Publications

Santoro M., Cartus, O., Quegan, S., Kay H., Lucas, R. M., Araza, A., Herold, M., Labrière, N., Chave, J., Rosenqvist, Å., Tadono, T., Kobayashi, K., Kellndorfer, J., Avitabile, V., Brown, H., Carreiras, J., Campbell, M. J., Cavlovic, J., Conceição Bispo, P., Gilani, H., Khan, M. L., Kumar, A., Lewis, S. L., Jingjing Liang, J., Mitchard, E. T. A., Pacheco-Pascagaza, A. M., Phillips, O. L., Ryan, C. M., Saikia, P., Schepaschenko, D., Sukhdeo, H., Verbeeck, H., Vieilledent, G., Wijaya, A., Willcock, S. and Seifert, F.M.. Design and performance of the Climate Chnage Initiative Biomass gobal retrieval algorithm. Science of Remote Sensing. 2024. https://doi.org/10.1016/j.srs.2024.100169
Chen, N., Tsendbazar, N. E., Requena Suarez, D., Silva-Junior, C. H. L., Verbesselt, J., Herold, M.. Revealing the spatial variation in biomass uptake rates of Brazil’s secondary forests.. ISPRS Journal of Photogrammetry and Remote Sensing. 2024. https://doi.org/10.1016/j.isprsjprs.2023.12.013
Hunka, N., Santoro, M., Armston. J. et al.. On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake.. Environmental Research Letters. 203. https://doi.org/10.1088/1748-9326/ad0b60
Dalagnol, R., Wagner, F., H., Galvão, L., S. et al.. Mapping tropical forest degradation with deep learning and Planet NICFI data.. Remote Sensing of Environment.. 2023. https://doi.org/10.1016/j.rse.2023.113798
Mo, L., Zohner, C.M., Reich, P.B. et al.. Integrated global assessment of the natural forest carbon potential.. Nature. 2023. https://doi.org/10.1038/s41586-023-06723-z
Araza, A., de Bruin, S., Hein, L. and Herold, M.. Spatial predictions and uncertainties of forest carbon fluxes for carbon accounting.. Scientific Reports. 2023. https://doi.org/10.1038/s41598-023-38935-8
Yang, H., Ciais, P., Frappart, F., et al.. Global increase in biomass carbon stock dominated by growth of northern young forests over past decade.. Nature Geoscience. 2023. https://doi.org/10.1038/s41561-023-01274-4
Araza, A., Herold, M., de Bruin, S., et al.. Past decade above-ground biomass change comparisons from four multi-temporal global maps. International Journal of Applied Earth Observation and Geoinformation. 2023. https://doi.org/10.1016/j.jag.2023.103274
Chen, N., Tsendbazar, N.E., Requena Suarez, D., Verbesselt, J. and Herold, M.. Characterizing aboveground biomass and tree cover of regrowing forests in Brazil using multi-source remote sensing data. Remote Sensing in Ecology and Conservation. 2023. https://doi.org/10.1002/rse2.328
Ochiai, O., Poulter, B., Seifert, F.M. et al.. Towards a roadmap for space-based observations of the land sector for the UNFCCC Global Stocktake.. iScience. 2023. http://dx.doi.org/10.1016/j.isci.2023.106489
Labrière, N., Davies, S. J., Disney, M. I., Duncanson, L. I., Herold, M., Lewis, S. L., Phillips, O. L., Quegan, S., Saatchi, S. S., Schepaschenko, D. G., Scipal, K., Sist, P., & Chave, J.. Toward a forest biomass reference measurement system for remote sensing applications. Global Change Biology. 2023. https://doi.org/10.1111/gcb.16497
Bennett, A. C., Rodrigues de Sousa, T., Monteagudo-Mendoza, A., Esquivel-Muelbert, A., Morandi, P. S., Coelho de Souza, F., ... & Phillips, O. L.. Sensitivity of South American tropical forests to an extreme climate anomaly. Nature Climate Change. 2023.
