Minneapolis Environmental Study:
Mississippi River Water Quality and
Land Cover Changes
Team members: Thomas Bales & Andrea Claassen
Course: FR5226
Date: 12/14/2011
Instructor: Joe Knight
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I. Introduction.
The 72-mile Mississippi River Corridor in the Twin Cities was
designated as a State Critical Area in 1976, because of its unique natural,
scenic, cultural, historical and recreational resources – shared community
assets that improve Minnesota's economy and quality of life.
The Mississippi River Corridor Critical Area is a resource of regional,
statewide and national significance that requires special management to
retain its health and vitality. Designated a part of our National Park
System in 1988, the Mississippi National River and Recreation Area
(MNRRA) relies upon the State Critical Area framework to ensure
protection of park resources. The Mississippi River is a drinking water
source for more than 20 million Americans. Unfortunately, every mile of
the river in the MRCCA fails to meet State standards for water quality.
New standards are needed to reduce runoff pollution to the river.
– Friends of the Mississippi, 2011
Problem Statement
The goal of this project is to use remote sensing and GIS techniques to assess trends
in environmental characteristics of the Mississippi River, thereby giving various
organizations the ability to make policy and/or dedicate resources to specific areas to
promote local river health.
The Mississippi River is an important economic, cultural, and ecological resource. In
recent decades, riverfront development policies have shifted as communities increasingly
view the Mississippi River as a community asset. In the Twin Cities, the Mississippi River is
an important economic resource for the cities, is a source of municipal drinking water, offers
recreational opportunities for residents, and provides important habitat for wildlife.
Although federal, state, and local government agencies have passed amendments to
improve water quality, water quality is still impaired in the Mississippi River in the Twin
Cities metro area and fails to meet state and federal water quality standards. Local
government agencies, non-profits, and communities are working to enhance water quality
and watershed protection through education, monitoring and stewardship programs through
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the Twin Cities metro area. Additionally, these groups have become engaged in various river
protection activities such as native plant restoration.
In light of the economic, cultural, and ecological importance of the Mississippi River it is
important to document current environmental characteristics, as well as to identify and assess
changes over time. This project will use remote sensing to examine and assess changes in
general river and bank health of the Mississippi River in the Twin Cities region, specifically
focusing on a few key variables related to river health such as water quality, sedimentation
patterns, and vegetation patterns. This information will better enable various local agencies
and organizations to make policy decisions and dedicate resources to specific areas to
promote local river health.
II. Methodology.
Preprocessing phase
To conduct a water clarity/quality analysis, imagery from The National Agriculture
Imagery Program (NAIP) was obtained. This is aerial imagery that is captured every year
since 2003 during the agricultural growing seasons in the continental United States. This
imagery is high resolution (between 1 and 2 meters) and contains the red, green, and blue
color bands. The exception is 2008 which contains an additional infrared band.
In order to do a time comparison, images from 2004 and 2009 were downloaded to cover
a five year period. These photographs were then clipped by using polygons representing the
river, obtained from MetroGIS. Another polygon, which included the river channel and a
0.25 mi buffer, was created to represent the surrounding riverbank and floodplain
characteristics. In addition, the shapefile representing the different mosaic tiles from the
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NAIP imagery had to be used to analyze where overlaps occurred to differentiate between the
different photograph exposure levels in the tiled mosaic (Appendix II, Figure 1).
In order to pre-test differences in water clarity, a principal component analysis was
performed using 2011 Terralook imagery. The principal component analysis was done in
ArcInfo 10 which had settings modified to isolate and highlight urban, vegetation, and water
areas of the image. This process transformed the multiband raster from the input multivariate
attribute, and a new multivariate attribute whose axes are rotated with respect to the original
was created. The new attributes in the new space are uncorrelated, and data in a principal
component analysis compressed the data by eliminating redundancy. The result was that
different water qualities were able to be differentiated over large areas (Appendix II, Figure
2).
Once the process was complete and the remaining raster bands were dropped, it was clear
that differences in water using RGB imagery could be extracted. For example, figure 2 (in
Appendix II) clearly shows red as urban, green as vegetation and mixed classes, but more
importantly that two types of water are present in the image. Purple represents the less clear
or cloudy water and blue represents clear water.
