Estimating snow depth Inversion Model Assisted Vector Analysis based on temperature brightness for North Xinjiang region of China-Reference-Cited by-同舟云学术

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Estimating snow depth Inversion Model Assisted Vector Analysis based on temperature brightness for North Xinjiang region of China

Published:2020-06-05 Issue:sup2 Volume:54 Page:265-274
ISSN:2279-7254
Container-title:European Journal of Remote Sensing
language:en
Short-container-title:European Journal of Remote Sensing

Author:

Chen LianJun¹,Muthu BalaAnand²,cb Sivaparthipan²³^ORCID

Affiliation:

1. School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China

2. V.R.S. College of Engineering & Technology, Villupuram, India

3. Department of Computer Science & Engineering, SNS College of Technology, Coimbatore, India

Publisher

Informa UK Limited

Subject

Applied Mathematics,Atmospheric Science,Computers in Earth Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/22797254.2020.1771217

Reference28 articles.

1. Improved snow depth retrieval algorithm in China area using passive microwave remote sensing data

2. Estimation of snow depth from passive microwave brightness temperature data in forest regions of northeast China

3. Snow depth and snow water equivalent estimation from AMSR-E data based on a priori snow characteristics in Xinjiang, China

4. Using a Support Vector Machine and a Land Surface Model to Estimate Large-Scale Passive Microwave Brightness Temperatures Over Snow-Covered Land in North America

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2. Moderate-resolution snow depth product retrieval from passive microwave brightness data over Xinjiang using machine learning approach;International Journal of Digital Earth;2024-01

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