Viana Santos, H. K., Borges De Lima, R., Figueiredo De Souza, R. L., Cardoso, D., Moonlight, P. W., Teixeira Silva, T., ... & Phillips, O. L.. Spatial distribution of aboveground biomass stock in tropical dry forest in Brazil. iForest-Biogeosciences and Forestry. 2023.
Málaga, N., De Bruin, S., McRoberts, R.E., Arana Olivos, A., de la Cruz Paiva, R., Durán Montesinos, P., Requena Suarez, D. and Herold, M.. Precision of subnational forest AGB estimates within the Peruvian Amazonia using a global biomass map.. International Journal of Applied Earth Observation and Geoinformation.. 2022. http://dx.doi.org/10.1016/j.jag.2022.103102
Fan, L., Wigneron, J.P., Ciais, P. et al.. Siberian carbon sink reduced by forest disturbances.. Nature Geoscience. 2022. http://dx.doi.org/10.1038/s41561-022-01087-x
Tao, S., Chave, J., Frison, P.L. and Saatchi, S.. Increasing and widespread vulnerability of intact tropical rainforests to repeated droughts.. PNAS. 2022. http://dx.doi.org/10.1073/pnas.2116626119
Liang, J., Gamarra, J.G.P., Picard, N. et al.. Co-limitation towards lower latitudes shapes global forest diversity gradients.. Nature Ecology and Evolution.. 2022. http://dx.doi.org/10.1038/s41559-022-01831-x
Santoro, M., Cartus, O., Wegmüller, U., Besnard, S., Carvalhais, N., Araza, A., Herold, M., Liang, J., Cavlovic, J., Engdahl, M.E.. Global estimation of above-ground biomass from spaceborne C-band scatterometer observations aided by LiDAR metrics of vegetation structure.. Remote Sensing of Environment. 2022. https://doi.org/10.1016/j.rse.2022.113114
Yang, H., Ciais, P., Wigneron, J.P., Chave, J., Cartus, O., Chen, X., Fan, L., Green, J.K., Huang, Y., Joetzjer, E. and Kay, H.. Climatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Niño.. PNAS. 2022. https://doi.org/10.1073/pnas.2101388119
Araza, A., de Bruin, S., Herold, M., Quegan, S., Labriere, N., Rodriguez-Veiga, P., Avitabile, V., Santoro, M., Mitchard, E.T.A., Ryan, C.M., Phillips, O.L., Willcock, S., Verbeeck, H., Carreiras, J., Hein, L. et al.. A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps. Remote Sensing of Environment. 2022. https://doi.org/10.1016/j.rse.2022.112917.
Adzhar, R., Kelley, D. I., Dong, N., George, C., Torello Raventos, M., Veenendaal, E., ... & Gerard, F.. MODIS Vegetation Continuous Fields tree cover needs calibrating in tropical savannas.. Biogeosciences. 2022.
de Lima, R. A., Phillips, O. L., Duque, A., Tello, J. S., Davies, S. J., de Oliveira, A. A., ... & Vásquez, R.. Making forest data fair and open.. Nature Ecology & Evolution. 2022.
Sousa, T. R., Schietti, J., Ribeiro, I. O., Emílio, T., Fernández, R. H., Ter Steege, H., ... & Costa, F. R.. Water table depth modulates productivity and biomass across Amazonian forests.. Global Ecology and Biogeography. 2022.