After conducting this preliminary analysis, three areas along the Mississippi River were
determined to be of concern for water quality assessment. They were the sections of the
Mississippi River in North Minneapolis, in downtown Minneapolis, and below the
confluence of the Minnesota River in South Minneapolis. For repeatability, an iterative selforganizing data analysis (ISO) clustered unsupervised classification was conducted on the
series of input raster bands using Esri’s maximum likelihood classification tools. Three areas
were determined to have different water signatures. However, for the purposes of this study
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only the northern (North/Northeast Minneapolis) and southern (confluence of the Minnesota
and Mississippi River) areas were targeted for further analysis (Appendix II, Figure 3).
Lastly, the shapefiles created in ArcInfo were imported to ERDAS to create Areas of Interest
(AOIs).
ERDAS: Sites for further analyses
For the following analyses we focused on two different sites on the Mississippi River
within the Twin Cities metropolitan area. The north site contains a stretch of the Mississippi
River situated in North/Northeast Minneapolis and the northern suburb of Columbia Heights.
The north site is primarily industrial use, with some residential areas and parkland. The south
site lies at the confluence of the Mississippi and Minnesota Rivers in south Minneapolis and
is primarily residential use with some parkland. The following analyses (classifications,
change detection, and accuracy assessment) were all performed using ERDAS (ERDAS
Imagine 2010 and 2011 software).
Changes in river clarity:
Unsupervised classifications of the river (clipped to the river channel) were conducted
for both the north and south sites for both 2004 and 2009. The unsupervised classifications
were performed several times for the 2009 south site imagery using different numbers of
clusters to test for the most appropriate number of clusters to use for further analyses. Using
ten clusters was the most appropriate for distinguishing various water clarity levels in the
river and for identifying areas to be excluded from water clarity analyses (e.g. bridges over
the river, emergent sandbars, shadows). A convergence threshold of 25 iterations and the
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principal axis intializing option were set for conducting the unsupervised classifications in
ERDAS. The defaults were used for all other parameters. Areas of non-interest (bridges,
sandbars, and shadows) included those with the two lowest pixel values (i.e. pixels pertaining
to the two darkest cluster levels) and the highest pixel value (i.e. pixels pertaining to the
lightest cluster value). After these areas of non-interest were excluded, seven clusters
pertaining to different levels of water clarity remained for inclusion in water clarity analyses.
Change detections were conducted to compare land use changes between years for both
the north and south river sites. Although the classified images with seven water clarity levels
were useful for visual interpretation (Appendix II, Figures 4 and 6), this was deemed to be
too many water classes to use for conducting change detections. Therefore, thematic recode
was used to combine clusters into a simpler subset of three classes, combining the two
darkest clusters, the three medium clusters, and the two lightest clusters (Appendix II,
Figures 5 and 7). These recoded clusters represented low, medium, and high levels of river
turbidity. Change detections were conducted for the recoded classifications containing the
three water clarity classes.
Changes in floodplain and channel land cover:
Supervised classifications of the buffered area (river area plus 0.25 mi buffer) of the
southern site (confluence of Mississippi and Minnesota Rivers) for 2004 and 2009 NAIP
imagery were conducted. We identified the following classes corresponding to land cover
types of interest: clear water, silty water, river sandbar, trees/forest, grass, wetland
vegetation, bare soil (dirt), and road/impervious surface. We established at least 5 training
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areas for each class. We used the maximum likelihood “parameter rule” for assigning pixels
to classes based on the training data that were input into ERDAS.
A change detection was performed to assess changes in land cover in the river buffer
area (i.e. river floodplain and channel areas) between 2004 and 2009.
Accuracy assessment:
An accuracy assessment was performed for the supervised classifications for the south site
for both 2004 and 2009. The same data (NAIP 2004 and 2009) that were used for classifying
the images were also used as reference data for the accuracy assessment because other high
resolution reference data were not available. A stratified random sampling distribution was
used for each accuracy assessment, with 100 sample points used and a minimum of 10 points
per class. Although the number of sample points used was lower than the recommended 50
points per class, time limitations prevented the use of a larger sample size.
III. Results
Based on results of the change detection of the unsupervised classifications, water clarity
did not appear to change in the north area of the Mississippi River from 2004 to 2009.
