Analysis of Water Clarity in Lake Superior using MODIS Images Yan Wang, Beth Peterson Forest...
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Transcript of Analysis of Water Clarity in Lake Superior using MODIS Images Yan Wang, Beth Peterson Forest...
Lake Superior Water Clarity
Analysis of Water Clarity in Lake Superior using MODIS ImagesYan Wang, Beth Peterson
Forest Resources 3262 / 5262Remote Sensing of Natural Resources and Environment12/10/12
Objective• Analyze water quality in Lake Superior near
Duluth• 2011 and 2012• June – September
• Evaluate the effectiveness of MODIS data for determining water clarity
• Evaluate the compatibility of MODIS data with field data from streams.
MODIS Data• Satellite Aqua (as opposed to Tera)• ~18:50 passover time• Product: MDY09A1 • bands 1–7• 500m resolution• 8 day composite (reduce cloud cover)
• Use bands 1 and 3 (red and blue)• 8 images per month (4 in each band)• Extracted: DN of the point at each site where field
data was collected
Field Data
• Turbidity Recorded as Nephelometric Turbidity Units (NTU)
• Turbidity data from Lake Superior Streams• ~7 streams (depending on availability)• Data recorded ~every 15 minuites• Latitude and Longitude for each site
• Extracted: average of data collected at 18:30, 18:45, 18:90 for all 8 days of each image
Preprocess
• Geometry correction, atmospheric correction :
MRT tool
• ArcGIS: clip image and extract DN value of field samples from image
• Process field sample of turbidity
Regression Analysis
siteBand1 Band3
(Band3-Band1) / (Band3+Band1 field ln(field)
Chester Creek 395 172 -0.39329806 0.84375 -0.1699
Tischer Creek 605 370 -0.241025641 1.3625 0.309321
Kingsbury Creek 532 267 -0.331664581 5.545833 1.713047
Miller Creek 655 304 -0.366006257 5.65 1.731656
Oliver Bridge - St Louis River 661 317 -0.351738241 100.3775 4.608938
WLSSD 436 322 -0.150395778 5.36875 1.680595
Y=ln(field)X=(B3-B1)/(B3+B1)
-0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1
-1
0
1
2
3
4
5
f(x) = 0.600789237895685 x + 2.41251821812401R² = 0.002447531627357
Results: Algorithms
Month N equation R²
June24
y = 0.0041x - 0.2998
R² = 0.0024
July24 y = -0.0202x -
0.2635R² = 0.3799
August
24 y = 0.006x - 0.2982
R² = 0.0168
Sept 24 y = 0.0004x - 0.3366
R² = 0.0002
Month N equation R²
June 15y = 9.2004x + 6.0675
R² = 0.1396
July 11y = -11.955x - 0.7553
R² = 0.3609
August 10y =- 50.181x - 12.919
R² = 0.76
September 6
y = -1.62x + 3.0091
R² = 0.1518
2011 2012
Results: 2011 Images
June July
August September
Results: 2012 Images
June July
August September
Accuracy Assessment
Site and Julian date Band 1 Band3
Regression Equation used
Predicted Turbidity
Actual Turbidity
DE 185 476 252y = -11.955x - 0.7553
2.923161538 4.96
OS 185 448 241y = -11.955x - 0.7554 2.83640537 10.7
WE 185 395 188y = -11.955x - 0.7555 3.48944271 14
DE 193 600 391y = -11.955x - 0.7556
1.765986579 3.2
OS 193 606 407y = -11.955x - 0.7557
1.593214314 2.1
WE 193 605 393y = -11.955x - 0.7558
1.784239078 7.6
July 2012
Accuracy Assessment
1 1.5 2 2.5 3 3.5 40
2
4
6
8
10
12
14
16
f(x) = 4.59520497378437 x − 3.92937599012964R² = 0.616438316808711
July
Series1Linear (Series1)
Predicted (NTU)
Fie
ld (
NTU
)
Discussion• Regression analysis
produced very poor results.• Streams were too small in
comparison to MODIS pixels• Missing or inaccurate turbidity
data
• Turbidity values near the shore were different than values for the center of the lake.
• Much more variability in 2012, possibly as a result of the large flood that occurred early in the year