................................................................................................................................3

Results .............................................................................................................................................................6

Summary..........................................................................................................................................................8

Acknowledgments.........................................................................................................................................8

References Cited............................................................................................................................................8

Figures

1–2. Maps showing:

 1. Study area location ...............................................................................................................2

 2. Table Rock Lake sample locations......................................................................................3

3–4. Graphs showing: 

 3. Relation between predicted and measured values of secchi depth in meters for 

Table Rock Lake. ....................................................................................................................5

 4. Distribution of field samples with respect to number of days within satellite 

overpass..................................................................................................................................6

5–6. Maps showing: 

 5. Model predicted trophic state for Table Rock Lake – August 2003. .............................7

 6. Temporal comparison of model results for the James River arm of Table Rock 

Lake..........................................................................................................................................7

Tables

1. Mean Landsat brightness values for Table Rock Lake sample sites 2003 and 2005 .........4
iv

Conversion Factors, Abbreviations, and Datums

Inch/Pound to SI

Multiply By To obtain

Length

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2) 

acre 0.004047 square kilometer (km2)

SI to Inch/Pound

Multiply By To obtain

Length

meter (m) 3.281 foot (ft) 

Area

square meter (m2) 0.0002471 acre 

hectare (ha) 2.471 acre

square hectometer (hm2) 2.471 acre

square kilometer (km2) 247.1 acre

Vertical coordinate information is referenced to the North American Vertical Datum

of 1988 (NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 

(NAD 83).

Altitude, as used in this report, refers to distance above the vertical datum.
Table Rock Lake Water-Clarity Assessment 

Using Landsat Thematic Mapper Satellite Data

By Gary W. Krizanich and Michael P. Finn

Abstract 

Water quality of Table Rock Lake in southwestern Missouri is assessed using Landsat Thematic Mapper satellite 

data. A pilot study uses multidate satellite image scenes in 

conjunction with physical measurements of secchi disk transparency collected by the Lakes of Missouri Volunteer Program 

to construct a regression model used to estimate water clarity. 

The natural log of secchi disk transparency is the dependent 

variable in the regression and the independent variables are 

Thematic Mapper band 1 (blue) reflectance and a ratio of the 

band 1 and band 3 (red) reflectance. The regression model can 

be used to reliably predict water clarity anywhere within the 

lake. A pixel-level lake map of predicted water clarity or computed trophic state can be produced from the model output. 

Information derived from this model can be used by waterresource managers to assess water quality and evaluate effects 

of changes in the watershed on water quality.

Introduction

Table Rock Lake is a primary water resource located 

in southwestern Missouri with tourism related activities 

within the watershed accounting for more than a billion dollars in revenue each year (Missouri Department of Natural 

Resources, 2005). Decreasing water clarity in Table Rock 

Lake has caused concern with water-resource managers and 

private watershed groups. The reservoir was listed in 2002, 

in accordance with section 303(d) of the Federal Clean Water 

Act, as having impaired water quality because of nutrient 

enrichment. Long-term monitoring of the reservoir by University of Missouri researchers documents an increase in nutrients 

and chlorophyll with a corresponding decrease in water clarity 

over the past 20 years (Jones and Perkins, 1999). Increases 

in nitrogen and phosphorus inputs to the reservoir have been 

attributed to point and nonpoint sources, with major contributions from wastewater treatment, urban storm water, and agricultural runoff (Missouri Department of Natural Resources, 

2005). This report evaluates a remote sensing methodology 

for predicting water quality using satellite reflectance data and 

water clarity measured by secchi disk transparency.

Purpose and Scope

The purpose of this report is to describe the methods and 

techniques used to develop a predictive model for estimating 

Table Rock Lake water quality based on satellite observations 

combined with field-data collection. The techniques described 

can be used to calculate estimates of water clarity from secchi 

disk transparency or a lake trophic state index derived from 

these measurements. Model outputs can be applied to the 

entire water body enabling water-resource managers to identify areas of potential concern.

Background

Eutrophication is the process of organic enrichment of 

lake water with respect to time (Wetzel, 2001). It is a natural aging process experienced by all lakes. Nutrient supplies 

primarily are derived from atmospheric and terrestrial sources, 

the latter being more significant with runoff being the principal 

source of nutrients in lakes. Increased levels of nutrients result 

in increased biological productivity, which can have harmful 

effects to water supplies. 

