XXIX-B3, 2012
Te practiced per year,
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accuracy was 80.3%
total of 2,000 pixels
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rigated rice (91.9%).
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0 100 200 400 Kilometers QE
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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
Double-cropped rice
Triple-cropped rice
Field crops
"1 Forests/orchards/perennial trees
Built-up areas
Water bodies
Figure 3. Spatial distribution of cropping patterns.
Classification results
Ground reference (pixels) Single- Double- Triple- Fielderops Forests/ Built-up Total
cropped rice cropped rice cropped rice orchards areas
Single-cropped rice 1,774 6 11 195 34 183 2,203
Double-cropped rice 0 1,838 372 76 126 294 2,706
Triple-cropped rice 0 109 1,547 16 19 8 1,699
Field crops 3 14 19 1,350 80 13 1,479
Forests/orchards 211 26 37 363 1,735 100 2,472
Built-up areas 12 7 14 0 6 1,402 1,441
Total 2,000 2,000 2,000 2,000 2,000 2,000 12,000
Producer accuracy (%) 88.7 91.9 73.38 67.5 86.75 70.1
User accuracy (96) 80.5 67.9 91.1 913 70.2 97.3
Overall accuracy (%) 80.3
Kappa coefficient 0.76
Table 1. Results of the classification accuracy assessment.
6. CONCLUSIONS
The objective of this study was to develop a classification
approach for mapping major cropping patterns in Southeast Asia
using time-series MODIS data. The data were processed using
wavelet transform and ANNs. The results indicated that filtered
NDVI patterns reflected temporal characteristics of different
cropping patterns. This information was important for selecting
training patterns used in ANNs classification. The ANNs applied
to the filtered time-series MODIS NDVI data confirmed its
validity for mapping cropping patterns in the study area. The
results archived by comparisons between the classified map and
the ground reference map indicated the overall accuracy of
80.3% and Kappa coefficient of 0.76. The lowest producer
accuracy was observed for the field crops class (67.5%) due to
temporal confusion in discriminating between this class and
other classes. The methods using wavelet transform and ANNs
for mapping major cropping patterns in Southeast Asia from
filtered time-series MODIS NDVI data could be transferred to
other regions in the world to replace costly field investigations.
REFERENCES
Atkinson, P.M., Curran, P.J., 1995. Defining an optimal size of
support for remote sensing investigations. /JEEE Transactions on
Geoscience and Remote Sensing, 33, pp. 768-776.