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