Detection of Rice Distribution Using NDVI Time-Series Similarity Measure

Abstract:

Rice cultivation is essential for agricultural production in Mekong Delta. Rice production estimation is based on the measurement of paddy field area and plantation system. Detection of paddy rice area and the plantation system is significant to food security decision. Based on the MODIS NDVI time-series data and the Dynamic Time Wrapping (DTW) similarity measure we detected the single and multiple rice distribution in Mekong Delta in 2010. Firstly, a combination of replacement and filter method was applied to denoising the MODIS NDVI time-series. Secondly, extracted the standard NDVI time-series cycle of single and multiple rice on MODIS NDVI time-series image. Thirdly, compare each pixel’s NDVI time-series cycle with each standard NDVI time-series cycle based on DTW distance. Finally, choose threshold in DTW distance and determine paddy rice’s distribution. Results were examined by sampling point and high resolution image of Mekong Delta; it shows that the extraction accuracy is 86%, relatively high for MODIS data classification outcome.

• Periodical: Advanced Materials Research (Volumes 955-959)
• Pages: 3864-3868
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.955-959.3864
• Online since: June 2014
• Authors: Xu Dong Guan, Chong Huang*, Gao Huan Liu
• Keywords: DTW, Mekong Delta, MODIS NDVI, Paddy Field, Remote Sensing

References

[1] T. Sakamoto, M. Yokozawa, H. Toritani, et al. A crop phenology detection method using time-series MODIS data. Remote Sensing of Environment. Vol. 96 (2005), pp.366-374.

DOI: 10.1016/j.rse.2005.03.008

[2] J.P. Evans, R. Geerken: Classifying rangeland vegetation type and coverage using a Fourier component based similarity measure. Remote Sensing of Environment. Vol. 105 (2006), pp.1-8.

DOI: 10.1016/j.rse.2006.05.017

[3] X. Xiao, S. Boles, et al. Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images. Remote Sensing of Environment. Vol. 100 (2006), pp.95-113.

DOI: 10.1016/j.rse.2005.10.004

[4] R. Geerken, B. Zaitchik and J. Evans: Classifying rangeland vegetation type and coverage from NDVI time series using Fourier Filtered Cycle Similarity. International Journal of Remote Sensing. Vol. 26 (2005), pp.5535-5554.

DOI: 10.1080/01431160500300297

[5] T. Sakamoto, N. Nguyen, et al. Spatial-temporal distribution of rice phenology and cropping systems in the Mekong Delta with special reference to the seasonal water flow of the Mekong and Bassac rivers. Remote Sensing of Environment. Vol. 100 (2006).

DOI: 10.1016/j.rse.2005.09.007

[6] J. Chen, P. Jonsson, et al. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter. Remote Sensing of Environment. Vol. 91 (2004), pp.332-344.

DOI: 10.1016/s0034-4257(04)00080-x

[7] S. Chu, E. Keogh, et al. Iterative Deepening Dynamic Time Warping for Time Series. Proceedings of the 2002 SIAM International Conference on Data Mining. pp.195-212.

DOI: 10.1137/1.9781611972726.12