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Using remote sensing data to estimat...

Flores, Francisco Jose.

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Using remote sensing data to estimate leaf area index and foliar nitrogen of loblolly pine plantations.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using remote sensing data to estimate leaf area index and foliar nitrogen of loblolly pine plantations./
Author:	Flores, Francisco Jose.
Description:	115 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3013.
Contained By:	Dissertation Abstracts International64-07B.
Subject:	Agriculture, Forestry and Wildlife. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3098953

Using remote sensing data to estimate leaf area index and foliar nitrogen of loblolly pine plantations.
Flores, Francisco Jose.

Using remote sensing data to estimate leaf area index and foliar nitrogen of loblolly pine plantations. - 115 p.

Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3013.

Thesis (Ph.D.)--North Carolina State University, 2003.

High spectral resolution (Hyperspectral) and multispectral imagery was used to examine the spectral response of loblolly pine with contrasting LAI and foliar nitrogen concentration. The research studies included very different stand structures (age, number and size of the trees). As a result of treatments applied, seasonal, stand and site variation, the range in LAI (0.4–3.6 m<super>2</super> m<super>2</super>) and foliar nitrogen concentration (0.79–1.62%) on our study covered most of the range observed in midrotation loblolly pine plantations. Hyperspectral data was used to calculate narrowband vegetation indices (VIs) based on reflectance in the red (R) and near infrared (NIR). LAI was linearly related to the simple ratio (SR) vegetation index, the relationship was not affected by site, stand structure or season.Subjects--Topical Terms:

783690
Agriculture, Forestry and Wildlife.

Using remote sensing data to estimate leaf area index and foliar nitrogen of loblolly pine plantations.
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100 1 $a Flores, Francisco Jose. $3 1947531
245 1 0 $a Using remote sensing data to estimate leaf area index and foliar nitrogen of loblolly pine plantations.
300 $a 115 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3013.
500 $a Chair: H. Lee Allen.
502 $a Thesis (Ph.D.)--North Carolina State University, 2003.
520 $a High spectral resolution (Hyperspectral) and multispectral imagery was used to examine the spectral response of loblolly pine with contrasting LAI and foliar nitrogen concentration. The research studies included very different stand structures (age, number and size of the trees). As a result of treatments applied, seasonal, stand and site variation, the range in LAI (0.4–3.6 m<super>2</super> m<super>2</super>) and foliar nitrogen concentration (0.79–1.62%) on our study covered most of the range observed in midrotation loblolly pine plantations. Hyperspectral data was used to calculate narrowband vegetation indices (VIs) based on reflectance in the red (R) and near infrared (NIR). LAI was linearly related to the simple ratio (SR) vegetation index, the relationship was not affected by site, stand structure or season.
520 $a We also found a strong relationship between SR calculated from hyperspectral data and SR calculated from readily available Landsat 7 ETM+ data. Using that relationship, we determine an equation to estimate LAI from Landsat 7 ETM+ data.
520 $a Hyperspectral data was also used to estimate foliar nitrogen concentration and content of loblolly pine. We found a stronger relationship between nitrogen content and reflectance data than nitrogen concentration and reflectance data.
590 $a School code: 0155.
650 4 $a Agriculture, Forestry and Wildlife. $3 783690
650 4 $a Environmental Sciences. $3 676987
690 $a 0478
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710 2 0 $a North Carolina State University. $3 1018772
773 0 $t Dissertation Abstracts International $g 64-07B.
790 1 0 $a Allen, H. Lee, $e advisor
790 $a 0155
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3098953