US Croplands Richard Massey Dr Teki Sankey

Objectives 1.Classify annual cropland extent, Rainfed-Irrigated, and crop types for the US at 250m resolution 2.Develop an automated classification algorithm

Data Overview 1.MODIS MOD09Q1 8-day composite tiles for band 1 and band 2 2.FAO Global Agro Ecological Zones (GAEZ) for spatial stratification 3.Cropland extent and crop type distribution derived from GCE v1.0 and NASS Cropland Data Layer (CDL) 4.MIrAD-US 2007 classification of Irrigated US

Data Overview: MODIS NDVI dataset 16-day NDVI time-series derived from MOD09Q1 band 1 and band tiles in each annual stacks (3.12 TB/year) 16-day maximum value NDVI composite layer stacks: 24/year Cloud filtering to minimize noise

Data Overview: Global Agro-Ecological Zones (AEZ) (Version 3.0, FAO, UN) AEZ Total Area (Mha) Crop Area (Mha) US area percent % Cropland percent %

Data Overview: Cropland Data Layer (CDL) National Agricultural and Statistics Service, USDA Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops CDL 2008 Crop typeRainfed area (Mha) Percent area of Rainfed cropland (%) Irrigated area (Mha) Percent area of Irrigated cropland (%) Total cropland area (Mha) Percent area of total cropland (%) Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops Total

Data Overview: Sub-zones in AEZ Number of sub- zones: 298

Data Overview: Rainfed- Irrigated map MIrAD-2007 (Pervez and Brown, 2010) Percent area of US land under irrigation: 3% (27.9 Mha) Percent area of US croplands under irrigation: 22%

Temporal Extent: 2 approaches Year-specific classification 1.Cropland extent and crop type classification for 2008 and Classification Training: 2008: CDL crop type and extent from : CDL crop type and extent from 2010 Generalized Temporal Average (TA) 1.Cropland extent and crop type classification for annually 2.Classification Training: Temporal Average 2008: Average Precipitation 2010: Above-average precipitation 2012: Below-average precipitation

Cropland extent Binary overlay of crop classes Samples and extent: Generalized TA Sub-zones NDVI stack (Rainfed-Irrigated) AEZ CDL stack CDL stack CDL stack

Cropland extent: Generalized TA (CDL Temporal Average)

NDVI Temporal Average Samples Random samples for each subzone (center of the field) 3000 max samples/subzone Proportion of each crop class was based on ratio of its cropland area across all three years. Sample pixels were divided into training (75%) and validation (25%) datasets AEZ: 6 sub-zone: 4, 2008AEZ: 10 sub-zone: 14, 2011

AEZ: 6 sub-zone: 4 AEZ: 10 sub-zone: 17 If NDVI 15 + NDVI 16 < Corn-Soybean Wheat/Barley If NDVI 16 + NDVI 17 > Cotton Decision Tree Classification Corn-Soybean If NDVI 13 + NDVI 14 < Others

Corn-Soybean Wheat-Barley Corn-Soybean Wheat-Barley CDL 2008 Classified image CDL 2008 Classified image AEZ: 6 sub-zone: 4, 2008 AEZ: 10 sub-zone: 14, 2011 CORN- SOYBEAN WHEAT- BARLEYTotal User-s Acc % CORN- SOYBEAN72,49526,23998, WHEAT- BARLEY25,052121,498146, Total97,547147,737245,284 Prod Acc % Overall81.1% CORN- SOYBEANCOTTONOthersTotalUser-s Acc % CORN- SOYBEAN12,8875, , COTTON5,00319, , Others1, ,0133, Total18,89824,8863,08447,784 Prod Acc % Overall76.3% Decision Tree Classification Corn-Soybean Cotton Others Corn-Soybean Cotton Others

Decision Tree Classification Sub-zones (n = 298) NDVI stack (Rainfed-Irrigated) Cropland extent Decision tree classification for each sub-zone Mosaicking all sub- zones together Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops Classified crop type map

Algorithm Overview: Generalized TA Divide each AEZ into sub-zones using CDL 2008, 2010, and 2014 Sample spectra for each sub-zone using CDL 2008, 2010, and 2014 Combined crop map for US Subset NDVI time-series by AEZ, Rainfed-Irrigated, Extent Decision Tree classification Crop type map for each sub-zone Combined crop map for each AEZ Iterative Optimizaton Comparison with CDL Data preparation Training Classification Assimilation of Results Cropland extent by binary overlay CDL

Produced crop type maps for annually Irrigated and Rainfed Mapping accuracy calculated Pixel-to-pixel comparison with CDL Additional assessment coming from Kamini/Russ Results: Generalized TA Overall accuracies (%) for Rainfed-Irrigated maps in the US for years Rainfed Irrigated

Results: Generalized TA (By AEZ) AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ Overall Overall accuracies (%) for all AEZs in the US for years

CORN-SOYBEANWHEAT-BARLEYPOTATOALFALFACOTTONRICEOTHERSTotalUser-s Acc CORN-SOYBEAN14,447,100478,3563,738135,82583,17419,916371,01116,089, WHEAT-BARLEY354,8482,897,13023,296170,036110, ,8444,342, POTATO1,87827,07312,4298,610009,15259, ALFALFA356,022111,7274,420626,6717, ,5351,178, COTTON141,729115,14805,405620,2574,130120,5091,007, RICE47, ,828189,33112,346234, OTHERS141,103198,2318,48249,871144,5119,1641,909,5782,160, Total16,690,6163,328,14152,365996,720769,673124,1682,979,97525,071,658 Prod Acc Overall77.7 % Kappa: CDL crop types 2009 Classified crop type Results: Generalized TA Example Combined crop type map for 2009 Error matrix between CDL and classified map Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops

