open access publication

Article, 2024

Global carbon balance of the forest: satellite-based L-VOD results over the last decade

Frontiers in Remote Sensing, ISSN 2673-6187, Volume 5, Page 1338618, 10.3389/frsen.2024.1338618

Contributors

Wigneron, Jean-Pierre 0000-0001-5345-3618 (Corresponding author) [1] Ciais, Philippe [2] Li, Xiaojun [1] Brandt, Martin Stefan 0000-0001-9531-1239 [3] Canadell, Josep G 0000-0002-8788-3218 [4] Tian, Feng 0000-0002-9686-2769 [5] Wang, Huan 0000-0002-0818-3070 [6] Bastos, Ana Filipa Ferreira 0000-0002-7368-7806 [7] Fan, Lei 0000-0002-1834-5088 [8] Gatica, Gabriel [9] Kashyap, Rahul [10] Liu, Xiangzhuo 0000-0002-1690-7083 [1] Sitch, Stephen A 0000-0003-1821-8561 [11] Tao, Shengli 0000-0002-2145-4736 [6] Xiao, Xiang-Ming 0000-0003-0956-7428 [12] Yang, Hui [13] Villar, Jhan Carlo Espinoza [14] Frappart, Frédéric 0000-0002-4661-8274 [1] Li, Wei 0000-0003-2543-2558 [15] Qin, Yuanwei 0000-0002-5181-9986 [12] De Truchis, Aurélien 0000-0003-3515-4176 [16] Fensholt, Rasmus 0000-0003-3067-4527 [3]

Affiliations

  1. [1] ISPA, UMR 1391, INRAE Nouvelle-Aquitaine, INRAE Nouvelle-Aquitaine Bordeaux, INRAE Nouvelle Aquitaine Poitiers, Bordeaux Villenave d’Ornon, Paris, France
  2. [NORA names: France; Europe, EU; OECD];
  3. [2] Laboratoire des Sciences du Climat et de l'Environnement
  4. [NORA names: France; Europe, EU; OECD];
  5. [3] University of Copenhagen
  6. [NORA names: KU University of Copenhagen; University; Denmark; Europe, EU; Nordic; OECD];
  7. [4] Commonwealth Scientific and Industrial Research Organisation
  8. [NORA names: Australia; Oceania; OECD];
  9. [5] Wuhan University
  10. [NORA names: China; Asia, East];

Abstract

Monitoring forest carbon (C) stocks is essential to better assess their role in the global carbon balance, and to better model and predict long-term trends and inter-annual variability in atmospheric CO2 concentrations. On a national scale, national forest inventories (NFIs) can provide estimates of forest carbon stocks, but these estimates are only available in certain countries, are limited by time lags due to periodic revisits, and cannot provide spatially continuous mapping of forests. In this context, remote sensing offers many advantages for monitoring above-ground biomass (AGB) on a global scale with good spatial (50–100 m) and temporal (annual) resolutions. Remote sensing has been used for several decades to monitor vegetation. However, traditional methods of monitoring AGB using optical or microwave sensors are affected by saturation effects for moderately or densely vegetated canopies, limiting their performance. Low-frequency passive microwave remote sensing is less affected by these saturation effects: saturation only occurs at AGB levels of around 400 t/ha at L-band (frequency of around 1.4 GHz). Despite its coarse spatial resolution of the order of 25 km × 25 km, this method based on the L-VOD (vegetation optical depth at L-band) index has recently established itself as an essential approach for monitoring annual variations in forest AGB on a continental scale. Thus, L-VOD has been applied to forest monitoring in many continents and biomes: in the tropics (especially in the Amazon and Congo basins), in boreal regions (Siberia, Canada), in Europe, China, Australia, etc. However, no reference study has yet been published to analyze L-VOD in detail in terms of capabilities, validation and results. This paper fills this gap by presenting the physical principles of L-VOD calculation, analyzing the performance of L-VOD for monitoring AGB and reviewing the main applications of L-VOD for tracking the carbon balance of global vegetation over the last decade (2010–2019).

Keywords

Australia, CO2 concentration, China, Europe, L-VOD, L-band, National Forest Inventory, above-ground biomass, annual variation, applications, atmospheric CO2 concentration, balance, biomass, biomes, boreal regions, calculations, canopy, capability, carbon, carbon balance, carbon stocks, coarse spatial resolution, concentration, context, continent, continental scale, countries, decades, effect, estimation, estimation of forest carbon stocks, forest, forest above-ground biomass, forest carbon, forest carbon stocks, forest inventory, forest monitoring, global carbon balance, global scale, global vegetation, index, inter-annual variability, inventory, lag, levels, long-term trends, method, microwave, microwave remote sensing, microwave sensors, model, monitoring, monitoring vegetation, national scale, passive microwave remote sensing, performance, periodic revisits, physical principles, region, remote sensing, remotely, resolution, results, revisits, saturation, saturation effects, scale, sensing, sensor, spatial resolution, spatially, stock, time, time lag, traditional methods, trends, tropics, validity, variables, variation, vegetation, vegetation canopy

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