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Agricultural Research Service United States Department of Agriculture
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OPE3
Crop Condition and Yield Research
Jornada Experiment
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Soil Moisture Program
 

Research Project: INTEGRATING MODIS AND LANDSAT DATA FOR ECOLOGICAL AND CROP CONDITION....FOR THE SERVIR PROJECT IN HINDU-KUSH HIMALAYA (HKH)REGION

Location: Hydrology and Remote Sensing Laboratory

Project Number: 1245-13610-028-40
Project Type: Reimbursable

Start Date: Sep 01, 2012
End Date: Aug 31, 2013

Objective:
To build an operational data fusion approach to integrate existing Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance products and Landsat data for ecological and crop condition monitoring in HKH region.

Approach:
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.

   

 
Project Team
Gao, Feng
 
Related National Programs
  Water Availability and Water Management (211)
 
 
Last Modified: 02/18/2013
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