A technique is being developed for use of ERTS in estimating and monitoring trophic levels of inland lakes. Preliminary findings are that Michigan lakes and ponds of one acre or more are resolvable in bands 5, 6 and 7 of NASA MSS imagery under fair conditions (haze and 70% cloud cover). In processed imagery (CCT) smaller features, including water color patterns, are evident within some lakes of 40 acres or more. Image distortion of lake size, shape, orientation, etc. is minimal; discrimination of lakes and ponds from various wetlands is good. Subsequent ERTS and aircraft imagery will be correlated with detailed ground truth of water color and quality in eutrophic test lakes

Chase, P. E.

Reed, L.

Smith, V. E.

English

NASA Technical Reports Server

UTILIZATION OF ERTS-1 DATA TO MONITOR AND CLASSIFY 
EUTROPHICATION OF INLAND LAKES 
Phillip E. Chase and Larry Reed, The Bendix Corporation, Ann Arbor, Michigan; 
V. Elliott Smith, Cranbrook Institute of Science, Bloomfield Hills, Michigan 
ABSTRACT 
A technique is being developed for use of ERTS in estimating and 
monitoring trophic levels of inland lakes. Preliminary findings a r e  that 
Michigan lakes and ponds of one acre or more a r e  resolvable in bands 5, 
6 and 7 of NASA MSS imagery under fair conditions (haze and 70%-cloud 
cover). In processed imagery (CCT) smaller features, including water 
color patterns, are evident within some lakes of 40 acres  or more. 
age distortion of lake size, shape, orientation, etc. is minimal; discri- 
mination of lakes and ponds from various wetlands is good. Subsequent 
ERTS and aircraft imagery will be correlated with detailed ground truth 
of water color and quality in eutrophic test lakes. 
Im- 
1. INTRODUCTION 
Eutrophication or  nutrient-organic enrichment is responsible for 
losses in water quality, property values and recreational uses of inland 
lakes. 
large inputs of sewage and fertilizer nutrients. Algal blooms, macro- 
phyte growths and high turbidity result from increasing productivity in 
these waters. Since the attendant discoloration of lakes is detectable by 
remote sensors, water color is the mediating factor between ERTS ima- 
gery and water quality. 
Lakes in urban and suburban areas  a r e  being degraded rapidly by 
In a study of 530 Wisconsin lakes Juday and Birge (1933) established 
empirical relationships between water transparency (turbidity) and its 
plankton content and color (platinum-cobalt scale). A similar relationship 
was found between water color and its organic carbon content. 
lake becomes more productive (eutrophic) it undergoes a series of color 
changes from blue to green, yellow, brown and even red (Hutchinson, 1957). 
These color changes must be accounted for in terms of other trophic state 
indicators before color itself can be used to gauge water quality. Lake 
water colors also must be identified in remote imagery. 
petitive monitoring is essential to recognize long-term trophic changes 
Thus as a 
Finally, re- 
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https://ntrs.nasa.gov/search.jsp?R=19730019643 2020-03-17T09:15:18+00:00Z
a s  distinct from short-term or  seasonal variations. ERTS provides a 
means for regular surveillance of lake trophic levels and rates of en- 
richment. The present study focusses on the practical correlation of 
ERTS data and water quality in lakes. 
2. GROUND MONITORING AND TEST SITE AREA 
Six glacial lakes (40-1280 acres), varying from mildly to highly 
eutrophic, a r e  under study in Oakland County, Michigan. 
chemical factors in four of these have been surveyed for the previous 
three years. 
average differences in  color and quality between lakes allow them to be 
ranked in order of increasing productivity. A program of in situ and 
laboratory measurements has been designed to  characterize water and 
lake color and to define trophic levels at the time of ERTS passes. 
measurements include: water transparency (turbidimetry), water color 
(platinum- cobalt and Forel-Ule scales), particulate color (reflectance 
spectra), particulate ash/dry weight ratios, organic carbon, nitrogen 
and phosphorus, chlorophyll, plankton (qualitative and surface - sky radio- 
metry. 
noted as well. Ground monitoring will begin a s  soon as the lakes a r e  ice- 
free. 
Biological and 
While water color has been highly variable in each lake, 
These 
Transient factors, such a s  pH, temperature and blooms, will be 
Figure 1 presents the test  area and five of the test lakes (Cass, 
Orchard, Lower Long, Forest  and Island). The map i s  based upon data 
in USGS maps (1965). aerial  photos and ground observation. 
3. REMOTE MONITORING 
Despite urifavorable weather locally since ERTS launch, one set  of 
In this scene (Figure 1) usable imagery is available for the study area. 
for September 28, 1972 five of the six study lakes a r e  visible through 70% 
cloud cover within the indicated 50-square-mile area. This area includes 
numerous other lakes and ponds that also have been useful for analyzing 
ERTS resolution of small water bodies and their discrimination from 
various wetlands. 
a r e  approximately 200 ft. in diameter or slightly less than one acre  in 
area. 
o r  channels that a r e  approximately 100 ft. in width a re  also evident but 
have no definite shape in the imagery. 
The smallest ponds (or channels) that can be resolved 
Elongated ponds These appear a s  gray spots in the B/W imagery. 
Larger ponds that appear as black (full density) images a r e  a t  least 
550 ft. in diameter, o r  approximately 5 acres  in area. Their greater 
1598 
Figure 1 Oakland County Planning Commission Map of 
ERTS Study-Sub Area (1968) ERTS Scene 1067- 15463-7 
Inset Upper Left Hand Corner 
1599 
image density may be a function of sensor response or, possibly, may be 
related to their shallow depth and generally more turbid waters. 
