Evidence map›Paper›PMID 40624011›Full record

ArticleScientific data2025

IB-AGC: Annual 25 km global live biomass carbon product from SMOS L-band passive microwave vegetation optical depth.

Xiaojun Li, Philippe Ciais, Frédéric Frappart, Klaus Scipal, Lei Fan, Hui Yang, Clément Albergel, Xiangzhuo Liu, Yuqing Liu, Mengjia Wang and 4 more

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. How accurately does L band vegetation optical depth predict aboveground biomass?International journal of applied earth observation and geoinformation : ITC journal · 2025
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Xiaojun LiINRAE, Bordeaux Sciences Agro, UMR 1391 ISPA, Villenave-d'Ornon, France.ORCID 0000-0002-3831-4852
Philippe CiaisLaboratoire des Sciences du Climat et de l'Environnement, UMR 1572 CEA-CNRS-5 UVSQ, Gif-sur-Yvette, France.ORCID 0000-0001-8560-4943
Frédéric FrappartINRAE, Bordeaux Sciences Agro, UMR 1391 ISPA, Villenave-d'Ornon, France.ORCID 0000-0002-4661-8274
Klaus ScipalEuropean Space Agency (ESA), Frascati, Italy.
Lei FanChongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing, China.ORCID 0000-0002-1834-5088
Hui YangInstitute of Ecology, College of Urban and Environmental Sciences, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, 100871, China.
Clément AlbergelEuropean Space Agency Climate Office, ECSAT, Didcot, UK.
Xiangzhuo LiuINRAE, Bordeaux Sciences Agro, UMR 1391 ISPA, Villenave-d'Ornon, France.
Yuqing LiuINRAE, Bordeaux Sciences Agro, UMR 1391 ISPA, Villenave-d'Ornon, France.
Mengjia WangSchool of Geoscience and Technology, Zhengzhou University, Zhengzhou, 450001, China.
Huan WangInstitute of Ecology, College of Urban and Environmental Sciences, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing, 100871, China.
Zanpin XingCenter for the Pan-Third Pole Environment, Lanzhou University, Lanzhou, 730000, China.
Aurelien De TruchisKayrros SAS, Paris, 75009, France.
Jean-Pierre WigneronINRAE, Bordeaux Sciences Agro, UMR 1391 ISPA, Villenave-d'Ornon, France. Jean-Pierre.Wigneron@inrae.fr.ORCID 0000-0001-5345-3618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring aboveground biomass carbon (AGC) stocks and their changes is crucial for understanding the global carbon cycle and the impact of climate change. Among remotely sensed methods, the use of the L-band (1.4 GHz) vegetation optical depth (L-VOD) derived from passive microwave satellite observations, offers rapid updates for timely monitoring of interannual AGC changes. L-VOD is sensitive to changes in the total water content of vegetation, which is determined by both AGC (the biomass of vegetation) and vegetation moisture content. While several methods have been used to understand and correct for the influence of the latter parameter when inferring AGC from L-VOD, there is still a lack of quantified corrections for its impact. Moreover, varying benchmark biomass datasets and fitting functions are currently used for converting L-VOD to AGC, making it difficult to harmonize or compare AGC estimates at regional and global scales. To address these issues, we first corrected the L-VOD time series for changes in the vegetation moisture content and then implemented a systematic global-scale calibration, resulting in annual AGC data set (called INRAE-BORDEAUX AGC, hereafter IB AGC) from 2010 to 2020 at a 25 km resolution. The accuracy assessments showed that IB AGC had a reasonably good spatial agreement with LiDAR referenced AGC data (R

Indexed as

BiomassCarbonMicrowavesPlantsCarbon CycleClimate ChangeRemote Sensing TechnologyCarbon

Identifiers

PMID40624011
PMCPMC12234700

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.