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