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Abstract
Statistical correction methods, the Cumulative Distribution Function (CDF) matching technique and Regional Statistics Method (RSM) are applied to adjust the limited temporal variability of Advanced Microwave Scanning Radiometer E (AMSR-E) data using the Common Land Model (CLM). The temporal variability adjustment between CLM and AMSR-E data was conducted for annual and seasonal periods for 2003 in the Little River region, GA. The results showed that the statistical correction techniques improved AMSR-E’s limited temporal variability as compared to ground-based measurements. The regression slope and intercept improved from 0.210 and 0.112 up to 0.971 and -0.005 for the non-growing season. The R2 values also modestly improved. The Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) products were able to identify periods having an attenuated microwave brightness signal that are not likely to benefit from these statistical correction techniques.
Department
Earth Systems Research Center
Publication Date
4-14-2008
Journal Title
Sensors
Publisher
MDPI AG
Digital Object Identifier (DOI)
Document Type
Article
Recommended Citation
Choi, M., and J.M. Jacobs. 2008. Temporal variability corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) surface soil moisture: Case study in SMEX03 Little River, Georgia, U.S. Sensor. 8(4). 2617-2627.
Comments
This is an article published by MDPI AG in Sensors in 2008, available online: https://dx.doi.org/10.3390/s8042617