Evaluation of various spectral inputs for estimation of forest biochemical and structural properties from airborne imaging spectroscoopy data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F16%3A00461345" target="_blank" >RIV/86652079:_____/16:00461345 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.5194/isprs-archives-XLI-B7-961-2016" target="_blank" >http://dx.doi.org/10.5194/isprs-archives-XLI-B7-961-2016</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5194/isprs-archives-XLI-B7-961-2016" target="_blank" >10.5194/isprs-archives-XLI-B7-961-2016</a>

Result language

angličtina

Original language name

Evaluation of various spectral inputs for estimation of forest biochemical and structural properties from airborne imaging spectroscoopy data

Original language description

In this study we evaluated various spectral inputs for retrieval of forest chlorophyll content (Cab) and leaf area index (LAI) from high spectral and spatial resolution airborne imaging spectroscopy data collected for two forest study sites in the Czech Republic (beech forest at Štítná nad Vláří and spruce forest at Bílý Kříž). The retrieval algorithm was based on a machine learning method – support vector regression (SVR). Performance of the four spectral inputs used to train SVR was evaluated: a) all available hyperspectral bands, b) continuum removal (CR) 645 – 710 nm, c) CR 705 – 780 nm, and d) CR 680 – 800 nm. Spectral inputs and corresponding SVR models were first assessed at the level of spectral databases simulated by combined leaf-canopy radiative transfer models PROSPECT and DART. At this stage, SVR models using all spectral inputs provided good performance (RMSE for Cab < 10 μg cm2 and for LAI < 1.5), with consistently better performance for beech over spruce site. Since application of trained SVRs on airborne hyperspectral images of the spruce site produced unacceptably overestimated values, only the beech site results were analysed. The best performance for the Cab estimation was found for CR bands in range of 645 – 710 nm, whereas CR bands in range of 680 – 800 nm were the most suitable for LAI retrieval. The CR transformation reduced the across-track bidirectional reflectance effect present in airborne images due to large sensor field of view.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

EH - Ecology - communities

OECD FORD branch

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Project

<a href="/en/project/LO1415" target="_blank" >LO1415: CzechGlobe 2020 – Development of the Centre of Global Climate Change Impacts Studies</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2016

Confidentiality

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

Article name in the collection

The international archives of the Photogrammetry, Remote sensing and spatial information sciences

ISBN

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ISSN

1682-1750

e-ISSN

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Number of pages

6

Pages from-to

961-966

Publisher name

International Society of Photogrammetry and Remote Sensing

Place of publication

s. l.

Event location

Prague

Event date

Jul 12, 2016

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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