Pattern to process, research to practice: remote sensing of plant invasions
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985939%3A_____%2F23%3A00577356" target="_blank" >RIV/67985939:_____/23:00577356 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/44555601:13520/23:43897773
Výsledek na webu
<a href="https://doi.org/10.1007/s10530-023-03150-z" target="_blank" >https://doi.org/10.1007/s10530-023-03150-z</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10530-023-03150-z" target="_blank" >10.1007/s10530-023-03150-z</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Pattern to process, research to practice: remote sensing of plant invasions
Popis výsledku v původním jazyce
Processes that drive plant invasions play out across multiple spatial and temporal scales. Understanding individual steps along the introduction-naturalization-invasion continuum and its drivers is crucial for management. This review, targeting the broad audience of invasion scientists, feld ecologists and land managers, summarizes the state-of-the-art and potential of remote sensing (RS) in plant invasion science and management. It identifes challenges and research gaps, discusses the discrepancies between technology, science and practice, and suggests ways of addressing some of these issues. Mapping, modelling and predicting invasion processes across scales is a major challenge since they are dynamic and highly complex. Integration of RS data collected at diferent spatial and temporal scales (“rocking” across scales) has the potential to elucidate the dynamics of invasions and to reveal its drivers, thereby improving the efciency of control measures. Increasing spatial/temporal resolution of imagery from satellites and drones has much potential to (i) precisely identify even less conspicuous invasive species, (ii) map invasion dynamics, and (iii) provide information on.
Název v anglickém jazyce
Pattern to process, research to practice: remote sensing of plant invasions
Popis výsledku anglicky
Processes that drive plant invasions play out across multiple spatial and temporal scales. Understanding individual steps along the introduction-naturalization-invasion continuum and its drivers is crucial for management. This review, targeting the broad audience of invasion scientists, feld ecologists and land managers, summarizes the state-of-the-art and potential of remote sensing (RS) in plant invasion science and management. It identifes challenges and research gaps, discusses the discrepancies between technology, science and practice, and suggests ways of addressing some of these issues. Mapping, modelling and predicting invasion processes across scales is a major challenge since they are dynamic and highly complex. Integration of RS data collected at diferent spatial and temporal scales (“rocking” across scales) has the potential to elucidate the dynamics of invasions and to reveal its drivers, thereby improving the efciency of control measures. Increasing spatial/temporal resolution of imagery from satellites and drones has much potential to (i) precisely identify even less conspicuous invasive species, (ii) map invasion dynamics, and (iii) provide information on.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10618 - Ecology
Návaznosti výsledku
Projekt
<a href="/cs/project/EF18_053%2F0017850" target="_blank" >EF18_053/0017850: Mobility 2020</a><br>
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Biological Invasions
ISSN
1387-3547
e-ISSN
1573-1464
Svazek periodika
25
Číslo periodika v rámci svazku
12
Stát vydavatele periodika
DE - Spolková republika Německo
Počet stran výsledku
26
Strana od-do
3651-3676
Kód UT WoS článku
001059975300001
EID výsledku v databázi Scopus
2-s2.0-85169074661