remote sensing for regional assessment and … sensing for regional assessment and analysis of...
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![Page 1: Remote Sensing for Regional Assessment and … Sensing for Regional Assessment and Analysis of Minnesota Lake and River Water Quality Leif Olmanson Marvin Bauer Patrick Brezonik UNIVERSITY](https://reader031.vdocuments.us/reader031/viewer/2022030417/5aa3cc727f8b9ab4208eb529/html5/thumbnails/1.jpg)
Remote Sensing for Regional Assessment and Analysis of Minnesota Lake and River Water
Quality
Leif OlmansonMarvin Bauer
Patrick Brezonik
UNIVERSITY OF MINNESOTA
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Areas of Research and Accomplishments
• Developed large Landsat water clarity database ~10,500 MN lakes
– Analyzed geospatial and temporal trends of water clarity in Minnesota
• Investigated and evaluated alternative remote sensing systems for regional water quality assessment
• Developed techniques for remote sensing of optically complex river waters using high spatial and spectral resolution airborne imagery
How clear is your Lake?
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Lake Water Quality Monitoring: Summary
1. Citizens measure lake clarity
2. Near the same time, satellites collect imagery
4. Clarity of all lakes is classified
~1,000 Lakes monitored
Over 10,000 Lakes monitored
3. Build statistical models
y = -15.583x + 4.6742R2 = 0.84
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
0.15 0.2 0.25 0.3 0.35 0.4 0.45
TM3:TM1 Ratio
ln(S
DT) -
- met
ers
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0
500
1000
1500
2000
2500
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3500
>4 3-4 2-3 1-2 0.5-1 <0.5
Water Clarity (m)
Num
ber o
f Lak
es
Minnesota Lake ClarityLake Level 2005
33‐year “Census” of Minnesota lake clarity with 7 assessments for 1975–2008
Over 10,000 lakes classified for each time periodAll lakes >8 hectares are includedDatabase includes 1‐ 4 measurements per time period
Used for statistical analysis of Lake water clarity
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Water Clarity Trends by Ecoregion, 1985 − 2005
75%
15%
10%
93%
1%6%
95%
3%2%
85%
8%7%
68%
27%
5%
80%
12%8%
76%
19%
5%
NLF4,717 lakes
RRV184 lakes
NGP534 lakes
WCBP520 lakes
NMW155 lakes
NCHF3,496 lakes
DLA41 lakes
9,647 lakes assessed in 1985, 1990, 1995, 2000 and 2005
1,039 lakes (10.8%) had trend line change ≥ 10 TSI units
440 (4.6%) improved clarity 599 (6.2%) decreased clarity
0
50
100
150
200
250
<20 20-50 50-150 150-500 >500
Num
ber
of L
akes
Lake Area (acres)
Minnesota Lakes with Trends by Size
0
50
100
150
200
250
300
Type 5 Type 4 Type 3 Type 2 No ID
Num
ber o
f Lak
es
Wetland Type from Bulletin 25
Minnesota Lakes with Trends by Type
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Land cover versuswater clarity by depth
within lake watershed
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August 25, 2008Imagery
MODIS Terra 500 mCalibrated Radiance
• MODIS 250, 1000 m calibrated radiance• MODIS 8-day surface reflectance
MERIS L1 TOA Calibrated Radiance
• MERIS L2 Surface radiance/reflectance (Bright Pixel method)
• MERIS C2 Water leaving reflectance (radiative transfer simulations-NN method)
Landsat ETM+ SLC off
Comparison and Evaluation of Medium to Low Resolution Satellite Imagery for Regional Lake Water Quality Assessment
Objectives
• Develop the capability for frequent monitoring, of clarity and chlorophyll, in medium-to-large lakes using MODIS and MERIS data.
• Compare alternative sensors.
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Landsat ETM+ 30mMERIS 300mMODIS 250 & 500mMODIS 1000m
Reflectance spectra of 15 Minnesota lakes with Landsat, MERIS and MODIS band locations indicated (Menken et al. 2006)
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Landsat ETM+ 30mMERIS 300mMODIS 250 & 500mMODIS 1000m
Reflectance spectra of 15 Minnesota lakes with Landsat, MERIS and MODIS band locations indicated (Menken et al. 2006)
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Image processing calibration fit and lakes assessed for Landsat, MERIS and MODIS (8/25/08)
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 ha
MERIS L2 140 0.77 56 0.76 300 m 471 300 ha
MERIS C2 186 0.50 75 0.41 300 m 664 250 ha
MODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 ha
MODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 haMERIS L2 140 0.77 56 0.76 300 m 471 300 haMERIS C2 186 0.50 75 0.41 300 m 664 250 haMODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 ha
MODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Secchi Disk Chl a
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Image processing calibration fit and lakes assessed for Landsat, MERIS and MODIS (8/25/08)
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 ha
MERIS L2 140 0.77 56 0.76 300 m 471 300 ha
MERIS C2 186 0.50 75 0.41 300 m 664 250 ha
MODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 ha
MODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 haMERIS L2 140 0.77 56 0.76 300 m 471 300 haMERIS C2 186 0.50 75 0.41 300 m 664 250 haMODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 ha
MODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 haMERIS L2 140 0.77 56 0.76 300 m 471 300 haMERIS C2 186 0.50 75 0.41 300 m 664 250 haMODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 haMODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Secchi Disk Chl a
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Landsat TM 30 m MODIS 500 m
*14,528 acre lake
Lake Minnetonka* Water QualityAugust 25, 2008
MERIS water clarity MERIS chlorophyll a
Map LegendSD Chl a(m) (μg/L)
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Hyperspectral Imagery for Water Quality Assessment of the Mississippi River and its
Major Tributaries in Minnesota
Mississippi River water
Minnesota River water
• Monitor the water quality of optically complex / dynamic rivers.
