Greenland Daily NDSI Data Reconstruction Based on Spatio-Temporal Extreme Gradient Boosting Model-Reference-Cited by-同舟云学术

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Greenland Daily NDSI Data Reconstruction Based on Spatio-Temporal Extreme Gradient Boosting Model

Published:2023-07-16 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Ye Fan¹,Cheng Qing¹,Hao Weifeng²,Yu Dayu³

Affiliation:

1. China University of Geosciences,School of Computer Science,Wuhan,China,430074

2. Wuhan University,Chinese Antarctic Center of Surveying and Mapping,Wuhan,China,430079

3. Wuhan University,School of Remote Sensing and Information Engineering,Wuhan,China,430079

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10283400.pdf?arnumber=10283400

Reference14 articles.

1. Xgboost: extreme gradient boosting;chen;R package version 0 4-2,2015

2. Reconstructing daily snow and ice albedo series for Greenland by coupling spatiotemporal and physical models;ye;Int J Appl Earth Obs Geoinf,0

3. Recognizing activities of the elderly using wearable sensors: a comparison of ensemble algorithms based on boosting

4. Reconstructing a Gap-Free MODIS Normalized Difference Snow Index Product Using a Long Short-Term Memory Network

5. Spatiotemporal Reconstruction of MODIS Normalized Difference Snow Index Products Using U-Net with Partial Convolutions

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