Minneapolis Environmental Study: Mississippi River Water Quality and Land Cover Changes

trextemperΜηχανική

22 Φεβ 2014 (πριν από 3 χρόνια και 6 μήνες)

83 εμφανίσεις

1















Minneapolis Environmental Study:

Mississippi Riv
er Water Quality and

Land

C
over Changes


















Team members: Thomas Bales & Andrea Claassen

Course: FR5226

Date: 12/14/2011

Instructor:

Joe Knight

2


I.

Introduction
.



The 72
-
mile Mis
sissippi 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 lif
e.

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 Nation
al 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 MR
CCA 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 Statemen
t



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 spe
cific 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 commun
ity 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 agen
cies, non
-
profits, and communities are working to enhance water quality
and watershed protection through education, monitoring and stewardship programs through
3


the Twin Cities metro area.

Additionally, these groups have become engaged in various river
pro
tection 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 t
ime. 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, sedimen
tation
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.

M
ethodology
.


Preprocessing p
hase

T
o co
nduct 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 U
nited 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 photogra
phs were then clipped by using

polygon
s

representing the
river
,

obtained
from MetroGIS
. Another
polygon
, which included the river channel and a
0.25 mi buffer,

was created to represent

the surrou
nding riverbank and floodpla
in
characteristics
.

In addition
,

the
shapefile representing the
different mosaic tiles from the
4


NAIP imagery had to

be used to analyze where
overlaps occurred
to differentiate between the

different
photograph exposure levels

in the tile
d mosaic

(
Appendix I
I,
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 h
ad settings modified to isolate and highlight

urban,
vegetation, and water

areas of the

image
.
This
process

transform
ed

the multiband raster from the
input mu
ltivariate
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 uncorrelate
d, and
data in a pr
incipal
component analysis

compress
ed the

data by eli
minating redundancy
.

The result was that
different water qualities were able to be differentiated over large areas

(
Appendix II,
Figure
2)
.

Once the process was c
omplete 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
.
P
urple represents the less clear
or cloudy water and blue

represent
s clear water
.

After conducting this

preliminary

analysis, three areas along the Mississippi River were
determined to be
of concern for w
ater quality assessment
. They were the
sections of the
Mississippi River in North
Mi
nneapolis, in
downtown

Minneapolis, and below

the
confluence of the Minnesota River in South Minneapolis
.

For repeatability
,

a
n

iterative self
-
organizing data analysis (ISO
)

cluster
ed

u
nsupervised classification

was conducted

on
the

series of input raster bands using Esri’s
maximum likelihood c
lassification tools.
Three areas
were determined to have different water signatures.
However, for the purposes of this study
5


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 shape
file
s

created in ArcInfo
were imported to ERDAS to create Areas of I
nterest
(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 No
rth/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 classifi
cations 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
6


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 the
se areas of non
-
interest were excluded, seven clusters
pertaining to different levels of w
ater 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 rec
ode
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 l
evels 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 0.2
5 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,
tr
ees/
forest, grass, wetland
vegetation, bare soil (dirt), and road
/impervious surface
. We established at least 5 training
7


areas for each class. We used the maximum likelihood “parameter rule” for assigning pixels
to classes based on the training data that w
ere 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 avail
able. A stratified random sampling distribution was
used for each accuracy assessment, with 100 sample point
s

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 limi
tations prevented th
e 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
8


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
turb
id river (Appendix II, Figures 6

and

7
).

Although resu
lts 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 (Append
ix II, Figures 4
-
8
)
. Of note,
the classified images of the so
uth 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 detect
ion 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 s
upervised 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 i
n 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
9


accuracy, and wetlan
d 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
p
roducer’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
, cl
ear water was

most
confused with trees/forest, silt
y water was

most conf
used with clear water
, an
d 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 prov
ide

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 conflu
ence 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
10


frequency should be conducted, and relevant supplemental data
(e.g. rainfall patterns,
agricultural runoff

data
)
should be includ
ed in the analysis to better under
stand apparent
changes in river clarity and sedimentation patterns.






D
ata Limitations


T
he image classifications do not account for the possibility
of different river water levels,
river discharge rates, or water velocities between years
.
Also, sli
ghtly different

time of year
for the 2004
(August)
and 2009

(September) images
may affect the color intensities betw
een
the year; however, the image months

are as close as possible.



Additional data limitations are the lack of a longer term data set for t
he analysis. The 5
-
year period
from 2004 to 2009 was likely too short to discern large changes over time among
land cover classes. Also, the difference in spa
tial resolution between 2004 (2m resolution)
and 2009 (1
m resolution) may have affected the accura
cy 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 ima
gery used in the water clarity an
alyses, 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,
unacco
unted for radiometric image differences between images may have affected the results
and interpretation.


11



V.

References.

http://www.fmr.org/news/current/critical_area_
repeal_action_alert
-
2011
-
02



APPENDIX

1
(
M
aterials 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.

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
Class
2004
2009
Change



Table 2:

Matrix of changes (“from
-
to” information) for Mississippi River in North Minneapolis, 2004 to 2009.
Units listed are area (ha).

