A New Machine-Learning-Based Calibration Scheme for MODIS Thermal Infrared Water Vapor Product Using BPNN, GBDT, GRNN, KNN, MLPNN, RF, and XGBoost
Author:
Affiliation:
1. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
2. Meteorological Observation Center, China Meteorological Administration, Beijing, China
Funder
Research Grants Council of the Hong Kong Special Administrative Region, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/36/10354519/10410869.pdf?arnumber=10410869
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2. WATER VAPOR AND THE DYNAMICS OF CLIMATE CHANGES
3. Anthropogenic and Natural Radiative Forcing pages 705 to 740
4. A model for the relationship between tropical precipitation and column water vapor
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