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Across Beni lowland forest, ESA BIOMASS forest height is lower than GEDI lidar canopy height on average (mean difference -3.0 m, 95 percent block-bootstrap interval -4.4 to -1.1 m) and in 78 percent of forest cells, so the claim holds for most of the forest. It does not hold for low canopies: where GEDI canopy height is lowest (median 10.4 m), BIOMASS is on average 2.1 m higher. BIOMASS compresses the height range: the fitted relation crosses the 1:1 line near 24 m of BIOMASS height. The two heights rank forests only moderately consistently. BIOMASS forest height in its first year is therefore usable for the EBV Ecosystem Vertical Profile only with a stated uncertainty of several metres." } } } rows { name { value: "hasConfidenceLevel" } } rows { name { value: "Moderate" } } rows { quad { p_iri { } o_iri { } } } rows { name { value: "hasEvidenceDescription" } } rows { quad { p_iri { } o_literal { lex: "Comparison on 1900 forest cells (HEALPix depth 11, WorldCover tree cover at least 50 percent, at least 5 GEDI footprints, at most 5 percent burned in 2024). BIOMASS minus GEDI RH98: mean -3.03 m (95 percent spatial block-bootstrap interval -4.39 to -1.06 m), median -3.83 m, root-mean-square difference 7.18 m; BIOMASS lower in 77.7 percent of cells. Spearman rank correlation 0.58, Pearson 0.52. By thirds of GEDI height (medians 10.4, 19.5, 25.6 m): mean difference +2.1, -4.6, -6.6 m; BIOMASS lower in 48, 87, 97 percent of cells. Linear relation GEDI = 8.61 + 0.645 x BIOMASS, in-sample R2 0.27, cross-validated error 6.59 m (5-fold, 42 spatial blocks). Checks: night-time footprints only, mean difference -2.91 m and Spearman 0.58 (1832 cells); passes combined without the bias weight, mean difference -3.35 m and Spearman 0.59; disagreement against the BIOMASS bias index, Spearman 0.15. Results: results/summary.json.\nGithub repository: https://github.com/annefou/beni-canopy-height-ebv" } } } rows { name { value: "hasLimitationsDescription" } } rows { quad { p_iri { } o_literal { lex: "One region and one BIOMASS season (April to August 2026, Level-2A, processors 4.4.4 and 4.4.5 mixed during reprocessing); the products are early and may change. GEDI footprints span 2019 to 2025, so the two heights are years apart; cells burned in 2024 are excluded but later disturbance is not. GEDI RH98 is a lidar energy percentile over 25 m footprints and BIOMASS forest height is an upper-canopy stand height (H100) from radar at 200 m, so part of the difference is definitional; GEDI is itself a satellite product, and no open field-plot heights exist in the region for an independent check. BIOMASS also reports non-zero heights over grassland, and one of 18 products was excluded for reporting about 30 m over grassland. The breakdown by thirds of GEDI height is affected by regression to the mean. The forest focus group uses a 50 percent tree-cover threshold that is our choice." } } } rows { name { value: "hasOutcomeRepository" } } rows { prefix { value: "https://doi.org/10.5281/" } } rows { name { value: "zenodo.23120435" } } rows { quad { p_iri { } o_iri { prefix_id: 12 } } } rows { name { value: "hasValidationStatus" } } rows { name { value: "PartiallySupported" } } rows { quad { p_iri { prefix_id: 10 } o_iri { } } } rows { name { value: "isOutcomeOf" } } rows { name { value: "RAcqXoAGeUnb9p0yakR1lohrkZA4wn2ksre3sXvXvQ548" } } rows { quad { p_iri { } o_iri { prefix_id: 1 } } } rows { name { value: "wasAttributedTo" } } rows { prefix { value: "https://orcid.org/" } } rows { name { value: "0000-0002-1784-2920" } } rows { quad { s_iri { prefix_id: 2 name_id: 4 } p_iri { prefix_id: 5 name_id: 27 } o_iri { prefix_id: 13 } g_iri { prefix_id: 2 name_id: 7 } } } rows { prefix { value: "http://xmlns.com/foaf/0.1/" } } rows { name { value: "name" } } rows { quad { s_iri { prefix_id: 13 name_id: 28 } p_iri { prefix_id: 14 } o_literal { lex: "Anne Fouilloux" } g_iri { prefix_id: 2 name_id: 9 } } } rows { name { value: "created" } } rows { datatype { value: "http://www.w3.org/2001/XMLSchema#dateTime" } } rows { quad { s_iri { prefix_id: 1 name_id: 1 } p_iri { prefix_id: 7 name_id: 30 } o_literal { lex: "2026-10-03T12:07:44.249Z" datatype: 2 } } } rows { name { value: "creator" } } rows { quad { p_iri { } o_iri { prefix_id: 13 name_id: 28 } } } rows { name { value: "license" } } rows { prefix { value: "https://creativecommons.org/licenses/by/4.0/" } } rows { quad { p_iri { prefix_id: 7 name_id: 32 } o_iri { prefix_id: 15 name_id: 2 } } } rows { name { value: "introduces" } } rows { quad { p_iri { prefix_id: 6 name_id: 33 } o_iri { prefix_id: 2 name_id: 12 } } } rows { name { value: "wasCreatedAt" } } rows { prefix { value: "https://" } } rows { name { value: "platform.sciencelive4all.org" } } rows { quad { p_iri { prefix_id: 6 name_id: 34 } o_iri { prefix_id: 16 } } } rows { quad { p_iri { prefix_id: 11 name_id: 15 } o_literal { lex: "ESA BIOMASS forest height is lower than GEDI lidar canopy height in most Beni lowland forest, but not in low canopies" } } } rows { prefix { id: 8 value: "https://w3id.org/np/o/ntemplate/" } } rows { name { value: "wasCreatedFromTemplate" } } rows { prefix { id: 3 value: "https://w3id.org/np/" } } rows { name { value: "RA2zljn0Nw9SadppOyxZoh-_Rxosslrq-vYG-p9SttnJE" } } rows { quad { p_iri { prefix_id: 8 name_id: 36 } o_iri { prefix_id: 3 } } } rows { name { value: "sig" } } rows { name { value: "hasAlgorithm" } } rows { quad { s_iri { prefix_id: 2 } p_iri { prefix_id: 6 } o_literal { lex: "RSA" } } } rows { name { value: "hasPublicKey" } } rows { quad { p_iri { } o_literal { lex: "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" } } } rows { name { value: "hasSignature" } } rows { quad { p_iri { } o_literal { lex: "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" } } } rows { name { value: "hasSignatureTarget" } } rows { quad { p_iri { } o_iri { prefix_id: 1 name_id: 1 } } } rows { name { value: "signedBy" } } rows { quad { p_iri { prefix_id: 6 name_id: 43 } o_iri { prefix_id: 13 name_id: 28 } } }