• Both Phytoplankton or inorganic sediment are optically dominant.
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Major Minnesota Rivers
September 5, 2003 Landsat TM imagery
Mississippi River40-45% of flow
20% of TSS load
Minnesota contributes2.9% of total nitrogen flux
2.0% of total phosphorus fluxdelivered to the Gulf of Mexico
St. Croix River25-30% of flow5% of TSS load
Minnesota River25-30% of flow
75% of TSS loadSpring Lake
Discharge (cfs) August 19, 2004 August 15, 2005 August 30, 2007River Site Mean 26,604 Discharge (cfs) 9,130 Discharge (cfs) 7,370 Discharge (cfs) 8,070
Minnesota Jordan 8810 - 33% 3190 - 35% 1840 - 25% 4160 - 52%Mississippi Anoka 11700 - 44% 2770 - 30% 4100 - 56% 1930 - 24%
St. Croix Stillwater 6094 - 23% 3170 - 35% 1430 - 19% 1980 - 24%
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Major Minnesota Rivers
September 5, 2003 Landsat TM imagery
Mississippi River40-45% of flow
20% of TSS load
Minnesota contributes2.9% of total nitrogen flux
2.0% of total phosphorus fluxdelivered to the Gulf of Mexico
St. Croix River25-30% of flow5% of TSS load
Minnesota River25-30% of flow
75% of TSS loadSpring Lake
Discharge (cfs) August 19, 2004 August 15, 2005 August 30, 2007River Site Mean 26,604 Discharge (cfs) 9,130 Discharge (cfs) 7,370 Discharge (cfs) 8,070
Minnesota Jordan 8810 - 33% 3190 - 35% 1840 - 25% 4160 - 52%Mississippi Anoka 11700 - 44% 2770 - 30% 4100 - 56% 1930 - 24%
St. Croix Stillwater 6094 - 23% 3170 - 35% 1430 - 19% 1980 - 24%
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LN of variable Bands r2
T Tube (cm) 705 0.77–0.91Turbidity (NTU) 705 0.77–0.93
TSS (mg/L) 705 0.77–0.93VSS (mg/L) 705/670 0.80–0.94Chl a (µg/L) 705/670 or 705/620 0.75–0.93
NVSS (mg/L) 705 & 705/670 0.85–0.97a
NVSS/TSS (%) 705 & 705/620 0.73–0.91a
aR2
River Water Quality Model Development *
Characteristic Reflectance Spectra * Used most consistent (2004, 2005 and 2007) best fit band or band combination model for each water quality variable
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LN of variable Bands r2
T Tube (cm) 705 0.77–0.91Turbidity (NTU) 705 0.77–0.93
TSS (mg/L) 705 0.77–0.93VSS (mg/L) 705/670 0.80–0.94Chl a (µg/L) 705/670 or 705/620 0.75–0.93
NVSS (mg/L) 705 & 705/670 0.85–0.97a
NVSS/TSS (%) 705 & 705/620 0.73–0.91a
aR2
River Water Quality Model Development *
Characteristic Reflectance Spectra * Used most consistent (2004, 2005 and 2007) best fit band or band combination model for each water quality variable
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LN of variable Bands r2
T Tube (cm) 705 0.77–0.91Turbidity (NTU) 705 0.77–0.93
TSS (mg/L) 705 0.77–0.93VSS (mg/L) 705/670 0.80–0.94Chl a (µg/L) 705/670 or 705/620 0.75–0.93
NVSS (mg/L) 705 & 705/670 0.85–0.97a
NVSS/TSS (%) 705 & 705/620 0.73–0.91a
aR2
River Water Quality Model Development *
Characteristic Reflectance Spectra * Used most consistent (2004, 2005 and 2007) best fit band or band combination model for each water quality variable
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Pig’s Eye Lake and the Mississippi River at St. Paul showing the transition from
inorganic sediment dominated to phytoplankton dominated
conditions, August 30, 2007.
Turbidity Chlorophyll a NVSS:TSS
Pig’s Eye Lake
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Pig’s Eye Lake and the Mississippi River at St. Paul showing the transition from
inorganic sediment dominated to phytoplankton dominated
conditions, August 30, 2007.
Turbidity Chlorophyll a NVSS:TSS
Pig’s Eye Lake