On using the Landsat archive to map crop cover history across the United States

David M. Johnsondave.johnson@nass.usda.gov

Landsat Science Team Summer MeetingUniversity of Colorado, Boulder

August 8th, 2018

The Findings and Conclusions in This Preliminary Presentation Have Not Been Formally Disseminated by the U. S. Department of Agriculture and Should Not Be Construed to Represent

Any Agency Determination or Policy.

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CORN SOYBEANS WHEAT

Crop Area Recent History for the United States

Planted Area Equivalency

1984 2017

US Cropland Maps Back through Time?

1984: no 2017: yes

The last decade does exist via the NASS Cropland Data Layer

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Landsat History

30m CDL history

30m history yet to exploit

4 years of overlap with CDL history and Landsat 5!

But what did crop cover look like 1984 - 2007?

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Historical Crop Cover Mapping Methodology• Perform all steps in Google Earth Engine• Run classifications at county-level• Leverage the Landsat Surface Reflectance Data as available within Earth Engine• Create annually 4 cloud-free, median-value composites from Landsat imagery

• Roughly winter, spring, summer, fall• Sequential 64-day “windows” starting early march each year• Landsat 5 is the primary source, but Landsat 7 integrated for those years available, a few 4

images might show up too

• “Stack” 4 seasonal composites together to create annual imagery dataset• Extract training samples by intersection of the 2008, 2009, 2010, 2011 CDLs with

the respective annual dataset stacks• Combine those sample into one training set of a few thousand points

• Some assumption that 2008 – 2011 is representing the variability that can exist any year

• Derive decision trees using Earth Engine implementation of CART.• Apply the decision trees to the annually stacked data for each year 1984 - 2007• Calculate corn, soybean, and winter wheat areas from each year’s classification

Expected normal US NDVI crop phenology against implemented Landsat 64-day composite time windows

winter spring summer fall

Winter

Summer

Summer

Fall

2007 – Landsat 5 and 7 surface reflectance composites

Winter

Summer

Summer

Fall

1984 – Landsat 5 surface reflectance composites

Fill any missing with nearby +/- 2 years

2007PredictedCornCover

178,527.6 acres

1984PredictedCornCover

158,631.9 acres

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Minnehaha

CORN SOYBEANS WHEAT

Or better, NASS does have historical county-level crop area statistics

Thus, all maps generated and compared to NASS area statistics

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Minnehaha County Corn Area Statistics by Year

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NASS

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GEE

Minnehaha County Corn NASS to GEE Area Relationship

y = 1.3774x - 74757R² = 0.523

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GEE

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Minnehaha County Soybeans Validation

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GEE

y = 0.9984x + 3000.8R² = 0.4228

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Boulder County Example

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Boulder

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Boulder County Crop Area Statistics

Boulder County Corn Area Validation Results

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y = 0.2792x + 1604.3R² = 0.5536

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Boulder County Winter Wheat Area Validation Results

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y = 0.0167x + 3204.7R² = 0.0016

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Beyond the Example Counties - 75 counties Randomly Sampled (25 each for corn, soybeans, wheat)

Area Correlation Results of the 25 Corn Counties Sampled

corn 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 ave

R2 0.20 0.06 0.25 0.24 0.31 0.15 0.14 0.09 0.07 0.12 0.26 0.38 0.02 0.03 0.27 0.00 0.29 0.19 0.38 0.15 0.00 0.30 0.53 0.02 0.30 0.19

slope 0.63 -0.27 0.91 0.70 0.85 0.64 1.01 0.36 0.71 0.38 0.92 0.84 0.32 0.20 0.74 0.12 0.19 0.55 0.62 0.54 0.03 0.67 0.96 -0.22 0.63 0.52

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Area Correlation Results of the 25 Soybean Counties Sampled

soy 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 ave

R2 0.15 0.10 0.00 0.00 0.24 0.27 0.00 0.31 0.09 0.00 0.07 0.20 0.04 0.25 0.01 0.83 0.23 0.16 0.45 0.27 0.06 0.16 0.29 0.00 0.07 0.17

slope 0.20 -1.29 -0.07 -0.02 0.66 0.56 0.02 0.75 0.57 -0.07 0.29 0.66 0.28 0.56 0.11 0.64 0.32 0.93 -1.35 0.10 0.34 0.45 0.30 -0.02 0.19 0.20

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Area Correlation Results of the 25 Wheat Counties Sampled

wheat 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 ave

R2 0.31 0.02 0.01 0.13 0.11 0.29 0.17 0.00 0.11 0.19 0.27 0.10 0.06 0.08 0.17 0.34 0.52 0.00 0.31 0.12 0.00 0.13 0.05 0.33 0.27 0.16

slope 0.50 0.10 0.25 0.48 0.46 0.28 0.33 0.07 0.48 0.16 0.54 0.31 0.46 0.20 0.98 0.22 0.36 0.12 0.68 0.50 -0.02 0.50 0.04 0.31 0.64 0.36

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Closer Examination of 30 Rapidly Changing counties

1980 1990 2000 2010 2020

Area expansion

1980 1990 2000 2010 2020

Area Contraction

30 Rapidly Changing Counties GEE vs NASS area Results

corn expanding contracting

R2 0.75 0.02 0.77 0.00 0.65 0.62 0.35 0.43 0.24 0.18

slope 0.66 0.08 0.59 0.26 0.54 0.25 0.28 0.10 0.26 0.16

Soy

R2 0.12 0.40 0.02 0.38 0.35 0.61 0.46 0.62 0.02 0.07

Slope 0.34 0.51 0.18 0.48 0.37 0.19 0.16 0.55 0.03 0.04

Wheat

R2 0.43 0.07 0.28 0.15 0.00 0.23 0.44 0.67 0.23 0.20

Slope 0.51 1.54 0.45 0.53 -0.09 0.21 0.32 0.50 0.09 0.15

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The good The bad

Summary• Ability to retroactively generate land cover datasets in now possible

• The convergence of GEE and Landsat Surface Reflectance data make this pragmatic

• GEE still has computational limitations• But easy to forget just how much imagery is being used

• Quantitative results were marginal when assessed against area statistics• Qualitatively though many years looked reasonable and useful

• There are years with lacking imagery mostly due to persistent clouds

• Years with Landsat 7 alongside Landsat 5 did not perform better

• Composite windowing is subjective, one size does not fit all crops or regions.