Land surface vegetation phenology reflects the responses of a terrestrial ecosystem to climate change. It is effective for monitoring the vegetation phenology of larger-scale area using time-series remotely sensed dataset. In this study, we used MODIS-NDVI and Landsat TM images for vegetation phenology analysis between 2001 and 2010 in Yilan. First, the monthly maximum value (MVC) images of MODIS were generated from 16-day NDVI time-series data. Second, the synthetic Landsat NDVI data were created using the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) algorithm for all dates when Landsat images were either unavailable or too cloudy. The monthly temperature and precipitation data during 2001 and 2010 and climate spatial layer were generated in ArcGIS 10.1 for vegetation-climate analysis. Then, the MODIS and Landsat images were provided as input for the phenology analysis toolbox TIMESAT, from which the phenological metrics including onset) start of growing season), offset) end of growing season) and the length of growing season were derived. The results was used to analyze the phonological parameters of vegetation, and used the climate data to know the relationship between the vegetation phenology and the climate change. In the end, the result of MODIS NDVI data and the synthetic Landsat NDVI data will be compared.
ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015; Crowne Plaza Manila GalleriaQuezon City, Metro Manila; Philippines; 24 October 2015 到 28 October 2015; 代碼 118634