Vše

Co hledáte?

Vše
Projekty
Výsledky výzkumu
Subjekty

Rychlé hledání

  • Projekty podpořené TA ČR
  • Významné projekty
  • Projekty s nejvyšší státní podporou
  • Aktuálně běžící projekty

Chytré vyhledávání

  • Takto najdu konkrétní +slovo
  • Takto z výsledků -slovo zcela vynechám
  • “Takto můžu najít celou frázi”

Spaceborne Canopy Height Products Should Be Complemented With Airborne Laser Scanning Data: Toward A European Canopy Height Model

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F26%3A00014168" target="_blank" >RIV/46747885:24510/26:00014168 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025EA004544" target="_blank" >https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025EA004544</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1029/2025EA004544" target="_blank" >10.1029/2025EA004544</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Spaceborne Canopy Height Products Should Be Complemented With Airborne Laser Scanning Data: Toward A European Canopy Height Model

  • Popis výsledku v původním jazyce

    Understanding the structure of vegetation is important for studying ecosystems and making informed environmental decisions. To meet the growing need for detailed vegetation data, scientists are combining satellite data with machine learning to estimate vegetation structure at very fine scales. However, these satellite-based models can have large errors when compared to more accurate measurements collected from airborne laser scanning (ALS). In this study, we show that in regions such as Europe, where extensive ALS data are available, it‘s better to use these local data than to rely on less accurate predictions from satellite products. Currently, around 30 European countries have completed or are close to completing nationwide airborne laser scanning, with several others partially covered. Newer acquisitions are being collected at increasingly higher point densities, providing more detailed information about 3D vegetation structure. We therefore emphasize the need to create consistent and accessible vegetation height maps using ALS data. This will require better coordination of data collection, standardized processing, and open data access. These detailed maps are not only useful for applications in forestry, ecology, and conservation, but they are also essential for improving future satellite missions that monitor Earth‘s vegetation.

  • Název v anglickém jazyce

    Spaceborne Canopy Height Products Should Be Complemented With Airborne Laser Scanning Data: Toward A European Canopy Height Model

  • Popis výsledku anglicky

    Understanding the structure of vegetation is important for studying ecosystems and making informed environmental decisions. To meet the growing need for detailed vegetation data, scientists are combining satellite data with machine learning to estimate vegetation structure at very fine scales. However, these satellite-based models can have large errors when compared to more accurate measurements collected from airborne laser scanning (ALS). In this study, we show that in regions such as Europe, where extensive ALS data are available, it‘s better to use these local data than to rely on less accurate predictions from satellite products. Currently, around 30 European countries have completed or are close to completing nationwide airborne laser scanning, with several others partially covered. Newer acquisitions are being collected at increasingly higher point densities, providing more detailed information about 3D vegetation structure. We therefore emphasize the need to create consistent and accessible vegetation height maps using ALS data. This will require better coordination of data collection, standardized processing, and open data access. These detailed maps are not only useful for applications in forestry, ecology, and conservation, but they are also essential for improving future satellite missions that monitor Earth‘s vegetation.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10500 - Earth and related environmental sciences

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2026

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název periodika

    Earth and Space Science>

  • ISSN

    2333-5084

  • e-ISSN

  • Svazek periodika

    13

  • Číslo periodika v rámci svazku

    1

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    20

  • Strana od-do

  • Kód UT WoS článku

    001656990700001

  • EID výsledku v databázi Scopus

    2-s2.0-105027004310