Trophic state is a measure of a lake’s productivity and 

is commonly used to assess water quality. Eutrophy is a state 

of high nutrient enrichment usually associated with declining water quality. The Carlson trophic state index (1977) is a 

numeric index commonly used for trophic state assessment of 

lakes, and is based on the relation between algal biomass and 

secchi disk transparency depth. The index ranges from 0 to 

100 with each increase of 10 units on the trophic state index 

equivalent to a doubling of algal biomass and can be computed 

from chlorophyll a concentration, total phosphorus concentration, or secchi disk transparency values. 

Remote sensing methods can be effective for waterquality monitoring and water-resource assessments (Ritchie 

and others, 2003). Advantages include multispectral band 

capabilities, repetitive coverage, a historical archive dating 

from the early 1970s, and the ability to cover large geographic 

areas with a single image scene. Early studies by Boland 
2 Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data

(1976) and Wezernak and others (1976) utilized complex 

multivariate statistical techniques for computation of a trophic 

state index based on reflectance data obtained from Landsat 

Multispectral Scanner (MSS) data. Their studies found that 

secchi disk transparency and chlorophyll a concentration could 

be used in conjunction with Landsat mean reflectance values 

to accurately predict lake trophic state. Increased spatial and 

radiometric resolution of the Thematic Mapper (TM) sensor 

provided improved accuracy of water-quality models derived 

from satellite observations (Lathrop and Lillesand, 1986). The 

empirical relation between secchi disk depth measurements 

and Landsat TM reflectance has been used to predict regionwide lake water clarity (Chipman and others, 2004; Fuller and 

others, 2004). Previous studies of Ozark lakes have shown that 

Landsat MSS and TM data can be effective in predicting water 

quality based on regression models developed from chlorophyll a and secchi disk depth data (Krizanich, 1986; Allee and 

Johnson, 1999).

Figure 1. Study area location.

95° 90°

40°

35°

0 25 50 75 100 MILES

0 25 50 75 100 KILOMETERS

Table Rock Lake

Missouri

Arkansas

Base from Environmental Systems Research Institute digital data, 1983

Universal Transverse Mercator projection, zone 15

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83)
Methods 3

Study Area

Table Rock Lake, located in southwestern Missouri and 

northwestern Arkansas (fig. 1), is a U.S. Army Corps of Engineers reservoir completed in 1959 to provide flood control 

and power generation in the Upper White River Basin. The 

reservoir has a surface area of 43,100 acres with 745 miles of 

shoreline. It is one of four reservoirs impounding the White 

River with Beaver Lake immediately upstream and Lake 

Taneycomo and Bull Shoals Lake downstream. Table Rock 

Lake is located within the Springfield Plateau of the Ozark 

Dome, an area dominated by relatively flat-lying carbonate 

rocks. Land cover of the area is predominantly forest and pasture, but increasing urban development within the watershed 

has the potential to affect water quality (Thorpe and others, 

2005). 

Methods

Two Landsat 5 Thematic Mapper scenes (8/22/2003, 

8/11/2005) were purchased from the Earth Resources Observation and Science (EROS) center in Sioux Falls, South Dakota. 

Landsat images were formatted as GeoTIFF and projected 

to Universal Transverse Mercator, North American Datum 

1983, Zone 15. Both scenes are from Worldwide Reference 

System 2 path 25, row 35 and were selected based on minimal scene cloud cover and closeness of the scene date to field 

data collection. The scenes were processed by EROS to level 

1P specifications, which include radiometric and geometric 

correction as well as the use of 25 ground-control points to 

improve geometric accuracy. 

93°40' 93°30' 93°20'

36°40'

36°30'

0 5 10 MILES

0 5 10 KILOMETERS

TR1

TR2 TR3

TR4.5

TR5

TR6.5

TR7 TR8

TR9

TR10

TR11

TR12

TR12

TR13

TR14

TR17

TR15

TR16 TR18

Data collection site and identifier 

 used in table 1

U.S. Geological Survey 1:24,000 National Hydrography Dataset, 1999 

Universal Transverse Mercator projection, zone 15

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83)

Figure 2. Table Rock Lake sample locations. Red dots indicate Lakes of Missouri Volunteer Program data collection sites.
4 Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data

Water-quality data were obtained from the Lakes of 

Missouri Volunteer Program (LMVP). This program consists 

of citizen volunteers who are trained to collect and process 

water samples from Missouri lakes. Volunteers monitor 

surface-water temperature, water clarity (secchi disk transparency), chlorophyll, total phosphorus, total nitrogen, and 

total suspended solids according to procedures established by 

LMVP (Obrecht, 1992). Samples are collected once every 3 

weeks between April and September for 18 sites (fig. 2) on 

Table Rock Lake. Repeat sampling is conducted by the same 

volunteer at each site with site occupation mostly dependent on aligning with visible landmarks. This method might 

Table 1. Mean Landsat brightness values for Table Rock Lake sample sites 2003 and 2005.

