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

Kód výsledku v 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>

Nalezeny alternativní kódy

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

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10508 - Physical geography

Projekt

<a href="/cs/project/SS02030018" target="_blank" >SS02030018: Centrum pro krajinu a biodiverzitu</a><br>

Návaznosti

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

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Earth and Space Science

ISSN

2333-5084

e-ISSN

2333-5084

Svazek periodika

11

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

26

Strana od-do

e2024EA003709

Kód UT WoS článku

001368252700001

EID výsledku v databázi Scopus

2-s2.0-85207567649