2004
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
2009









12


Table 3:

Water clarity changes for confluence of Mississippi and Minneso
ta Rivers in South Minneapolis, 2004
to 2009.

area (ha)
%
area (ha)
%
area (ha)
%
non-river
10.4
7.5
12.8
9.2
2.4
1.7
clear water
41.3
29.7
35.9
25.8
5.4
-3.9
med water
40.8
29.4
39.0
28.1
1.8
-1.3
silty water
40.0
28.8
45.3
32.6
5.3
3.8
Class
2004
2009
Change



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
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
total
2009
133.0



Table 5:
Land cover change for confl
uence of Mississippi and Minnesota Rivers and 0.25 mi buffer around
river channels, South Minneapolis, 2004 to 2009.

area (ha)
%
area (ha)
%
area (ha)
%
clear water
53.5
38.5
76.7
55.2
23.2
16.7
silty water
85.8
61.7
91.7
66.0
5.9
4.2
river sandbar
14.7
10.6
28.6
20.6
13.9
10.0
wetland veg
12.5
9.0
15.8
11.4
3.3
2.4
trees/forest
354.1
254.7
361.8
260.3
7.7
5.5
grass
106.1
76.3
64.3
46.3
41.8
-30.1
bare soil (dirt)
19.3
13.9
12.5
9.0
6.8
-4.9
roads/impervious
19.1
13.7
15.1
10.9
4.0
-2.9
Change
Class
2004
2009



Table 6:
Matrix of changes (“from
-
to” information) for confluence of Mississippi and Minnesota Rivers and
0.25 mi buffer around river c
hannels, South Minneapolis, 2004 to 2009. Units listed are area (ha).

2004
2004
clear water
silty water
river sandbar
wetland veg
trees/forest
grass
bare soil (dirt)
roads/impervious
total
clear water
37.2
3.1
1.0
0.3
11.2
0.5
0.1
0.1
53.5
silty water
9.0
60.1
1.7
1.1
9.4
3.9
0.3
0.3
85.8
river sandbar
0.2
1.3
4.8
0.2
0.9
2.5
3.1
1.7
14.7
wetland veg
0.1
0.4
0.4
5.2
2.1
3.9
0.2
0.2
12.5
trees/forest
26.2
9.7
3.4
2.8
289.7
19.3
0.6
2.4
354.1
grass
1.9
11.8
6.6
6.1
43.1
30.5
4.1
2
106.1
bare soil (dirt)
1.8
4.5
3.4
0.1
4.7
2.6
1.6
0.6
19.3
roads/impervious
0.3
0.8
7.2
0.1
0.5
0.9
2.5
6.8
19.1
2009
76.7
91.7
28.6
15.8
361.8
64.3
12.5
15.1
total
2009
666.5



13


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 Minneapoli
s, 2004.

Class
clear water
silty water
river sandbar
wetland veg
trees/forest
grass
bare soil (dirt)
roads/impervious
total
user's
accuracy
no. of
clear water
8
0
0
0
6
1
0
0
15
53.3
pixels
silty water
1
16
0
0
1
0
1
0
19
84.2
classified
river sandbar
0
0
2
0
3
1
2
3
11
18.2
as
wetland veg
0
0
0
4
0
2
0
0
6
66.7
trees/forest
0
0
0
0
23
1
0
0
24
95.8
grass
0
0
0
0
3
10
0
0
13
76.9
bare soil (dirt)
0
0
0
0
0
3
1
3
7
14.3
roads/impervious
0
0
1
0
0
1
1
4
7
57.1
total
9
16
3
4
36
19
5
10
102
producer's
88.9
100.0
66.7
100.0
63.9
52.6
20.0
40.0
65.4
accuracy
reference data

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.

Class
clear water
silty water
river sandbar
wetland veg
trees/forest
grass
bare soil (dirt)
roads/impervious
total
user's
accuracy
no. of
clear water
8
1
0
0
2
0
0
0
11
72.7
pixels
silty water
4
8
0
0
0
1
0
0
13
61.5
classified
river sandbar
0
0
3
0
0
0
2
4
9
33.3
as
wetland veg
0
0
0
6
0
4
0
0
10
60.0
trees/forest
0
0
0
0
21
0
0
0
21
100.0
grass
0
0
0
0
6
7
0
0
13
53.8
bare soil (dirt)
1
0
1
0
1
1
4
2
10
40.0
roads/impervious
0
0
2
0
0
1
0
7
10
70.0
total
13
9
6
6
30
14
6
13
97
producer's
61.5
88.9
50.0
100.0
70.0
50.0
66.7
53.8
66.0
accuracy
reference data

O
verall accuracy = 66.0%
,
Kappa statistic = 60.2%























14


Figures


Figure 1:
Shapefiles created and used for the pre
-
processing phase

.

15



Figure 2:
Principal Component Analysis

using

2011 Terralook Image.





Figure 3:
ISO unsupervised preliminary classification



16









Figure 4
:
Unsupervised classification using 10 clusters. North area (Mississippi River) in 2004 (left) and
2009 (right).








17



Figure 5
:
Unsupervised classi
fication using thematic recode to combine clusters into three groupings.
North area (Mississippi River) in 2004 (left) and 2009 (right).


18



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).









19



Figure 8
:
Supervised classification of southern section (confluence of Mississippi and Minnesota Rivers)
in 2004 (left) and 2009 (right).