Subsurface temperature estimation from remote sensing data using a clustering-neural network method-Reference-Cited by-同舟云学术

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Subsurface temperature estimation from remote sensing data using a clustering-neural network method

Published:2019-08 Issue: Volume:229 Page:213-222
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Lu Wenfang^ORCID,Su Hua^ORCID,Yang Xin,Yan Xiao-Hai^ORCID

Funder

National Natural Science Foundation of China

State Oceanic Administration

Outstanding Young Scientists Program in Universities of Fujian Province

SOA

Fujian Collaborative Innovation Center

Central Guide Local Science and Technology Development

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference41 articles.

1. A review of ocean/sea subsurface water temperature studies from remote sensing and non-remote sensing methods;Akbari;Water,2017

2. Estimation of ocean subsurface thermal structure from surface parameters: a neural network approach;Ali;Geophys. Res. Lett.,2004

3. Comparison of self-organizing maps classification approach with cluster and principal components analysis for large environmental data sets;Astel;Water Res.,2007

4. A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications;Atlas;Bull. Am. Meteorol. Soc.,2011

5. A study of the classification capabilities of neural networks using unsupervised learning: a comparison with K-means clustering;Balakrishnan;Psychometrika,1994

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