CORN-SOYBEANWHEAT-BARLEYPOTATOALFALFACOTTONRICEOTHERSTotalUser-s Acc CORN-SOYBEAN14,447,100278,3563,73835,825113,17439,916371,01116,089, WHEAT-BARLEY354,8482,747,13023,296120,036110, ,8443,842, POTATO1,87821,07328,4298,610009,15259, ALFALFA156,022111,7274,420826,6717, ,5351,178, COTTON241,72955,14805,405520,2574,130120,5091,007, RICE147, ,82869,33112,346234, OTHERS241,103198,2318,48249,871144,5119,1641,609,5782,160, Total16,690,6163,328,14152,365996,720899,673124,1682,979,97525,071,658 Prod Acc Overall75.5 % Kappa: CDL crop types 2011 Classified crop types Error matrix between CDL and classified map Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops Results : Generalized TA Example Combined crop type map for 2011 Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops

Area Estimates: Generalized TA Area (Mha) estimated in the annual classification ( ) Crop type Area of classified map 2008 (Mha) Area of classified map 2009 (Mha) Area of classified map 2010 (Mha) Area of classified map 2011 (Mha) Area of classified map 2012 (Mha) Area of classified map 2013 (Mha) Area of classified map 2014 (Mha) CORN-SOYBEAN WHEAT-BARLEY POTATO ALFALFA COTTON RICE OTHERS Total Crop type Area of CDL map 2008 (Mha) Area of CDL map 2009 (Mha) Area of CDL map 2010 (Mha) Area of CDL map 2011 (Mha) Area of CDL map 2012 (Mha) Area of CDL map 2013 (Mha) Area of CDL map 2014 (Mha) CORN-SOYBEAN WHEAT-BARLEY POTATO ALFALFA COTTON RICE OTHERS Total Area (Mha) estimated in annual CDL ( )

Comparison of area estimates

Produced crop type maps for 2008 and 2010 Irrigated and Rainfed Mapping accuracy calculated Pixel-to-pixel comparison with CDL Additional assessment coming from Kamini/Russ Results: Year-specific classification Overall accuracies (%) Rainfed Irrigated

Results: Year-Specific Classification By crop type, 2008 example CORN-SOYBEANWHEAT-BARLEYPOTATOALFALFACOTTONRICEOTHERSTotalUser-s Acc CORN-SOYBEAN 13,017,100475, ,969112,60172,445521,62914,358, WHEAT-BARLEY 547,3214,250,08011,118121,22341, ,6505,277, POTATO 17,79515,47420,8427, ,64768, ALFALFA 151,710132,4121,464595,8252, ,477969, COTTON 104,77444,20202,824557,61612,11080,692802, RICE 74, ,873137,02310,377228, OTHERS 574,915380,4417,76986,69681,7888,2932,415,6903,555, Total 14,487,9755,299,04442,134972,686801,675231,1003,425,16225,259,776 Prod Acc Overall83.0 % Kappa: CDL crop types2008 Classified crop types Error matrix between CDL and classification Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops

Comparison of overall accuracies Year-specific classification accuracies (%) Rainfed Irrigated Rainfed Irrigated Generalized TA classification accuracies (%) AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ Overall AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ AEZ Overall

Conclusion Developed Generalized Temporal Average algorithm to classify crop types annually between Generalized Temporal Average classification performs adequately and particularly well for 2012 Developed Year-specific classification algorithms for 2008 and 2010 Year-specific classification has higher accuracies than Generalized Temporal Average (~83% Vs ~78%) US crop type map for 2008 using year-specific classification is available at Publication manuscript: In preparation

Moving Forward Extend Generalized Temporal Average classification to in the USA Crop intensities at 250m Develop Generalized Temporal Average classification algorithm for Central America and Canada (between ) at 250m resolution Data fusion of MODIS 250m and Landsat 30m to generate high resolution time-series data for North America

Thank you

Sample cleaning using 5x5 buffer (pixel size 56m) CDL 2008 CDL 2008 after removing boundary pixels Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops Corn-Soybean Wheat-Barley Potato Alfalfa Cotton Rice Other Crops

Spectral Separability NDVI spectra for many crop types still look similar. We identify areas where each spectra differs from others: Quantitative method Automated approach Parameter for the decision tree Rice Corn Soybean Corn Separability=1.0 for both crops Separability=0.5 for Corn, 0.45 for Soybean

NASS CDL availability for conterminous US

Fallow Cropland Classified using: 1.NDVI time-series thresholds derived from CDL random samples 2.Different time-series thresholds for AEZ 2 – 6 and AEZ 7 – 13 3.NDVI time-series standard deviation < 0.05 for growing months (April - September) Fallow cropland area Year CDL Fallow (Mha) Classified Fallow (Mha)

Data Overview: Global Agro-Ecological Zones (AEZ) (Version 3.0, FAO, UN) AEZ Total Area (Mha) Crop Area (Mha) US area percent % Cropland percent %