A Method to Construct High Spatial and Temporal resolution NDVI Data Set-STAVFM
一种高时空分辨率NDVI数据集构建方法-STAVFM

While Landsat images have advantageous spatial characteristics for describing vegetation properties, the temporal resolution of the data is 16 days which will be easily extended due to cloud contamination. This lengthy data re-acquirement rate often results in a dearth of imagery for a desired time interval. In contrast, although MODIS (MODerate-resolution Imaging Spectroradiometer) can only achieve an spatial resolution of 250m in its NDVI product, it has a high temporal resolution, covering the Earth up to multiple times per day. To combine the high spatial resolution of Landsat and high temporal resolution of MODIS data, an 18km*18km study area in upper reaches of Guanting reservoir was selected. The new method (STAVFM) for blending NDVI of different spatial and temporal resolutions to produce high temporal-spatial resolution NDVI dataset was developed based on STARFM (Spatial and Temporal Adaptive Reflectance Fusion Model). The result showed that the new method can combine the temporal information of MODIS NDVI and spatial difference information of ETM NDVI and predict the missed ETM NDVI with a high accuracy (the correlation coefficients of 3 pairs of observed and predicted ETM NDVI are 0.82, 0.90 and 0.91). A high temporal and high spatial resolution NDVI dataset was constructed, which maintain the temporal trend of high temporal resolution data and the detailed spatial difference information of high spatial resolution data.