IMPROVING THE ESTIMATION OF LEAF AREA INDEX FROM MULTISPECTRAL REMOTELY SENSED DATA

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" IMPROVING THE ESTIMATION OF LEAF AREA INDEX FROM MULTISPECTRAL REMOTELY SENSED DATA "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	149619
Doc. No	:	ET21411
Main Entry	:	Hongliang Fang
Title Proper	:	IMPROVING THE ESTIMATION OF LEAF AREA INDEX FROM MULTISPECTRAL REMOTELY SENSED DATA
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	Leaf Area Index (LAI) is an important structural property of surface vegetation. Manyalgorithms use LAI in regional and global biogeochemical, ecological, andmeteorological applications. This dissertation reports several new, improved methods toestimate LAI from remotely sensed data.To improve LAI estimation, a new atmospheric correction algorithm was developed forthe Enhanced Thematic Mapper Plus (ETM+) imagery. It can effectively estimate thespatial distribution of atmospheric.
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL44570.pdf
Title and statement of responsibility and	:	IMPROVING THE ESTIMATION OF LEAF AREA INDEX FROM MULTISPECTRAL REMOTELY SENSED DATA [Thesis]