Evaluating Variable Selection and Machine Learning Algorithms for Estimating Forest Heights by Combining Lidar and Hyperspectral Data

Machine learning has been employed for various mapping and modeling tasks using input variables from different sources of remote sensing data. For feature selection involving high- spatial and spectral dimensionality data, various methods have been developed and incorporated into the machine learnin...

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書誌詳細

主要な著者:	Sanjiwana Arjasakusuma, Sandiaga Swahyu Kusuma, Stuart Phinn
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2020-08-01
シリーズ:	ISPRS International Journal of Geo-Information
主題:	forest height feature selection dimensionality reduction lidar AISA hyperspectral
オンライン･アクセス:	https://www.mdpi.com/2220-9964/9/9/507
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