F. Achard, R. Beuchle, P. Mayaux, H. Stibig, C. Bodart et al., Determination of tropical deforestation rates and related carbon losses from, Glob. Change Biol, vol.20, pp.2540-2554, 1990.

G. P. Asner and J. Mascaro, Mapping tropical forest carbon: Calibrating plot estimates to a simple Li-DAR metric, Remote Sens. Environ, vol.140, pp.614-624, 2014.

G. P. Asner, G. V. Powell, J. Mascaro, D. E. Knapp, J. K. Clark et al., High-resolution forest carbon stocks and emissions in the Amazon, P. Natl. Acad. Sci. USA, vol.107, pp.16738-16742, 2010.

G. P. Asner, J. Mascaro, H. C. Muller-landau, G. Vieilledent, R. Vaudry et al., A universal airborne LiDAR approach for tropical forest carbon mapping, Oecologia, vol.168, pp.1147-1160, 2012.

G. L. Baskerville, Use of Logarithmic Regression in the Estimation of Plant Biomass, Can. J. For. Res, vol.2, pp.49-53, 1972.

D. K. Bolton, N. C. Coops, and M. A. Wulder, Characterizing residual structure and forest recovery following high-severity fire in the western boreal of Canada using Landsat time-series and airborne lidar data, Remote Sens. Environ, vol.163, pp.48-60, 2015.

W. Y. Brockelman, A. Nathalang, and G. A. Gale, The Mo Singto forest dynamics plot, Nat. Hist. Bull. Siam Soc, vol.57, pp.35-55, 2011.

W. Y. Brockelman, A. Nathalang, and J. F. Maxwell, Mo Singto Plot: Flora and Ecology, National Science and Technology Development Agency, and Department of National Parks, Wildlife and Plant Conservation, 2017.

S. Brown and A. E. Lugo, Tropical secondary forests, J. Trop. Ecol, vol.6, pp.1-32, 1990.

L. Cao, N. C. Coops, J. L. Innes, J. Dai, H. Ruan et al., Tree species classification in subtropical forests using small-footprint full-waveform LiDAR data, Int. J. Appl. Earth Obs. Geoinformation, vol.49, pp.39-51, 2016.

F. Y. Chai, Above-Ground biomass estimation of a secondary forest in Sarawak, J. Trop. For. Sci, vol.9, pp.359-368, 1997.

W. Chanthorn, Y. Ratanapongsai, W. Y. Brockelman, M. A. Allen, C. Favier et al., Structure and community composition in a tropical forest suggest a change of ecological processes during stand development, For. Ecol. Manag, vol.9, pp.100-107, 2016.

J. Chave, D. Coomes, S. Jansen, S. L. Lewis, N. G. Swenson et al., Towards a worldwide wood economics spectrum, Ecol. Lett, vol.12, pp.351-366, 2009.

J. Chave, M. Réjou-méchain, A. Búrquez, E. Chidumayo, M. S. Colgan et al., Improved allometric models to estimate the aboveground biomass of tropical trees, Glob. Change Biol, vol.20, pp.3177-3190, 2014.
URL : https://hal.archives-ouvertes.fr/hal-02063299

J. Chave, C. Piponiot, I. Maréchaux, H. De-foresta, D. Larpin et al., Slow rate of secondary forest carbon accumulation in the Guianas compared with the rest of the Neotropics, Ecol. Appl, vol.30, 2004.
URL : https://hal.archives-ouvertes.fr/hal-02309463

R. L. Chazdon, Second Growth: The Promise of Tropical Forest Regeneration in an Age of Deforestation, 2014.

R. L. Chazdon, S. G. Letcher, M. Van-breugel, M. Martínez-ramos, F. Bongers et al., Rates of change in tree communities of secondary Neotropical forests following major disturbances, Philos. Trans. R. Soc. B Biol. Sci, vol.362, pp.273-289, 2007.

