MODIS-based Cropland Classification in North America

Teki Sankey and Richard MasseyNorthern Arizona University

Outline

• Datasets chosen for processing: 2000 and 2007• Preprocessing• Classification• Spatial and temporal extrapolation• Crop type labeling

Preprocessing workflow

MODIS data

Re-projection

Mosaicking

Layer stacking

NDVIBand 1 (RED) Band 2 (NIR)

Min-value 16-day Composite Min-value 16-day Composite Max-value 16-day Composite

Cloud Filtering/smoothing Cloud Filtering/smoothing Cloud Filtering/smoothing

47 tiles, 8-day composites (Feb 2000 to Feb 2001)(Feb 2007 to Feb 2008)

Composites

• Cloud-covered pixels make up for most of the noise in the data stack

• 16-day minimum value composites for band 1 and band 2 as cloud reflectance is higher

• 16-day maximum value composite for NDVI as cloud NDVI is lower

• NDVI maximum value composite is more useful in classification

Cloud filteringN

DVI

Days

NDV

I

Days

Return Value

Difference

Direction

Return Value

Difference

Direction

NDV

I

Days

NDV

I

DaysThresholds:-Return Value < 0.20Difference > 0.15

Cloud filteringN

DVI

Days

NDV

I

Days

DifferenceDifference

NDV

I

Days

NDV

I

DaysThresholds:-Difference > 0.15

Cluster computing workflow

• The NAU computing cluster has 32 cores each with 500 nodes, shared memory of 1.5 TB per node

• ENVI services engine and ENVI version 5.1

Master C Program

Batch file for execution

IDL code for each process

Batch file for IDL process

Node Allocation

IDL parallel process

NDVI stack - 2000

Year 2007

• No existing crop type map for 2000• 2000 classification needs labeling• 2007 = 2000 in region-wise annual precipitation• NASS CDL available for year 2007• Assumption: Similar spectral signatures between the two years

Region-wise annual precipitation statistics US (2000-2013, National Climatic Data Center)

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 20130

20

40

60

80

100

120

140

160

WesternCentralSouthernEastern

Inches

Year

NASS CDL availability for conterminous US

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

0 8 16 24 32 40 48

Number of states

Spatial and Temporal Extrapolation

USA North America2007 2000

Spatial extrapolation: GCE v1.0

• Most accurate irrigated class = AOI-1 (4/4 maps) (63,102,129 acres)• Further split: Agro-Ecological Zones

Agro-Ecological Zones based on length of growing period (GAEZ-FAO)

GCE v1.0 AOI-1 and Agro-Ecological zones

MODIS-based US Irrigation map, 2001 (Ozdogan and Gutman, 2008)

GCE v1.0 AOI-1, Agro-Ecological Zones, andIrrigated map

Irrigated map 2001 (US)

GCE v1.0 Class1 GCE v1.0 Class3

AEZ 1 AEZ 2 AEZ 3 AEZ 14

AEZ 1 AEZ 2 AEZ 3 AEZ 14

ISODATA Classification

Ove

rlay

…………

Irrigated map 2001 (US)

GCE v1.0 AOI-1 GCE v1.0 AOI-3

AEZ 1 AEZ 2 AEZ 3 AEZ 14

AEZ 1 AEZ 2 AEZ 3 AEZ 14

Class 1 Class 2 Class 25 Class 1 Class 2 Class

25

Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 100

ISODATA Classification

Class Grouping

Ove

rlay

………..

…………

… …

Spatial extrapolation: Spatial subsets

Spatial extrapolation

Spatial extrapolation: Labels

• Spectral correlation matrix• Classes are grouped together (R2 > 0.98)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

1 0.966 0.995 0.979 0.91 0.987 0.969 0.944 0.989 0.888 0.972 0.925 0.962 0.886 0.658 0.547

2 0.39 0.907 0.92 0.99 0.884 0.877 0.957 0.825 0.888 0.878 0.872 0.796 0.572 0.447

