Mapping forest aboveground biomass using airborne hyperspectral and LiDAR data in the mountainous conditions of Central Europe

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F17%3A00473954" target="_blank" >RIV/86652079:_____/17:00473954 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.ecoleng.2016.12.004" target="_blank" >http://dx.doi.org/10.1016/j.ecoleng.2016.12.004</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ecoleng.2016.12.004" target="_blank" >10.1016/j.ecoleng.2016.12.004</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Mapping forest aboveground biomass using airborne hyperspectral and LiDAR data in the mountainous conditions of Central Europe

Popis výsledku v původním jazyce

The study presents three methods for estimation of forest aboveground biomass (AGB) at tree and plot levels using different categories of airborne data. The first method estimates AGB from high spatial resolution hyperspectral (HS) data. The second method estimates AGB from airborne laser scanning data. The third method explores the synergy between hyperspectral and LiDAR data to estimate AGB. The results are compared with AGB estimated from field measurements. The results demonstrate that, 1) The biomass estimation from the HS data showed a good correlation with field biomass values for spruce, beech and mixture of these species at tree and plot levels, but also the highest uncertainties in comparison with the other two methods, 2) The biomass estimation from the LiDAR data had a strong correlation with field biomass values for spruce for tree level and a good correlation for spruce, beech and mixture of these species for plot level, 3) The biomass estimation from fused HS and LiDAR data showed the best results for tree and plot levels for the study sites. This study expands on previous research assessing the applicability of HS, LiDAR and fused datasets for AGB assessment. It proves the efficiency of using fused HS and LiDAR data and suggests the use of HS-based methods for biomass assessment when laser scanning data are not available.

Název v anglickém jazyce

Mapping forest aboveground biomass using airborne hyperspectral and LiDAR data in the mountainous conditions of Central Europe

Popis výsledku anglicky

The study presents three methods for estimation of forest aboveground biomass (AGB) at tree and plot levels using different categories of airborne data. The first method estimates AGB from high spatial resolution hyperspectral (HS) data. The second method estimates AGB from airborne laser scanning data. The third method explores the synergy between hyperspectral and LiDAR data to estimate AGB. The results are compared with AGB estimated from field measurements. The results demonstrate that, 1) The biomass estimation from the HS data showed a good correlation with field biomass values for spruce, beech and mixture of these species at tree and plot levels, but also the highest uncertainties in comparison with the other two methods, 2) The biomass estimation from the LiDAR data had a strong correlation with field biomass values for spruce for tree level and a good correlation for spruce, beech and mixture of these species for plot level, 3) The biomass estimation from fused HS and LiDAR data showed the best results for tree and plot levels for the study sites. This study expands on previous research assessing the applicability of HS, LiDAR and fused datasets for AGB assessment. It proves the efficiency of using fused HS and LiDAR data and suggests the use of HS-based methods for biomass assessment when laser scanning data are not available.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

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

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Ecological Engineering

ISSN

0925-8574

e-ISSN

—

Svazek periodika

100

Číslo periodika v rámci svazku

Mar

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

12

Strana od-do

219-230

Kód UT WoS článku

000394062600023

EID výsledku v databázi Scopus

2-s2.0-85007048805