R. L. Chazdon, E. N. Broadbent, D. M. Rozendaal, F. Bongers, A. M. Zambrano et al., Carbon sequestration potential of second, 2016.

W. B. Cohen, M. E. Harmon, D. O. Wallin, and M. Fiorella, Two Decades of Carbon Flux from Forests of the Pacific Northwest: Estimates from a new modeling strategy, BioScience, vol.46, pp.836-844, 1996.

D. A. Coomes, M. Dalponte, T. Jucker, G. P. Asner, L. F. Banin et al., Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data, Remote Sens. Environ, vol.194, pp.77-88, 2017.

P. F. Cumberlege and V. M. Cumberlege, A preliminary list of the orchids of Khao Yai National Park, Nat. Hist. Bull. Siam Soc, vol.20, pp.155-182, 1963.

R. O. Dubayah, S. L. Sheldon, D. B. Clark, M. A. Hofton, J. B. Blair et al., Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica, J. Geophys. Res.-Biogeo, vol.115, 2010.

J. J. Ewel, P. Chai, L. M. Tsai, T. R. Feldpausch, C. Prates-clark et al., FAO: Global forest resources assessment 2010: terms and definitions. FAO working paper 144/E, Food and Agriculture Organization (FAO) of the United Nations, The State of Food and Agriculture, Investing in agriculture for a better future, FAO publications, vol.46, pp.967-979, 1983.

T. R. Feldpausch, L. Banin, O. L. Phillips, T. R. Baker, S. L. Lewis et al., Biogeosciences, vol.8, pp.1081-1106, 2011.

T. R. Feldpausch, J. Lloyd, S. L. Lewis, R. J. Brienen, M. Gloor et al., Biogeosciences, vol.9, pp.3381-3403, 2012.

A. Ferraz, S. Saatchi, L. Xu, S. Hagen, J. Chave et al., Carbon storage potential in degraded forests of Kalimantan, vol.13, p.95001, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02403113

H. K. Gibbs, S. Brown, J. O. Niles, and J. A. Foley, Monitoring and estimating tropical forest carbon stocks: making REDD a reality, Environ. Res. Lett, vol.2, p.45023, 2007.

S. J. Goetz, A. Baccini, N. T. Laporte, T. Johns, W. Walker et al., Mapping and monitoring carbon stocks with satellite observations: a comparison of methods, Carbon Balance Manag, vol.4, 2009.

M. C. Hansen, P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova et al., High-Resolution Global Maps of 21st-Century Forest Cover Change, Science, vol.342, pp.850-853, 2013.

N. L. Harris, S. Brown, S. C. Hagen, S. S. Saatchi, S. Petrova et al., Baseline Map of Carbon Emissions from Deforestation in Tropical Regions, Science, vol.336, pp.1573-1576, 2012.

E. H. Helmer, M. A. Lefsky, and D. A. Roberts, Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System, J. Appl. Remote Sens, vol.3, pp.1-31, 2009.

M. Hiratsuka, T. Toma, R. Diana, D. Hadriyanto, and Y. Morikawa, IPCC: Guidelines for national greenhouse gas inventories, Agriculture, Forestry and other land use (AFLOLU), Institute for Global Environmental strategies, Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC-49th Session, vol.40, pp.277-282, 2006.

K. E. Jenks, P. Chanteap, D. Kanda, C. Peter, P. Cutter et al., Using Relative Abundance Indices from Camera-Trapping to Test Wildlife Conservation Hypotheses -An Example from Khao Yai National Park, Tropical Conservation Science, vol.4, pp.113-131, 2011.

M. R. Jepsen, Above-ground carbon stocks in tropical fallows, For. Ecol. Manag, vol.225, pp.287-295, 2006.

N. Jha, Forest aboveground biomass stock and resilience
URL : https://hal.archives-ouvertes.fr/hal-02404726

T. Jucker, G. P. Asner, M. Dalponte, P. G. Brodrick, C. D. Philipson et al., Estimating aboveground carbon density and its uncertainty in Borneo's structurally complex tropical forests using airborne laser scanning, Biogeosciences, vol.15, pp.3811-3830, 2018.

