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

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10511 - Environmental sciences (social aspects to be 5.7)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

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

Name of the periodical

Ecological Engineering

ISSN

0925-8574

e-ISSN

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Volume of the periodical

100

Issue of the periodical within the volume

Mar

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

12

Pages from-to

219-230

UT code for WoS article

000394062600023

EID of the result in the Scopus database

2-s2.0-85007048805