question will be resolved later by ground truth. 
of the study lakes (Forest, 40 acres) is visible in full image density. 
This 
In any event, smallest 
No differences were noted (in Bands 6 and 7 of the NASA GSFC 
imagery) in the resolution of small elongated ponds that a r e  oriented 
with the direction of scan (west to east) and those that a r e  aligned nor- 
mal to scan lines (north to south). Similarly, no apparent distortion o r  
displacement of small ponds was observed in Bands 6 and 7.  Some dis- 
tortion (banding effect) in the imagery received from NASA was noted in 
Band 5 ,  which was not evident in later imagery produced from CCT in 
Bendix Earth Resources Data Center (Figure 2 and Figure 3). 
Electronic enlargements of this imagery (Bendix CCT imagery), 
which became available just prior to this report, show improved resolu- 
tion of these features (some distortion exists in Figure 2 and Figure 3 
because earth rotation and other geometric e r r o r s  a r e  not corrected. 
Such corrections a r e  underway). For example, swamps composed of 
floating and emergent vegetation a re  readily distinguished from the 
smallest lakes visible. 
distinct from other wooded areas. Further study will resolve the ques- 
tion of how much floating o r  emergent vegetation a lake may contain and 
still show the image characteristics of "open water". 
In bands 6 and 7 swamps appear a s  gray areas  
One of the study lakes contains a one-acre island visible in bands 
6 and 7. 
same whether it concerns a light object in a dark field (islands on water) 
o r  a dark object in a light field (ponds on land), 
determining that ERTS- 1 detects and separates small inland water bodies 
and wetlands - has been accomplished. 
The conclusion is that ERTS resolution is approximately the 
The first key step - 
The image density of lake water has been examined for variations in 
all  four bands. 
particularly in the negative transparency images. With few exceptions 
the variations in water %olor" were evident only in Band 5 (Figure 3). 
However, because of partial cloud cover it was unclear whether these 
tonal effects represented real differences in water quality. Under better 
atmospheric conditions Bands 4 and 5 would be expected to record dif- 
ferences in water color that a r e  within the visible spectrum (blue to red). 
W a t e r  colors of green, green-yellow, yellow, yellow-brown, and red- 
brown a r e  common occurrences among the six study lakes. 
phenomena, such a s  algal blooms (of cyanophytes) that a r e  seen occas- 
ionally on the lakes, may well be detectable in Bands 6 and 7 (near IR) 
In certain lakes patterns of variable density were noted, 
Surface 
1600 
Figure 2 Enlargement of ERTS Study Sub-Area 
as Shown in Figure 1 
(1067-15463 Band 7 )  
Figure 3 Enlargement of ERTS Study Sub-Area, 
as Shown in Figure 1 
(1067- 15463, Band 5) 
1601 
a r  well, Comp~r i ron  of them imager wifh bathymetry mapr of laker in- 
dicates that only part of the variable denrity ir due to bottom reflection 
and macrophytes, Some of the variation is due to backscatter from or- 
ganic and inorganic suspensions. (See Table 1) for a summary. 
4. DATA PROCESSING 
A series of lake water surface maps combining the CCT data of all 
four channels will be prepared. Preliminary statistical computer proc- 
essing indicates a wide variety of color data in the four bands. The next 
key test now underway is the comparison (for Orchard Lake) of the bathy-k 
metry map, ERTS- 1 individual band alpha numeric printouts, (CCT) ERTS- 1 
probability density imagery (CCT), ERTS- 1 decision imagery, ERTS- 1 
Cal Comp water feature boundaries, and simi ar statistically processed 
to verify that ERTS-1 can detect the various causes of lake water color 
for smaller inland lakes - including the important backscatter from BUS- 
pensions. 
imagery for an 11-channel scanner (Bendix M B S). This study is expected 
The final key step of correlation ERTS-1 data to trophic level and 
classifying lakes will be performed in the spring, summer and fall of 
1973. 
5. SIGNIFICANT RESULTS 
ERTS-1 imagery has shown several changes (or inaccuracies) to 
have occurred since the Oakland County map (Figure 1) was drawn (1968). 
ERTS- 1 and ground observation indicates the southern part of Otter Lake 
is a swamp. A pond w 
in the ERTS-1 imagerJ'). Other detail corrections of the base map could 
be listed. ( 5 )  
dredged to become a lake, as is now apparent 
More key is establishing that ERTS-1 detects lake areas  of one acre  
and can monitor average lake colors to as small as  5 acres. In addition 
color features a re  demonstrably observable in a t  least 3 of the test lakes 
in the imagery. And of course statistical processing of the CCT is pro- 
ducing improved geometrical re solution and spectral separation because 
of the greater information present in the CCT. 
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6. REFERENCES 
1. Chase, P. E. & V. E. Smith, 1973. Utilization of ERTS- 1 Data to 
Monitor and Classify Eutrophication in Inland Lakes. Interim report 
to NASA GSFC September 1972 - January 1973, Contract NAS 521810, 
Bendix Report BSR 40 10. 
2. Hutchinson, G. E. (ea. ) 1957. A treatise on limnology. Vol. 1. 
Geography, physics and chemistry. 
York. 1015p. 
John Wiley and Sons, Inc. New 
3. Juday, C. and E. A. Birge. 1933. The transparency, the color 
and the specific conductance of the lake waters of northeastern 
Wisconsin. Trans. Wisc. Acad. 28:205-259. 
4. The new 'lake' l ies on a line between Wabeek and Pine'Lake in Figure 
2. 
5. Golf courses and cemetaries a re  particularly visible in Figure 2. 
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Utilization of ERTS-1 data to monitor and classify eutrophication of inland lakes

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