V. Junttila, T. Kauranne, A. O. Finley, and J. B. Bradford, Linear Models for Airborne-Laser-Scanning-Based Operational Forest Inventory With Small Field Sample Size and Highly Correlated LiDAR Data, IEEE Trans. Geosci. Remote Sens, vol.53, pp.5600-5612, 2015.

D. K. Kennard, K. Gould, F. E. Putz, T. S. Fredericksen, and F. Morales, Effect of disturbance intensity on regeneration mechanisms in a tropical dry forest, For. Ecol. Manag, vol.162, pp.197-208, 2002.

S. Kitamura, T. Yumoto, P. Poonswad, P. Chuailua, and K. Plongmai, Characteristics of hornbill-dispersed fruits in a tropical seasonal forest in Thailand, Bird Conserv. Int, vol.14, pp.81-88, 2004.

K. Kronseder, U. Ballhorn, V. Böhm, and F. Siegert, Above ground biomass estimation across forest types at different degradation levels in Central Kalimantan using LiDAR data, Int. J. Appl. Earth Obs. Geoinformation, vol.18, pp.37-48, 2012.

N. Labriere, S. Tao, J. Chave, K. Scipal, T. L. Toan et al., In Situ Reference Datasets From the TropiSAR and AfriSAR Campaigns in Support of Upcoming Spaceborne Biomass Missions, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens, vol.11, pp.3617-3627, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01932955

S. G. Letcher and R. L. Chazdon, Rapid Recovery of Biomass, Species Richness, and Species Composition in a Forest Chronosequence in Northeastern Costa Rica, Biotropica, vol.41, pp.608-617, 2009.

A. Liaw and M. Wiener, Classification and Regression by Ran-domForest, R news, vol.2, pp.18-22, 2002.

M. Lohbeck, L. Poorter, M. Martínez-ramos, and F. Bongers, Biomass is the main driver of changes in ecosystem process rates during tropical forest succession, Ecology, vol.96, pp.1242-1252, 2015.

E. C. Losos and E. G. Leigh, Tropical forest diversity and dynamism: findings from a large-scale plot network, 2004.

D. Lu, The potential and challenge of remote sensing-based biomass estimation, Int. J. Remote Sens, vol.27, pp.1297-1328, 2006.

A. E. Lugo and S. Brown, Tropical forests as sinks of atmospheric carbon, For. Ecol. Manag, vol.54, pp.239-255, 1992.

M. Maltamo, P. Packalén, X. Yu, K. Eerikäinen, J. Hyyppä et al., Identifying and quantifying structural characteristics of heterogeneous boreal forests using laser scanner data, For. Ecol. Manag, vol.216, pp.41-50, 2005.

J. G. Masek and G. J. Collatz, Estimating forest carbon fluxes in a disturbed southeastern landscape: Integration of remote sensing, forest inventory, and biogeochemical modeling, J. Geophys. Res, vol.111, p.1006, 2006.

S. M. Mcmahon, G. Arellano, and S. J. Davies, The importance and challenges of detecting changes in forest mortality rates, Ecosphere, 10, e02615, 2019.

V. Meyer, S. S. Saatchi, J. Chave, J. W. Dalling, S. Bohlman et al., Detecting tropical forest biomass dynamics from repeated airborne lidar measurements, Biogeosciences, vol.10, pp.5421-5438, 2013.

V. Meyer, S. Saatchi, A. Ferraz, L. Xu, A. Duque et al., Forest degradation and biomass loss along the Chocó region of Colombia, Carbon Balance Manag, vol.14, 2019.

E. T. Mitchard, S. S. Saatchi, A. Baccini, G. P. Asner, S. J. Goetz et al., Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps, Carbon Balance Manag, vol.8, 2013.

