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Inversion of Physical Models Using L-Band Airborne SAR Data for Soil Moisture Estimates at Field Scale

Kim, Seungbum and Huang, Huanting and Liao, Tienhao (2018) Inversion of Physical Models Using L-Band Airborne SAR Data for Soil Moisture Estimates at Field Scale. In: 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018). IEEE , Piscataway, NJ, pp. 6115-6118. ISBN 978-1-5386-7150-4. http://resolver.caltech.edu/CaltechAUTHORS:20181108-105444595

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Abstract

L-band capability to monitor soil moisture at field scale (∼100m) is examined using ground and airborne radar data. We report the recent progress in inverting physically-based forward models for radar scattering through time-series retrieval algorithm to systematically correct for the effect of the roughness and vegetation. The retrievals are performed for various vegetation types: pasture, corn, soybean, canola, and shrub over the entire vegetation growth cycles. Various changes to the forward and retrieval algorithm per each species are summarized. Assessed over all available fields of corn, bean, pasture, and wheat, the data-cube time-series inversion has the retrieval rmse of 0.050 to 0.075 m^3 /m^3, and the correlation of 0.5 to 0.9.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/IGARSS.2018.8519540DOIArticle
https://ieeexplore.ieee.org/document/8519540PublisherArticle
Additional Information:© 2018 IEEE. This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA.
Funders:
Funding AgencyGrant Number
NASA/JPL/CaltechUNSPECIFIED
Subject Keywords:L-band, soil moisture, SAR
Record Number:CaltechAUTHORS:20181108-105444595
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181108-105444595
Official Citation:S. Kim, H. Huang and T. Liao, "Inversion of Physical Models Using L-Band Airborne SAR Data for Soil Moisture Estimates at Field Scale," IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 2018, pp. 6115-6118. doi: 10.1109/IGARSS.2018.8519540
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90753
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:08 Nov 2018 20:33
Last Modified:08 Nov 2018 20:33

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