Although clear water declined by 5.5%, silty water also declined by an equivalent amount
(5.4%), and medium clear water increased by 9.6% (Appendix II, Table 1). These changes
likely reflect difficulties in separating the classes rather than any true differences in water
clarity in the north area of the Mississippi River. In the south area (confluence of the
Mississippi and Minnesota Rivers), however, water quality declined during the same period,
as evidenced by a negative change (-3.9%) in the amount of clear water, and a positive
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change (+3.8%) in the amount of silty water (Appendix II, Table 3). In the south area, water
clarity changes reflect sedimentation patterns of the Minnesota River, a highly polluted and
turbid river (Appendix II, Figures 6 and 7).
Although results of the change detections of the unsupervised classifications of the river
channel provide estimates of net change to river clarity, inspections of the classified images
themselves also reveal changes in sedimentation patterns (Appendix II, Figures 4-8). Of note,
the classified images of the south area (Appendix II, Figures 6 and 7) reveal that in 2009
sedimentation was lower on the Minnesota River and higher on the Mississippi River below
the confluence of the Minnesota River than in 2004.
The results of the change detection of the buffered south area (Mississippi and Minnesota
River channels, plus a 0.25m buffer to include the floodplain), seem to somewhat contradict
the results of the unsupervised classification of the river channel. The change detection of the
buffered south area shows clear water increasing by 16.7% and silty water increasing by a
smaller 4.2% (Appendix II, Table 5). These differences may be a result of the unsupervised
classification having three water clarity classes, whereas the supervised classification of the
buffered south area only used two water clarity classes. The use of two rather than three
water clarity classes for the supervised classification was necessary due to difficulty in
visually selecting training areas for use in the supervised classification. The discrepancy in
change detection results for water clarity from the two types of classifications performed may
also reflect differences in classification accuracy of the two methods.
Overall accuracy assessment of the classifications of the buffered south area were 65.4%
and 66.0% for 2004 and 2009, respectively (Appendix II, Tables 7 and 8). In 2004, bare soil
(dirt) had the lowest user’s and producer’s accuracy, trees/forest had the highest user’s
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accuracy, and wetland vegetation had the highest producer’s accuracy (Appendix II, Table
7). In 2009, river sandbar’s had the lowest user’s accuracy and one of the lowest producer’s
accuracy (tied with grass), and trees/forest and wetland vegetation both had 100% user’s and
producer’s accuracy (Appendix II, Table 8). The results of the accuracy assessment suggest
that for this analysis the darker land cover types had higher accuracy than the lighter colored
land cover types. Of the river channel landcover types of interest, clear water was most
confused with trees/forest, silty water was most confused with clear water, and river sandbars
were most confused with roads/impervious surfaces (Appendix II, Tables 7 and 8).
IV. Discussion.
The results of this study are useful to provide some initial insight into environmental
characteristics of the Mississippi and Minnesota Rivers, including how river clarity and
floodplain land cover may change over time. These preliminary results indicate that water
clarity in the area of the confluence of the Mississippi and Minnesota Rivers in south
Minneapolis has declined somewhat from 2004 to 2009, and that the pattern of sedimentation
has changed, with lower sedimentation in the Minnesota River above the confluence and
greater sedimentation in the Mississippi River below the confluence with the Minnesota
River. However, this study should be viewed as phase 1 of a more thorough investigation
into changes in river land cover classes over time, with an emphasis in future project phases
on improving the accuracy of land cover classifications used to detect environmental
changes. Further investigation should be conducted over a longer time period, further trial
supervised classifications should be performed to better identify appropriate and relevant
land cover classes for analysis, more extensive accuracy assessments with a greater sampling
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frequency should be conducted, and relevant supplemental data (e.g. rainfall patterns,
agricultural runoff data) should be included in the analysis to better understand apparent
changes in river clarity and sedimentation patterns.
Data Limitations
The image classifications do not account for the possibility of different river water levels,
river discharge rates, or water velocities between years. Also, slightly different time of year
for the 2004 (August) and 2009 (September) images may affect the color intensities between
the year; however, the image months are as close as possible.
