Determination of chlorophyll content in selected grass communities of Krkonoše mts. tundra based on laboratory spectroscopy and aerial hyperspectral dat
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F22%3A10449204" target="_blank" >RIV/00216208:11310/22:10449204 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-381-2022" target="_blank" >https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-381-2022</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5194/isprs-archives-XLIII-B3-2022-381-2022" target="_blank" >10.5194/isprs-archives-XLIII-B3-2022-381-2022</a>
Alternative languages
Result language
angličtina
Original language name
Determination of chlorophyll content in selected grass communities of Krkonoše mts. tundra based on laboratory spectroscopy and aerial hyperspectral dat
Original language description
The study focuses on the determination of chlorophyll content in four prevailing grasses in the relict arctic-alpine tundra located in the Krkonoše Mountains National Park, Czech Republic. We compared two methods for determination of leaf chlorophyll content (LCC) - spectrophotometric determination in the laboratory, and the LCC assessed by fluorescence portable chlorophyll meter CCM-300. Relationships were established between the LCCs and vegetation indices calculated from leaf spectra acquired with contact probe coupled with an ASD FieldSpec4 Wide-Res spectroradiometer. Canopy chlorophyll contents (CCC) were computed from the LCCs and green leaf area index (LAI), and modelled based on the field spectra measured by the spectroradiometer and the hyperspectral images acquired by Headwall Nano-Hyperspec (R) mounted on the DJI Matrice 600 Pro drone. The calculations are performed on datasets acquired in June, July and August 2020 together and separately for species and months. In general, the correlations based on June datasets work the best at both levels: median R(2) for all indices was 0.52 for all species together at leaf level and median R(2) = 0.47 at the canopy level (vegetation indices computed from field spectra). Canopy chlorophyll content map was created based on the results of stepwise multiple linear regression. The R(2) was 0.42 when using four wavelengths from the red and red edge spectral region. We attribute the weak model performance to a combination of several factors: leaf structure may bias LCC from laboratory measurements, effects of LAI variability on CCC, and the sampling design, probably not covering the whole phenology equally for all studied species.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10508 - Physical geography
Result continuities
Project
<a href="/en/project/LTAUSA18154" target="_blank" >LTAUSA18154: Assessment of ecosystem function based on Earth observation of vegetation quantitative parameters retrieved from data with high spatial, spectral and temporal resolution</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
ISBN
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ISSN
1682-1750
e-ISSN
2194-9034
Number of pages
8
Pages from-to
381-388
Publisher name
International Society for Photogrammetry and Remote Sensing
Place of publication
France
Event location
Nice
Event date
Jun 6, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000855647800053