Estimating average tree crown size using high-resolution airborne data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67179843%3A_____%2F15%3A00447271" target="_blank" >RIV/67179843:_____/15:00447271 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/62156489:43410/15:43906789

Výsledek na webu

<a href="http://dx.doi.org/10.1117/1.JRS.9.096053" target="_blank" >http://dx.doi.org/10.1117/1.JRS.9.096053</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/1.JRS.9.096053" target="_blank" >10.1117/1.JRS.9.096053</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Estimating average tree crown size using high-resolution airborne data

Popis výsledku v původním jazyce

Tree crown size is a key parameter of tree structure that has a variety of uses, including assessment of stand density, tree growth, and amount of timber volume assessment. Remote sensing techniques provide a potentially low-cost alternative to field-based assessments, but require the development of algorithms to easily and accurately extract the required information. This study presents a method for average crown diameter estimation on a plot level based on high-resolution airborne data. The method consists of the combination of a window binarization procedure and a granulometric algorithm. This approach avoids the complicated crown delineation procedure that is currently used to estimate crown size. The method was applied to a spruce mountain forest and was verified on 23 reference plots. The method achieved best results of R-2 = 76% [RMSE = 0.37 m (11.2% of the observed mean)] and R-2 = 79% [RMSE = 0.49 m (16.7% of the observed mean)]. The study investigates the dependence of the algorithm results on the sun altitude of each image, and determines the optimal combination of spectral bands from hyperspectral airborne images for the application of the method. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

Název v anglickém jazyce

Estimating average tree crown size using high-resolution airborne data

Popis výsledku anglicky

Tree crown size is a key parameter of tree structure that has a variety of uses, including assessment of stand density, tree growth, and amount of timber volume assessment. Remote sensing techniques provide a potentially low-cost alternative to field-based assessments, but require the development of algorithms to easily and accurately extract the required information. This study presents a method for average crown diameter estimation on a plot level based on high-resolution airborne data. The method consists of the combination of a window binarization procedure and a granulometric algorithm. This approach avoids the complicated crown delineation procedure that is currently used to estimate crown size. The method was applied to a spruce mountain forest and was verified on 23 reference plots. The method achieved best results of R-2 = 76% [RMSE = 0.37 m (11.2% of the observed mean)] and R-2 = 79% [RMSE = 0.49 m (16.7% of the observed mean)]. The study investigates the dependence of the algorithm results on the sun altitude of each image, and determines the optimal combination of spectral bands from hyperspectral airborne images for the application of the method. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

GK - Lesnictví

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Applied Remote Sensing

ISSN

1931-3195

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

may 13

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

096053-1-096053-13

Kód UT WoS článku

000356276300001

EID výsledku v databázi Scopus

2-s2.0-84929645866