Additional data limitations are the lack of a longer term data set for the analysis. The 5year period from 2004 to 2009 was likely too short to discern large changes over time among
land cover classes. Also, the difference in spatial resolution between 2004 (2m resolution)
and 2009 (1m resolution) may have affected the accuracy of the river classifications, thus
affecting the results of the change detection for water clarity between years. Furthermore,
shadows and other areas of non-interest (river bridges, emergent river sandbars) in the
images used for water clarity analyses may have affected the accuracy of land cover
classifications, as well as the interpretation of the imagery and results of change detections.
However, we tried to account for this by excluding areas of non-interest (shadows, bridges,
sandbars) from the imagery used in the water clarity analyses, first by clipping the areas of
the river channel to exclude as many of these areas as possible, and second by coding these
features as areas on non-interest in the classifications that were performed. Lastly,
unaccounted for radiometric image differences between images may have affected the results
and interpretation.
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V. References.
http://www.fmr.org/news/current/critical_area_repeal_action_alert-2011-02
APPENDIX 1 (Materials and Software)
NAIP Imagery (2004 and 2009)
Terralook imagery (ASTER 2011)
ERDAS Imagine
Esri ArcInfo
APPENDIX II (Tables and Figures)
Tables
Table 1: Water clarity changes for Mississippi River in North Minneapolis, 2004 to 2009.
2004
2009
Change
Class
area (ha)
%
area (ha)
%
area (ha)
%
non-river
16.7
12.0
18.6
13.4
1.9
1.4
clear water
27.6
19.9
20.0
14.4
7.6
-5.5
med water
71.5
51.4
84.8
61.0
13.3
9.6
silty water
23.7
17.1
16.2
11.7
7.5
-5.4
Table 2: Matrix of changes (“from-to” information) for Mississippi River in North Minneapolis, 2004 to 2009.
Units listed are area (ha).
2004
2009
2004
non-river clear water med water silty water total
non-river
7.9
1.6
5
2.2
16.7
clear water
2.8
3.2
18.9
2.7
27.6
med water
4.8
6.5
50.3
9.9
71.5
silty water
3.1
8.7
10.6
1.4
23.7
2009
18.6
20
84.8
16.2
139.5
total
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Table 3: Water clarity changes for confluence of Mississippi and Minnesota Rivers in South Minneapolis, 2004
to 2009.
Class
non-river
clear water
med water
silty water
2004
area (ha)
%
10.4
7.5
41.3
29.7
40.8
29.4
40.0
28.8
2009
area (ha)
12.8
35.9
39.0
45.3
%
9.2
25.8
28.1
32.6
Change
area (ha)
%
2.4
1.7
5.4
-3.9
1.8
-1.3
5.3
3.8
Table 4: Matrix of changes (“from-to” information) for confluence of Mississippi and Minnesota Rivers in
South Minneapolis, 2004 to 2009. Units listed are area (ha).
2004
2009
2004
non-river clear water med water silty water total
non-river
5.6
1.6
1.6
1.6
10.4
clear water
2.1
29.6
6.7
2.9
41.3
med water
3.4
4.1
14.4
18.9
40.8
silty water
1.6
0.5
16.1
21.8
40.0
2009
12.8
35.9
39.0
45.3
133.0
total
Table 5: Land cover change for confluence of Mississippi and Minnesota Rivers and 0.25 mi buffer around
river channels, South Minneapolis, 2004 to 2009.
Class
clear water
silty water
river sandbar
wetland veg
trees/forest
grass
bare soil (dirt)
roads/impervious
2004
area (ha)
53.5
85.8
14.7
12.5
354.1
106.1
19.3
19.1
2009
%
38.5
61.7
10.6
9.0
254.7
76.3
13.9
13.7
area (ha)
76.7
91.7
28.6
15.8
361.8
64.3
12.5
15.1
%
55.2
66.0
20.6
11.4
260.3
46.3
9.0
10.9
Change
area (ha)
%
23.2
16.7
5.9
4.2
13.9
10.0
3.3
2.4
7.7
5.5
41.8
-30.1
6.8
-4.9
4.0
-2.9
Table 6: Matrix of changes (“from-to” information) for confluence of Mississippi and Minnesota Rivers and
0.25 mi buffer around river channels, South Minneapolis, 2004 to 2009. Units listed are area (ha).