[TM1 and TM3, Thematic Mapper bands]

Data collection 

site (fig. 2)

Year Pixel 

count

TM1 TM3 TM1/TM3 Secchi 

(meters)

ln Secchi 

(meters)

TR1 2003 9 80 24 3.3 4.9 1.6

TR2 2003 9 80 23 3.4 4.0 1.4

TR3 2003 9 78 22 3.5 3.9 1.4

TR4.5 2003 9 78 23 3.4 2.7 1.0

TR5 2003 9 79 24 3.3 1.9 0.6

TR6.5 2003 9 82 27 3.1 1.5 0.4

TR8 2003 9 75 21 3.6 3.5 1.3

TR9 2003 9 82 27 3.1 2.4 0.9

TR10 2003 9 83 26 3.2 2.4 0.9

TR11 2003 9 79 26 3.1 1.1 0.1

TR12 2003 9 80 28 2.9 0.8 -0.3

TR13 2003 9 80 27 3.0 0.9 -0.1

TR14 2003 9 77 22 3.5 3.8 1.3

TR15 2003 9 78 24 3.3 3.2 1.2

TR16 2003 9 80 28 2.9 1.4 0.3

TR17 2003 9 79 23 3.4 3.0 1.1

TR18 2003 9 86 28 3.1 3.0 1.1

TR1 2005 9 66 17 3.8 4.1 1.4

TR2 2005 9 67 17 3.8 2.0 0.7

TR3 2005 9 65 16 4.0 3.6 1.3

TR4.5 2005 9 65 16 4.0 2.6 1.0

TR5 2005 9 64 18 3.6 1.3 0.3

TR6.5 2005 9 64 19 3.4 1.6 0.5

TR7 2005 9 62 19 3.3 0.7 -0.3

TR8 2005 9 65 18 3.6 1.0 0

TR9 2005 9 65 18 3.6 3.0 1.1

TR10 2005 9 67 18 3.8 3.6 1.3

TR11 2005 9 65 19 3.4 1.1 0.1

TR12 2005 9 67 23 3.0 0.8 -0.2

TR13 2005 9 66 20 3.3 0.8 -0.2

TR14 2005 9 64 16 4.1 4.0 1.4

TR15 2005 9 66 15 4.3 4.6 1.5

TR16 2005 9 72 25 2.8 1.0 0

TR17 2005 9 65 16 4.1 3.8 1.3

TR18 2005 9 65 16 4.0 5.4 1.7
Methods 5

account for some error in consistently occupying the same 

sample location, but most volunteers are local residents and 

have an intricate knowledge of their sampling locations. 

Processing of the satellite data was done using ERDAS 

Imagine software and modified from the procedures described 

by Olmanson and others (2001). The first step is to produce 

a water only image so that areas outside of the water body 

are eliminated from the analysis area. This is accomplished 

by performing an unsupervised classification on the Landsat 

image to differentiate water pixels from all others. The scene 

can then be recoded to create a binary image representing 

water and terrestrial areas. The water only image is further 

processed using an unsupervised classification to separate 

deep, open water areas from areas of the lake affected by 

vegetation, shoreline, or bottom effects. These areas should be 

avoided when choosing sample points in the satellite scene.

Sample sites for satellite signature acquisition were 

selected to coincide with the LMVP water-quality sites. A 3 

by 3 (9 pixel) area of interest (AOI) was created for each of 

the sample sites. The AOI size was determined based on a 

previous study by Kloiber and others (2002) that showed correlation strength improved with an increase in AOI size from 

1 to 9 pixels, but was marginal when the AOI was increased 

beyond 25 pixels. AOIs were centered over the LMVP sample 

site location and visual inspection performed to avoid areas 

with potential vegetation, shoreline, or bottom effects. Mean 

brightness values for each TM band were collected for each 

sample site AOI (table 1).

