Improving soil moisture estimation from polarimetric radar observations: A study of scene heterogeneity, land cover, and vegetation seasonality - researchr publication related

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Mariko Burgin, Jakob van Zyl. Improving soil moisture estimation from polarimetric radar observations: A study of scene heterogeneity, land cover, and vegetation seasonality. In 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016, Beijing, China, July 10-15, 2016. pages 7524-7526, IEEE, 2016. [doi]

The following publications are possibly variants of this publication:

Analysis of Polarimetric Radar Data and Soil Moisture From Aquarius: Towards a Regression-Based Soil Moisture Estimation AlgorithmMariko S. Burgin, Jakob J. van Zyl. staeors, 9(8):3497-3504, 2016. [doi]

Regression-based soil moisture estimation from SMAP polarimetric radar data with Aquarius derived coefficientsMariko S. Burgin, Jakob J. van Zyl. igarss 2017: 4136-4138 [doi]

Soil Moisture Estimation by Linear Regression from Smap Polarimetric Radar Data with Aquarius Derived CoefficientsMariko S. Burgin, Lukas Mandrake, Gary B. Doran Jr., Brian D. Bue, Jakob J. van Zyl. igarss 2018: 1816-1817 [doi]

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