3 0.863 0.996 0.978 0.978 0.963 0.974 0.897 0.983 0.909 0.97 0.869 0.675 0.556

4 0.961 0.9 0.931 0.898 0.971 0.813 0.945 0.848 0.923 0.791 0.555 0.426

5 0.984 0.944 0.937 0.981 0.911 0.937 0.96 0.935 0.908 0.693 0.589

6 0.973 0.964 0.959 0.792 0.987 0.889 0.974 0.85 0.679 0.548

7 0.964 0.926 0.967 0.945 0.983 0.96 0.983 0.834 0.771

8 0.938 0.674 0.863 0.974 0.881 0.959 0.834 0.628

9 0.925 0.946 0.97 0.967 0.976 0.769 0.696

10 0.878 0.971 0.897 0.952 0.924 0.863

11 0.951 0.953 0.963 0.677 0.619

12 0.713 0.812 0.999 0.963

13 0.987 0.742 0.725

14 0.934 0.994

15 0.826

Temporal extrapolation: 20072000

2000 AOI + Irrigated map + Agro Eco zone 2007 NASS CDL2007 AOI + Agro Eco zone

Labeling of classes using

NASS CDL 2007

Master-file

• Primary layers– Cropland extent– Crop type– Crop intensity– Irrigated/Rainfed

• Secondary layers– Temperature– Precipitation– Elevation

Attribute Name ValueCropland Extent Non-Cropland 0

Cropland 1Irrigated/Rainfed Rainfed 0

Irrigated 1Crop Type Non-Cropland 0

Wheat 1Rice 2Corn 3

Barley 4Soybean 5Pulses 6

Potatoes 7Cotton 8Others 9

Intensity No crop 0Single crop 1

Double crop 2Double+ crop 3

Temperature Celsius -value-Precipitation Centimeters -value-

Elevation meters -value-

NASS CDL 2007

MIrAD US 2007

NCEP NARR 2007

SRTM DEM

Spectral database• Isodata classification for each AOI• Class comparison with master-file• Group classes based on attributes• Group member classes lie in ± 0.1 buffer of the group mean spectra for

more than 80% of bands• Spectral database for each attribute combination

Corn: Irrigated, Single crop

Wheat: Irrigated, Single crop

Soybean: Irrigated, Single crop

Spectral database

Attribute Name ValueCropland Extent Non-Cropland 0 Cropland 1Irrigated/Rainfed Irrigated 0 Rainfed 1Crop Type Non-Cropland 0 Wheat 1 Rice 2 Corn 3 Barley 4 Soybean 5 Pulses 6 Potatoes 7 Cotton 8 Others 9Intensity Single crop 0 Double crop 1 Triple crop 2 Triple+ crop 3Temperature Celsius -value-Precipitation Centimeters -value-Elevation meters -value-

Class ID Band 1 Band 2 ……… Band NClass 1 0.51 0.59 ……… 0.60Class 2 0.50 0.58 ……… 0.66. . . ……… 0.59. . . ……… 0.46. . . ……… 0.62. . . ……… 0.61Class M 0.49 0.57 ……… 0.63

Cropland attributes Grouped classes for one set of attributes

Extrapolation rules: CorrelationSpectral match between classes in 2007 and 2000

ISOdata classification 2007 resultISOdata classification 2000 result

1 2 3 4 5 6 7 8 9 10 11 12 13 14 151 0.966 0.995 0.979 0.91 0.987 0.969 0.944 0.989 0.888 0.972 0.925 0.962 0.886 0.658 0.5472 0.39 0.907 0.92 0.99 0.884 0.877 0.957 0.825 0.888 0.878 0.872 0.796 0.572 0.4473 0.863 0.996 0.978 0.978 0.963 0.974 0.897 0.983 0.909 0.97 0.869 0.675 0.5564 0.961 0.9 0.931 0.898 0.971 0.813 0.945 0.848 0.923 0.791 0.555 0.4265 0.984 0.944 0.937 0.981 0.911 0.937 0.96 0.935 0.908 0.693 0.5896 0.973 0.964 0.959 0.792 0.987 0.889 0.974 0.85 0.679 0.5487 0.964 0.926 0.967 0.945 0.983 0.96 0.983 0.834 0.7718 0.938 0.674 0.863 0.974 0.881 0.959 0.834 0.6289 0.925 0.946 0.97 0.967 0.976 0.769 0.696

