Vegetation mapping and monitoring by unmanned aerial systems (UAS) - current state and perspectives

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985939%3A_____%2F23%3A00574368" target="_blank" >RIV/67985939:_____/23:00574368 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/44555601:13520/23:43897367

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/abs/pii/B9780323852838000084?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/B9780323852838000084?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/B978-0-323-85283-8.00008-4" target="_blank" >10.1016/B978-0-323-85283-8.00008-4</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Vegetation mapping and monitoring by unmanned aerial systems (UAS) - current state and perspectives

Popis výsledku v původním jazyce

Over the last years, unmanned aerial systems (UASs) have been receiving much attention, becoming essential tools for characterizing vegetation patterns and processes. Thanks to its ultrahigh spatial resolution and flexibility, UASs bear potential to bridge the gap between field surveys and satellite remote sensing (RS) studies and, to certain extent, replace or complement laborious field work. For natural vegetation, ultrahigh spatial resolution is particularly beneficial for tasks such as biodiversity monitoring, habitat mapping, or measures against ecosystem degradation via invasive species or disturbances. Additionally, the acquisition frequency UASs provide can also be much higher, and this fact can assist in studies of ecosystem functions and services. On top of that, UAS optical data can provide spectral and structural information on ecosystems, substituting expensive active sensors. Last but not least, the availability of UASs at low costs opens new applications in vegetation research and practical management. UASs can thus serve well to derive remote sensingenabled essential biodiversity variables (EBVs), specifically those on species and community composition, ecosystem structure, species traits, and ecosystem functions. UAS can also help to upscale the point or plot field measurements to the landscape scale and overcome limitations imposed by traditional in situ measurements and destructive sampling, one of the challengesin RS applications. The variety of sensors, platforms, and procedures used to collect and process UAS data is vast. To adequately address the research questions with sufficient accuracy, it is necessary to optimize survey workflows and processing methods. In this chapter, we summarize the methods applied to ecosystem assessment and discuss selected studies divided into state, structure, status, and dynamic components. To better illustrate the different workflows, we provide several pilot study cases that offer a wide spectra of challenges in vegetation monitoring. At the end, we introduce challenges and future perspectives related to UAS applications in mapping and monitoring natural vegetation.

Název v anglickém jazyce

Vegetation mapping and monitoring by unmanned aerial systems (UAS) - current state and perspectives

Popis výsledku anglicky

Over the last years, unmanned aerial systems (UASs) have been receiving much attention, becoming essential tools for characterizing vegetation patterns and processes. Thanks to its ultrahigh spatial resolution and flexibility, UASs bear potential to bridge the gap between field surveys and satellite remote sensing (RS) studies and, to certain extent, replace or complement laborious field work. For natural vegetation, ultrahigh spatial resolution is particularly beneficial for tasks such as biodiversity monitoring, habitat mapping, or measures against ecosystem degradation via invasive species or disturbances. Additionally, the acquisition frequency UASs provide can also be much higher, and this fact can assist in studies of ecosystem functions and services. On top of that, UAS optical data can provide spectral and structural information on ecosystems, substituting expensive active sensors. Last but not least, the availability of UASs at low costs opens new applications in vegetation research and practical management. UASs can thus serve well to derive remote sensingenabled essential biodiversity variables (EBVs), specifically those on species and community composition, ecosystem structure, species traits, and ecosystem functions. UAS can also help to upscale the point or plot field measurements to the landscape scale and overcome limitations imposed by traditional in situ measurements and destructive sampling, one of the challengesin RS applications. The variety of sensors, platforms, and procedures used to collect and process UAS data is vast. To adequately address the research questions with sufficient accuracy, it is necessary to optimize survey workflows and processing methods. In this chapter, we summarize the methods applied to ecosystem assessment and discuss selected studies divided into state, structure, status, and dynamic components. To better illustrate the different workflows, we provide several pilot study cases that offer a wide spectra of challenges in vegetation monitoring. At the end, we introduce challenges and future perspectives related to UAS applications in mapping and monitoring natural vegetation.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10611 - Plant sciences, botany

Projekt

<a href="/cs/project/LTC18007" target="_blank" >LTC18007: Využití bezpilotních systémů (UAS) v monitoringu rostlinných invazí na různé prostorové i časové škále</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments

ISBN

978-0-323-85283-8

Počet stran výsledku

32

Strana od-do

93-124

Počet stran knihy

346

Název nakladatele

Elsevier

Místo vydání

Amsterodam

Kód UT WoS kapitoly

—