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How to Find Accurate Terrain and Canopy Height GEDI Footprints in Temperate Forests and Grasslands?

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F24%3A10486646" target="_blank" >RIV/00216208:11310/24:10486646 - isvavai.cz</a>

  • Alternative codes found

    RIV/67985939:_____/24:00601030 RIV/60460709:41330/24:100310

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ymi8DQx_r-" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ymi8DQx_r-</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1029/2024EA003709" target="_blank" >10.1029/2024EA003709</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    How to Find Accurate Terrain and Canopy Height GEDI Footprints in Temperate Forests and Grasslands?

  • Original language description

    Filtering approaches on Global Ecosystem Dynamics Investigation (GEDI) data differconsiderably across existing studies and it is yet unclear which method is the most effective. We conducted anin-depth analysis of GEDI&apos;s vertical accuracy in mapping terrain and canopy heights across three study sites intemperate forests and grasslands in Spain, California, and New Zealand. We started with unfiltered data (2,081,108 footprints) and describe a workflow for data filtering using Level 2A parameters and for geolocationerror mitigation. We found that retaining observations with at least one detected mode eliminates noise moreeffectively than sensitivity. The accuracy of terrain and canopy height observations depended considerably onthe number of modes, beam sensitivity, landcover, and terrain slope. In dense forests, a minimum sensitivity of 0.9 was required, while in areas with sparse vegetation, sensitivity of 0.5 sufficed. Sensitivity greater than 0.9 resulted in an overestimation of canopy height in grasslands, especially on steep slopes, where high sensitivityled to the detection of multiple modes. We suggest excluding observations with more than five modes ingrasslands. We found that the most effective strategy for filtering low-quality observations was to combine thequality flag and difference from TanDEM-X, striking an optimal balance between eliminating poor-quality dataand preserving a maximum number of high-quality observations. Positional shifts improved the accuracy of GEDI terrain estimates but not of vegetation height estimates. Our findings guide users to an easy way ofprocessing of GEDI footprints, enabling the use of the most accurate data and leading to more reliable applications.

  • Czech name

  • Czech description

Classification

  • 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

Result continuities

  • Project

    <a href="/en/project/SS02030018" target="_blank" >SS02030018: Center for Landscape and Biodiversity</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Earth and Space Science

  • ISSN

    2333-5084

  • e-ISSN

    2333-5084

  • Volume of the periodical

    11

  • Issue of the periodical within the volume

    10

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    26

  • Pages from-to

    e2024EA003709

  • UT code for WoS article

    001368252700001

  • EID of the result in the Scopus database

    2-s2.0-85207567649