Start Date: Sep 01, 2012
End Date: Aug 31, 2013
Ecological and crop condition monitoring requires high temporal and spatial resolution remote sensing data. A synthesized approach fusing multiple remote sensing inputs provides a feasible and economic solution for many application areas. In recent years, we have developed a Spatial Temporal Adaptive Reflectance Fusion Model (STARFM) that allows fusing high spatial resolution data from Landsat (16-day, 30m) with high temporal resolution data from MODIS (daily, 250-500m). The fused reflectance products can provide synthesized images with MODIS revisit frequency and Landsat spatial details. Here, we will build an operational STARFM approach to integrate existing MODIS reflectance products and freely available Landsat data for the SERVIR (Spanish “to serve”) project. The operational algorithm will maintain a cloud-free historical Landsat and MODIS image database for forward predictions as new MODIS acquisitions become available. The Landsat and MODIS image pairs will be updated once the latest clear Landsat and MODIS image pair becomes available. We will evaluate and test the STARFM algorithm for crop and ecological condition monitoring in the HKH region.