Regression analysis was performed using SPSS 14.0 for 

Windows (SPSS Inc., 2005). The following regression equation developed by Kloiber and others (2002) was used in the 

analysis of the two scene dates:

ln(SDT) = a(TM1/TM3) + bTM1 + c (1)

where

ln(SDT) is the natural log of secchi disk transparency 

depth, in meters, computed from the 

LMVP water quality data;

a, b, and c are the coefficients derived from the 

regression analysis; and

TM1 and TM3 are bands 1 [0.45-0.52 micrometers (μm)] and 

3 (0.63-0.69 μm), respectively, from the 

Landsat 5 TM.

Figure 3. Relation between predicted and measured values of secchi depth for Table Rock Lake.

0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

PREDICTED SECCHI DEPTH, IN METERS

MEASURED SECCHI DEPTH, IN METERS
6 Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data

Results

The regression analysis based on equation (1) produced 

the following linear model: 

ln(SDT) = -10.061(TM1/TM3) + 1.788(TM1) + 0.064 

 (2)

with a reliability (R2) of 0.76 and standard error of the estimate of 0.314. These results are consistent with similar studies 

using the TM1 and TM3 band relation to secchi disk transparency (Kloiber and others, 2002; Lathrop, 1992). Figure 3 is 

a plot of the relation between predicted and measured secchi 

depth for sample locations on Table Rock Lake. The plot 

shows a strong linear relation (r=0.83) between measured 

secchi depth and secchi depth predicted from mean Landsat 

reflectance values.

Field data collected on the same day as the satellite overpass result in the best regression results. Data collected from 1 

to 7 days off the overpass date result in a decreasing strength 

of correlation (Kloiber and others, 2002; Chipman and others, 

2004). All of the field data for this study were collected within 

4 days of the satellite overpass (fig. 4) with a distribution as 

follows: same day (0 percent), 1 day (3 percent), 2 days (28 

percent), 3 days (44 percent), and 4 days (25 percent). This 

distribution is inherent in the volunteer sample program as no 

effort is made to collect all samples on the same day. 

Quality and reliability of volunteer collected data have 

been evaluated by Obrecht and others (1998). They found no 

statistical differences in data collected by volunteers and data 

collected by University of Missouri personnel for total phosphorus, total nitrogen, chlorophyll, or secchi depth.

Results of the regression analysis were used to create 

models using Imagine Spatial Modeler to output images showing the ln(SDT) and trophic state index (TSI) derived from 

ln(SDT) for the entire lake. The relation between TSI and secchi disk depth is defined as:

TSI = 60-14.41 ln secchi disk (3)

where

TSI is the Carlson trophic state index, and

ln secchi disk is the natural logarithm of the depth 

measurement, in meters.

Output images are pixel-level representations of transparency 

or trophic state that can be used to examine differences in 

Figure 4. Distribution of field samples with respect to number of days within satellite overpass. All field samples 

were collected within 4 days with the largest percentage of samples collected 3 days from the time of satellite data 

collection.

0

1

2

3

4

5

6

7

8

9

10

-4 -3 -2 -1 0 1 2 3 4

DAYS FROM SCENE ACQUISITION

NUMBER OF OBSERVATIONS 
Results 7

Figure 5. Model predicted trophic state for Table Rock Lake – August 2003. Water quality is degraded in the main tributaries 

compared to the main channel of the reservoir.

Figure 6. Temporal comparison of model results for the James River arm of Table Rock Lake. Water clarity has decreased in 2005.

EXPLANATION

Universal Transverse Mercator projection, zone 15

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83)

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

Universal Transverse Mercator projection, zone 15

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83)

0 5 10 MILES

0 5 10 KILOMETERS
8 Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data

water quality throughout the reservoir (fig. 5). Differences in 

water quality are readily apparent between the main channel 

and major tributaries with darker green and yellow pixels in 

the tributaries representing decreased water clarity. Temporal 

comparisons can also be made to assess changes in water clarity over time. Figure 6 shows the difference in water clarity 

for the James River arm of Table Rock Lake between the 2003 

and 2005 scene dates. The increase in the TSI value can be 

seen extending much farther south in the James River arm in 

the 2005 image.

Summary

Remote sensing techniques can be effective in monitoring 

water quality in southwestern Missouri. Mean Landsat brightness values can be used with field data collected by citizen 

volunteers to produce reliable predictive models of water 

clarity and trophic state based on measurements of the secchi 

depth transparency. Predictive models can be used to supplement standard water-quality analyses during periods when 

field data are not being collected by volunteers. Temporal 

analyses are possible through the exploitation of the Landsat 

archive. Pixel-level representations of water clarity and trophic 

state provide a means of visually interpreting the status of 

water quality.

