Relationship Between Satellite-derived Phenology and Climatic Factors Over Northeastern Asia

Phenology means seasonal activities of vegetation, such as green-up, flowering, leaves-coloring or leaves-dropping. It is closely related to seasonal dynamics of the lower atmosphere and important elements in global models and vegetation monitoring. Time-series NDVI data derived from AVHRR or MODIS are suitable for phenological monitoring, because these sensors provide data with a high temporal frequency. In this study, we analyzed variations in green-up date over northeastern Asia from 1984 to 2004 with NOAA AVHRR data received at Institute of Industrial Science, The University of Tokyo. Firstly, daily AVHRR data were radiometrically and geometrically corrected, and data improve- ment procedures were implemented including sensor degradation, sensor change. Secondly, 10-day composite images were created and these images were converted to NDVI. However, constructed time-series NDVI data was contaminated with remained cloud or poor atmospheric condition. In order to overcome this problem, a noise reduction algorithm was applied to the data. Then, green- up date of each pixel was computed by using characteristics of annual profile of NDVI. The date was defined intersecting points between annual mean NDVI and variations in NDVI, and detected green-up date were consistent with ground observation data. In time-series analysis of green-up date, it was found that green-up in mixed forest tend to be getting earlier at a rate of -0.58 days/year, and the tendency was strong especially in northern part of study area. And as a result of sensitivity analysis between green-up date and meteorological data (temperature, precipitation, cloud cover), the area where green-up had a tendency to getting earlier showed a higher sensitivity to temperature rise.