E. T. Mitchard, T. R. Feldpausch, R. J. Brienen, G. Lopez-gonzalez, A. Monteagudo et al., Glob. Ecol. Biogeogr, vol.23, pp.935-946, 2014.

E. Naesset, Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data, Remote Sens. Environ, vol.80, pp.88-99, 2002.

A. E. N'guessan, J. K. N'dja, O. N. Yao, B. H. Amani, R. G. Gouli et al., Drivers of biomass recovery in a secondary forested landscape of West Africa, For. Ecol. Manag, vol.433, pp.325-331, 2019.

N. Norden, R. C. Mesquita, T. V. Bentos, R. L. Chazdon, and G. B. Williamson, Contrasting community compensatory trends in alternative successional pathways in central

O. Amazonia, , vol.120, pp.143-151, 2011.

N. Norden, H. A. Angarita, F. Bongers, M. Martínez-ramos, I. Granzow-de-la-cerda et al., Successional dynamics in Neotropical forests are as uncertain as they are predictable, P. Natl. Acad. Sci. USA, vol.112, pp.8013-8018, 2015.

C. D. Oliver and B. C. Larson, Forest stand dynamics, 1996.

D. Pflugmacher, W. B. Cohen, and E. R. Kennedy, Using Landsat-derived disturbance history (1972-2010) to predict current forest structure, Remote Sens. Environ, vol.122, pp.146-165, 2012.

D. Pflugmacher, W. B. Cohen, R. E. Kennedy, Y. , and Z. , Using Landsat-derived disturbance and recovery history and lidar to map forest biomass dynamics, Remote Sens. Environ, vol.151, pp.124-137, 2014.

P. D. Pickell, T. Hermosilla, R. J. Frazier, N. C. Coops, and M. A. Wulder, Forest recovery trends derived from Landsat time series for North American boreal forests, Int. J. Remote Sens, vol.37, pp.138-149, 2016.

L. Poorter, F. Bongers, T. M. Aide, A. M. Zambrano, P. Balvanera et al., Biomass resilience of Neotropical secondary forests, vol.530, pp.211-214, 2016.

L. Poorter, F. Bongers, T. M. Aide, A. M. Zambrano, P. Balvanera et al., Data from: Biomass resilience of Neotropical secondary forests, Dryad, Dataset, vol.2, pp.156-163, 2006.

M. Réjou-méchain, H. C. Muller-landau, M. Detto, S. C. Thomas, T. Le-toan et al., Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks, Biogeosciences, vol.11, pp.93-101, 2014.

M. Réjou-méchain, A. Tanguy, C. Piponiot, J. Chave, and B. Hérault, Biomass: an R package for estimating above-ground biomass and its uncertainty in tropical forests, Methods Ecol. Evol, vol.8, pp.1163-1167, 2017.

M. Réjou-méchain, N. Barbier, P. Couteron, P. Ploton, G. Vincent et al., Upscaling Forest Biomass from Field to Satellite Measurements: Sources of Errors and Ways to Reduce Them, Surv. Geophys, vol.40, pp.881-911, 2019.

R. Suarez, D. Rozendaal, D. M. De-sy, V. Phillips, O. L. Alvarez-dávila et al., Estimating aboveground net biomass change for tropical and subtropical forests: Refinement of IPCC default rates using forest plot data, Glob. Change Biol, vol.25, pp.3609-3624, 2019.

J. Roussel and D. Auty, lidR: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications, 2017.

N. Jha, Demographic drivers of tree biomass change during secondary succession in northeastern Costa Rica, Forest aboveground biomass stock and resilience, vol.25, pp.506-516, 2015.

D. M. Rozendaal, R. L. Chazdon, F. Arreola-villa, P. Balvanera, T. V. Bentos et al., Demographic Drivers of Aboveground Biomass Dynamics During Secondary Succession in Neotropical Dry and Wet Forests, Ecosystems, vol.20, pp.340-353, 2017.