Acknowledgments

Field data used in this study was provided by the Lakes 

of Missouri Volunteer Program. Special thanks go to Tony 

Thorpe for his help in acquiring the original data and for 

discussions on procedures and interpretations of the volunteer 

data.

References Cited

Allee, R.J., and Johnson, J.E., 1999, Use of satellite imagery 

to estimate surface chlorophyll a and secchi disk depth of 

Bull Shoals Reservoir, Arkansas, USA: International Journal of Remote Sensing, v. 20, no. 6, p. 1057–1072.

Boland, D.H.P., 1976, Trophic classification of lakes using 

Landsat-1 (ERTS-1) multispectral scanner data: U.S. Environmental Protection Agency, Corvallis, Oreg., EPA-600/3-

76-03, 245 p.

Carlson, R.E.,1977, A trophic state index for lakes: Limnology 

and Oceanography, v. 22, no. 2, p. 361–369.

Chipman, J.W., Lillesand, T.M., Schmaltz, J.E., Leale, J.E., 

and Nordheim, M.J., 2004, Mapping lake water clarity with 

Landsat images in Wisconsin, U.S.A.: Canadian Journal of 

Remote Sensing, v. 30, p. 1–7.

Fuller, L.M., Aichele, S.S., and Minnerick, R.J., 2004, Predicting water quality by relating secchi-disk transparency and 

chlorophyll a measurments to satellite imagery for Michigan inland lakes, August 2002: U.S. Geological Survey 

Scientific Investigations Report 2004–5086, 25 p.

Jones, J.R., and Perkins, Bruce, 1999, Table Rock Lake: 

An evaluation of factors regulating its trophic state, Final 

Report to Missouri Department of Natural Resources and 

U.S. Environmental Protection Agency. University of Missouri, 82 p.

Kloiber, S.M., Brezonik, P.L., Olmanson, L.G., and Bauer, 

M.E., 2002, A procedure for regional lake water clarity 

assessment using Landsat multispectral data: Remote Sensing of Environment, v. 82, p. 38–47.

Krizanich, G.W., 1986, Landsat trophic state assessment of 

Fellows Lake: Missouri State University, Masters thesis, 

64 p.

Lathrop, R.G., 1992, Landsat thematic mapper monitoring of 

turbid inland water quality: Photogrammetric Engineering 

and Remote Sensing, v. 58, p. 465–470.

Lathrop, R.G., and Lillesand, T.M., 1986, Utility of thematic 

mapper data to assess water quality in southern Green Bay 

and west-central Lake Michigan: Photogrammetric Engineering and Remote Sensing, v. 52, p. 671–680.

Missouri Department of Natural Resources, 2005, Table Rock 

Lake total maximum daily load information sheet: Missouri 

Department of Natural Resources Water Protection Program, 4 p.

Obrecht, D.V., 1992, Lakes of Missouri Volunteer Program 

Manual: Lakes of Missouri Volunteer Program, Universtiy 

of Missouri, 17 p.

Obrecht, D.V., Milanick, Margaret, Perkins, B.D., Ready, 

Diana, and Jones, J.R., 1998, Evaluation of data generated 

from lake samples collected by volunteers: Journal of Lake 

and Reservoir Management, v. 14, no. 1, p. 21–27.

Olmanson, L.G., Kloiber, S.M., Bauer, M.E., and Brezonik, 

P.L., 2001, Image processing protocol for regional assessments of lake water quality: Water Resources Center and 

Remote Sensing Lab, University of Minnesota.

Ritchie, J.C., Zimba, P.V., and Everitt, J.H., 2003, Remote 

sensing techniques to assess water quality: Photogrammetric 

Engineering and Remote Sensing, v. 69, no. 6, p. 695–704.

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9

Thorpe, A.P., Obrecht, D.V., and Jones, J.R., 2005, Lakes of 

Missouri Volunteer Program 2005 data report, Department 

of Fisheries and Wildlife Sciences, University of Missouri.

Wetzel, R.G., 2001, Limnology: lake and river ecosystems (3d 

ed.): San Diego, CA, Academic Press, 1006 p.

Wezernak, C.T., Tanis, F.J., and Bajza, C.A., 1976, Trophic 

state analysis of inland lakes: Remote Sensing of Environ-

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Krizanich and Finn—Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data—Scientific Investigations Report 2009–5162