Comprehensive evaluation of soil moisture retrieval models under different crop cover types using C-band synthetic aperture radar data-Reference-Cited by-同舟云学术

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Comprehensive evaluation of soil moisture retrieval models under different crop cover types using C-band synthetic aperture radar data

Published:2018-05-03 Issue:9 Volume:34 Page:1022-1041
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Kumar P.¹,Prasad R.²,Choudhary A.³,Gupta D. K.²,Mishra V. N.²,Vishwakarma A. K.²,Singh A. K.¹,Srivastava P. K.⁴

Affiliation:

1. Department of Physics, Institute of Science, Banaras Hindu University, Varanasi, India

2. Department of Physics, Indian Institute of Technology (BHU), Varanasi, India

3. Environmental Science Division, Central Road Research Institute, New Delhi, India

4. Institute of Environment and Sustainable Development (BHU), Varanasi, India

Funder

DST, New Delhi, India

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2018.1464601

Reference69 articles.

1. Estimating soil moisture using remote sensing data: A machine learning approach

2. Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach

3. Review of Machine Learning Approaches for Biomass and Soil Moisture Retrievals from Remote Sensing Data

4. Support Vector Regression to Forecast the Demand and Supply of Pulpwood

5. Coupling SAR C-Band and Optical Data for Soil Moisture and Leaf Area Index Retrieval Over Irrigated Grasslands

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