J. Ruiz, M. C. Fandino, and R. L. Chazdon, Vegetation Structure, Composition, and Species Richness Across a 56-year Chronosequence of Dry Tropical Forest on Providencia Island, Colom-bia1, Biotropica, vol.37, pp.520-530, 2005.

J. G. Saldarriaga, D. C. West, M. L. Tharp, and C. Uhl, Long-Term Chronosequence of Forest Succession in the Upper Rio Negro of Colombia and Venezuela, J. Ecol, vol.76, pp.938-958, 1988.

N. Sasaki and F. E. Putz, Critical need for new definitions of "forest" and "forest degradation" in global climate change agreements, Conserv. Lett, vol.2, pp.226-232, 2009.

W. L. Silver, R. Ostertag, and A. E. Lugo, The Potential for Carbon Sequestration Through Reforestation of Abandoned Tropical Agricultural and Pasture Lands, Restor. Ecol, vol.8, pp.394-407, 2000.

T. Smitinand, Vegetation of Khao Yai National Park, 1968.

S. M. Stas, E. Rutishauser, J. Chave, N. P. Anten, and Y. Laumonier, Estimating the aboveground biomass in an old secondary forest on limestone in the Moluccas, Indonesia: Comparing locally developed versus existing allometric models, For. Ecol. Manag, vol.389, pp.27-34, 2017.

H. Stibig, F. Achard, S. Carboni, R. Ra?i, and J. Miettinen, Change in tropical forest cover of Southeast Asia from, Biogeosciences, vol.11, pp.247-258, 1990.

M. J. Sullivan, J. Talbot, S. L. Lewis, O. L. Phillips, L. Qie et al., , 2017.

S. C. Thomas and A. R. Martin, Carbon Content of Tree Tissues: A Synthesis, Forests, vol.3, pp.332-352, 2012.

M. Toledo and J. Salick, Secondary Succession and Indigenous Management in Semideciduous Forest Fallows of the Amazon Basin: Secondary Succession and Indigenous Management, Biotropica, vol.38, pp.161-170, 2006.

J. C. White, N. Saarinen, V. Kankare, M. A. Wulder, T. Hermosilla et al., Confirmation of postharvest spectral recovery from Landsat time series using measures of forest cover and height derived from airborne laser scanning data, Remote Sens. Environ, vol.216, pp.262-275, 2018.

M. A. Wulder, J. C. White, C. W. Bater, N. C. Coops, C. Hopkinson et al., Lidar plots -a new large-area data collection option: context, concepts, and case study, Can. J. Remote Sens, vol.38, pp.600-618, 2012.

H. S. Zald, J. L. Ohmann, H. M. Roberts, M. J. Gregory, E. B. Henderson et al., Influence of lidar, Landsat imagery, disturbance history, plot location accuracy, and plot size on accuracy of imputation maps of forest composition and structure, Remote Sens. Environ, vol.143, pp.26-38, 2014.

A. E. Zanne, G. Lopez-gonzalez, D. A. Coomes, J. Ilic, S. Jansen et al., Data from: Towards a worldwide wood economics spectrum, Dryad, Dataset, 2009.

K. Zhao, S. Popescu, N. , and R. , Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers, Remote Sens. Environ, vol.113, pp.182-196, 2009.

D. Zheng, J. Rademacher, J. Chen, T. Crow, M. Bresee et al., Estimating aboveground biomass using Landsat 7 ETM+ data across a managed landscape in northern Wisconsin, USA, Remote Sens. Environ, vol.93, pp.402-411, 2004.

S. G. Zolkos, S. J. Goetz, and R. Dubayah, A metaanalysis of terrestrial aboveground biomass estimation using lidar remote sensing, Remote Sens. Environ, vol.128, pp.289-298, 2013.