TY - JOUR
T1 - A crop phenology detection method using time-series MODIS data
AU - Sakamoto, Toshihiro
AU - Yokozawa, Masayuki
AU - Toritani, Hitoshi
AU - Shibayama, Michio
AU - Ishitsuka, Naoki
AU - Ohno, Hiroyuki
N1 - Funding Information:
We would thank three anonymous reviewers for their valuable comments. Statistical data were provided by the Production, Marketing, and Consumption Statistics Division of the Statistics Department, Ministry of Agriculture, Forestry and Fisheries of Japan. This study was funded by MAFF.
PY - 2005/6/30
Y1 - 2005/6/30
N2 - Information of crop phenology is essential for evaluating crop productivity and crop management. Therefore we developed a new method for remotely determining phenological stages of paddy rice. The method consists of three procedures: (i) prescription of multi-temporal MODIS/Terra data; (ii) filtering time-series Enhanced Vegetation Index (EVI) data by time-frequency analysis; and (iii) specifying the phenological stages by detecting the maximum point, minimal point and inflection point from the smoothed EVI time profile. Applying this method to MODIS data, we determined the planting date, heading date, harvesting date, and growing period in 2002. And we validated the performance of the method against statistical data in 30 paddy fields. As for the filtering, we adopted wavelet and Fourier transforms. Three types of mother wavelet (Daubechies, Symlet and Coiflet) were used in Wavelet transform. As the results of validation, the wavelet transform performed better than the Fourier transform. Specifically, the case using Coiflet (order = 4) gave remarkably good results in determining phenological stages and growing periods. The root mean square errors of the estimated phenological dates against the statistical data were: 12.1 days for planting date, 9.0 days for heading date, 10.6 days for harvesting date, and 11.0 days for growing period. The method using wavelet transform with Coiflet (order = 4) allows the determination of regional characteristics of rice phenology. We proposed this new method using the wavelet transform; Wavelet based Filter for determining Crop Phenology (WFCP).
AB - Information of crop phenology is essential for evaluating crop productivity and crop management. Therefore we developed a new method for remotely determining phenological stages of paddy rice. The method consists of three procedures: (i) prescription of multi-temporal MODIS/Terra data; (ii) filtering time-series Enhanced Vegetation Index (EVI) data by time-frequency analysis; and (iii) specifying the phenological stages by detecting the maximum point, minimal point and inflection point from the smoothed EVI time profile. Applying this method to MODIS data, we determined the planting date, heading date, harvesting date, and growing period in 2002. And we validated the performance of the method against statistical data in 30 paddy fields. As for the filtering, we adopted wavelet and Fourier transforms. Three types of mother wavelet (Daubechies, Symlet and Coiflet) were used in Wavelet transform. As the results of validation, the wavelet transform performed better than the Fourier transform. Specifically, the case using Coiflet (order = 4) gave remarkably good results in determining phenological stages and growing periods. The root mean square errors of the estimated phenological dates against the statistical data were: 12.1 days for planting date, 9.0 days for heading date, 10.6 days for harvesting date, and 11.0 days for growing period. The method using wavelet transform with Coiflet (order = 4) allows the determination of regional characteristics of rice phenology. We proposed this new method using the wavelet transform; Wavelet based Filter for determining Crop Phenology (WFCP).
KW - MODIS
KW - Paddy field
KW - Phenological stage
KW - Remote sensing
KW - Wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=21444460280&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=21444460280&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2005.03.008
DO - 10.1016/j.rse.2005.03.008
M3 - Article
AN - SCOPUS:21444460280
VL - 96
SP - 366
EP - 374
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
SN - 0034-4257
IS - 3-4
ER -