Paper Info
Title
Evaluating The Application Of Microwave-Based Vegetation Observations In An Operational Soil Moisture Data Assimilation System
Abstract
A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.
Year
Venue
Keywords
2015
2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
data assimilation, soil moisture, observation error, vegetation density, optical depth
Field
DocType
ISSN
Vegetation,Satellite,Optical depth,Satellite imagery,Computer science,Remote sensing,Normalized Difference Vegetation Index,Data assimilation,Water content,Ensemble Kalman filter
Conference
2153-6996
Citations 
PageRank 
References 
0
0.34
4
Authors
4
Name
Order
Citations
PageRank
Iliana E. Mladenova100.34
John D. Bolten24710.83
Wade T. Crow353855.96
richard de jeu49817.89