Landsat Data Based Prediction of Loblolly Pine Plantation Attributes in Western Gulf Region, USA

The suitability of using Landsat sensor variables to predict key stand attributes, including stand average dominant/codominant tree height (HT), mean diameter at breast height (DBH), the number of trees per hectare (NT), basal area per hectare (BA), and stand density index (SDI), of intensively mana...

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Bibliographic Details

Published in:	Remote Sensing
Main Authors:	Chongzhi Chen, Ke Wang, Luming Fang, Jason Grogan, Clinton Talmage, Yuhui Weng
Format:	Article
Language:	English
Published:	MDPI AG 2022-09-01
Subjects:	loblolly pine forestry inventory Landsat series regression analysis random forests
Online Access:	https://www.mdpi.com/2072-4292/14/19/4702