2004
2009
clear water silty water river sandbar wetland veg trees/forest
clear water
37.2
3.1
1.0
0.3
11.2
silty water
9.0
60.1
1.7
1.1
9.4
river sandbar
0.2
1.3
4.8
0.2
0.9
wetland veg
0.1
0.4
0.4
5.2
2.1
trees/forest
26.2
9.7
3.4
2.8
289.7
grass
1.9
11.8
6.6
6.1
43.1
bare soil (dirt)
1.8
4.5
3.4
0.1
4.7
roads/impervious
0.3
0.8
7.2
0.1
0.5
2009
76.7
91.7
28.6
15.8
361.8
total
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grass
0.5
3.9
2.5
3.9
19.3
30.5
2.6
0.9
64.3
bare soil (dirt) roads/impervious
0.1
0.1
0.3
0.3
3.1
1.7
0.2
0.2
0.6
2.4
4.1
2
1.6
0.6
2.5
6.8
12.5
15.1
2004
total
53.5
85.8
14.7
12.5
354.1
106.1
19.3
19.1
666.5
Table 7: Accuracy assessment (error matrix) for supervised classification of confluence of Mississippi and
Minnesota Rivers and 0.25 mi buffer around river channels, South Minneapolis, 2004.
reference data
Class
clear water silty water river sandbar wetland veg trees/forest
no. of
clear water
8
0
0
0
6
pixels
silty water
1
16
0
0
1
classified river sandbar
0
0
2
0
3
as
wetland veg
0
0
0
4
0
trees/forest
0
0
0
0
23
grass
0
0
0
0
3
bare soil (dirt)
0
0
0
0
0
roads/impervious
0
0
1
0
0
total
9
16
3
4
36
producer's
88.9
100.0
66.7
100.0
63.9
accuracy
grass
1
0
1
2
1
10
3
1
19
52.6
bare soil (dirt) roads/impervious
0
0
1
0
2
3
0
0
0
0
0
0
1
3
1
4
5
10
20.0
40.0
total
15
19
11
6
24
13
7
7
102
user's
accuracy
53.3
84.2
18.2
66.7
95.8
76.9
14.3
57.1
65.4
Overall accuracy = 65.4%, Kappa statistic = 58.6%
Table 8: Accuracy assessment (error matrix) for supervised classification of confluence of Mississippi and
Minnesota Rivers and 0.25 mi buffer around river channels, South Minneapolis, 2009.
reference data
Class
no. of
clear water
pixels
silty water
classified river sandbar
as
wetland veg
trees/forest
grass
bare soil (dirt)
roads/impervious
total
producer's
accuracy
clear water
8
4
0
0
0
0
1
0
13
61.5
silty water river sandbar wetland veg trees/forest
1
0
0
2
8
0
0
0
0
3
0
0
0
0
6
0
0
0
0
21
0
0
0
6
0
1
0
1
0
2
0
0
9
6
6
30
88.9
50.0
100.0
70.0
Overall accuracy = 66.0%, Kappa statistic = 60.2%
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grass
0
1
0
4
0
7
1
1
14
50.0
bare soil (dirt) roads/impervious
0
0
0
0
2
4
0
0
0
0
0
0
4
2
0
7
6
13
66.7
53.8
total
11
13
9
10
21
13
10
10
97
user's
accuracy
72.7
61.5
33.3
60.0
100.0
53.8
40.0
70.0
66.0
Figures
Figure 1: Shapefiles created and used for the pre-processing phase
.
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Figure 2: Principal Component Analysis using 2011 Terralook Image.
Figure 3: ISO unsupervised preliminary classification
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Figure 4: Unsupervised classification using 10 clusters. North area (Mississippi River) in 2004 (left) and
2009 (right).
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Figure 5: Unsupervised classification using thematic recode to combine clusters into three groupings.
North area (Mississippi River) in 2004 (left) and 2009 (right).
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Figure 6: Unsupervised classification using 10 clusters. Southern section (confluence of Mississippi and
Minnesota Rivers) in 2004 (left) and 2009 (right).
Figure 7: Unsupervised classification using thematic recode to combine clusters into three groupings.
Southern section (confluence of Mississippi and Minnesota Rivers) in 2004 (left) and 2009 (right).
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Figure 8: Supervised classification of southern section (confluence of Mississippi and Minnesota Rivers)
in 2004 (left) and 2009 (right).
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