文件名称:A-crop-phenology-detection-method-using-time-seri
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- 2012-11-26
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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) prescr iption 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
-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) prescr iption 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
method for remotely determining phenological stages of paddy rice. The method consists of three procedures: (i) prescr iption 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
-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) prescr iption 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
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A crop phenology detection method using time-series.pdf