The role of the vegetation structure, primary productivity and senescence derived from airborne LiDAR and hyperspectral data for birds diversity and rarity on a restored site

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F21%3A87021" target="_blank" >RIV/60460709:41330/21:87021 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11310/21:10430480
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S016920462100027X" target="_blank" >https://www.sciencedirect.com/science/article/pii/S016920462100027X</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.lurbplan.2021.104064" target="_blank" >10.1016/j.lurbplan.2021.104064</a>

Result language
angličtina
Original language name
The role of the vegetation structure, primary productivity and senescence derived from airborne LiDAR and hyperspectral data for birds diversity and rarity on a restored site
Original language description
Management of restored areas requires ecologically meaningful spatial data providing objective measures of restoration success. Understanding relationships between species diversity on the one hand and habitat heterogeneity and productivity on the other can help establish such measures and prioritize restoration management. We used airborne LiDAR and hyperspectral data to derive characteristics of vegetation structure, primary productivity and senescent vegetation (i.e. old dead vegetation) for prediction of richness and rarity of bird communities colonizing newly available habitats restored after coal mining. In addition, we analysed, which type of restoration (i.e. agricultural, forest, or spontaneous succession) results in more favourable conditions. The boosted regression trees explained 52% and 12% of deviance of overall species richness and rarity, respectively. We found that the overall species richness was strongly affected by the variance in vegetation structure, while the rarity was also af
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10508 - Physical geography

Project
<a href="/en/project/GJ17-17156Y" target="_blank" >GJ17-17156Y: Fusion of LiDAR and UAV borne multispectral data to assess physiographic diversity of post-mining sites</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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