10 0.878 0.971 0.897 0.952 0.924 0.86311 0.951 0.953 0.963 0.677 0.61912 0.713 0.812 0.999 0.96313 0.987 0.742 0.72514 0.934 0.99415 0.826

Extrapolation rules: Buffer

• If the input spectra lies within ± 0.1 buffer of the database spectra for more than 80% of bands it is assigned the same label

• If secondary parameters indicate Drought or Abundance, buffer is adjusted accordingly

• Overall validation threshold: 90%

Buffer

Extrapolation

• Generation of NDVI stack for non-US region• Spatial extrapolation of labels to non-US region using updated

spectral database• Input spectra is assigned the same label if lies within ± 0.1

buffer of the database spectra for more than 80% of bands it• Verification of extent using GCE v1.0 and secondary

parameters

Class Labels

Irrigated map 2000 (US)

GCE v1.0 Class1 GCE v1.0 Class3

AEZ 1 AEZ 2 AEZ 3 AEZ 14

AEZ 1 AEZ 2 AEZ 3 AEZ 14

Class 1 Class 2 Class 25 Class 1 Class 2 Class

25

ISODATA Classification

Class Grouping and Labeling: 2007

Ove

rlay

Label 1 Label 2 Label 3 Label 4 Label 5 Label 6Label 100

Temporal Extrapolation: 2007 2000

………..

…………

… …

Cropland map 2000 (US)

Cropland map 2007

Cropland map 2000 (North America)

Spatial Extrapolation: US non-US

Thank you!

Class labeling

• 2007 classes are labeled by geolocating at least 10 random points within the 2007 CDL class

• Classes between 2000 and 2007 are matched together via correlation (R2 >0.98)

Labeled as crop type ‘A’

Spatial and temporal extrapolation

US classes NA_class1 NA_class2 NA_class3 NA_class4 NA_class5 NA_class6 NA_class7 NA_class8 NA_class9 NA_class10 NA_class11 NA_class12 NA_class13 NA_class14 NA_class15 NA_class16 NA_class17 NA_class18

1 0.966 0.995 0.979 0.981 0.987 0.969 0.944 0.989 0.888 0.972 0.925 0.962 0.886 0.658 0.547 0.881 0.761 0.809

2 0.99 0.997 0.92 0.993 0.884 0.877 0.957 0.825 0.888 0.878 0.872 0.796 0.572 0.447 0.798 0.676 0.738

3 0.963 0.996 0.978 0.978 0.963 0.974 0.897 0.983 0.909 0.97 0.869 0.675 0.556 0.855 0.735 0.77

4 0.961 0.99 0.931 0.898 0.971 0.813 0.945 0.848 0.923 0.791 0.555 0.426 0.788 0.642 0.705

5 0.984 0.944 0.937 0.981 0.911 0.937 0.96 0.935 0.908 0.693 0.589 0.906 0.809 0.853

6 0.973 0.964 0.959 0.892 0.987 0.889 0.974 0.85 0.679 0.548 0.834 0.711 0.741

7 0.964 0.926 0.967 0.945 0.983 0.96 0.983 0.834 0.771 0.966 0.918 0.915

8 0.938 0.974 0.863 0.974 0.881 0.959 0.834 0.628 0.496 0.692 0.739

9 0.925 0.946 0.97 0.967 0.976 0.769 0.696 0.979 0.906 0.932

10 0.878 0.971 0.897 0.952 0.924 0.863 0.923 0.921 0.874

11 0.951 0.953 0.963 0.677 0.619 0.971 0.877 0.934

12 0.713 0.812 0.999 0.963 0.769 0.847 0.728

13 0.987 0.742 0.725 0.996 0.96 0.992

14 0.934 0.994 0.684 0.816 0.674

15 0.826 0.976 0.994 0.981

Spectral correlation matrix

Validation

• Preprocessing of MODIS data for validation year (2009)• Generation of NDVI stack• Generation of validation-file using spectral database• Validation-file has same structure as master-file of normal

year (2008)• Comparison of NASS CDL for 2009 with the validation file