Kay, H., Santoro, M., Cartus, O., Bunting, P. and Lucas, R.. Exploring the relationship between forest canopy height and canopy density from Spaceborne LiDAR observations. Remote Sensing. 2021. https://doi.org/10.3390/rs13244961
Duncanson, L., Armston, J., Disney, M. et al.. Good Practices for Satellite-Derived and Product Validation: Land Product Validation Subgroup (WGCV/CEOS).. 2021. https://doi.org/10.5067/doc/ceoswgcv/lpv/agb.001
Santoro, M., Cartus, O. and Fransson, J.E.. Integration of allometric equations in the water cloud model towards an improved retrieval of forest stem volume with L-band SAR data in Sweden.. Remote Sensing of Environment. 2021. https://doi.org/10.1016/j.rse.2020.112235
ForestPlots.net, Blundo, C., Carilla, J., Grau, R., Malizia, A., Malizia, L., Osinaga-Acosta, O., Bird, M., et al.. Taking the pulse of Earth’s tropical forests using networks of highly distributed plots.. Biological Conservation. 2021. https://doi.org/10.1016/j.biocon.2020.108849
Rodríguez-Veiga, P., Carreiras, J., Smallman, T.L., Exbrayat, J.-F., Ndambiri, J., Mutwiri, F., Nyasaka, D., Quegan, S., Williams, M. and Balzter, H. Carbon Stocks and Fluxes in Kenyan Forests and Wooded Grasslands Derived from Earth Observation and Model-Data Fusion.. Remote Sensing. 2020. https://doi.org/10.3390/rs12152380
Schepaschenko, D., Chave, J., Phillips, O.L., Lewis, S.L., Davies, S.J., Réjou-Méchain, M., Sist, P., Scipal, K., Perger, C., Herault, B. and Labrière, N.. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass.. Scientific Data. 2019. https://doi.org/10.1038/s41597-019-0196-1
Herold, M., Carter, S., Avitabile, V., Espejo, A.B., Jonckheere, I., Lucas, R., McRoberts, R.E., Næsset, E., Nightingale, J., Petersen, R. and Reiche, J.. The role and need for space-based forest biomass-related measurements in environmental management and policy.. Surveys in Geophysics.. 2019. https://doi.org/10.1007/s10712-019-09510-6
Berzaghi, F., Longo, M., Ciais, P., Blake, S., Bretagnolle, F., Vieira, S., Scaranello, M., Scarascia-Mugnozza, G. and Doughty, C.E.. Carbon stocks in central African forests enhanced by elephant disturbance.. Nature Geoscience. 2019. https://www.nature.com/articles/s41561-019-0395-6
Fischer, F. J., Maréchaux, I., & Chave, J.. Improving plant allometry by fusing forest models and remote sensing. New Phytologist.. 2019. https://doi.org/10.1111/nph.15810
Chave, J., Davies, S. J., Phillips, O. L., Lewis, S. L., Sist, P., Schepaschenko, D., ... & Duncanson, L.. Ground data are essential for biomass remote sensing missions. Surveys in Geophysics. 2019. https://doi.org/10.1007/s10712-019-09528-w
Quegan, S., Le Toan, T., Chave, J. et al.. The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space. Remote Sensing of Environment. 2019. https://doi.org/10.1016/j.rse.2019.03.032
Tebaldini, S., Minh, D. H. T., d’Alessandro, M. M., Villard, L., Le Toan, T., & Chave, J.. The Status of Technologies to Measure Forest Biomass and Structural Properties: State of the Art in SAR Tomography of Tropical Forests. Surveys in Geophysics. 2019. https://doi.org/10.1007/s10712-019-09532-0
Duncanson, L., Armston, J., Disney, M. et al.. The importance of consistent global forest aboveground biomass product validation. Surveys in Geophysics. 2019. https://doi.org/10.1007/s10712-019-09538-8
Schepaschenko, D., See, L., Lesiv, M., Bastin, J.F., Mollicone, D., Tsendbazar, N.E., Bastin, L., McCallum, I., Bayas, J.C.L., Baklanov, A. and Perger, C. Recent Advances in Forest Observation with Visual Interpretation of Very High-Resolution Imagery. Surveys in Geophysics. 2019. https://doi.org/10.1007/s10712-019-09533-z
Phillips, O.L., Sullivan, M.J.P., Baker, T.R., Monteagudo Mendoza, A., Nunez Vargas, P., Vasquez, R.. Species Matter: Wood density Influences Tropical Forest Biomass at Multiple Scales.. Surveys in Geophysics.. 2019. https://doi.org/10.1007/s10712-019-09540-0
Schepaschenko, D., Moltchanova, E., Shvidenko, A., Blyshchyk, V., Dmitriev, E., Martynenko, O., See, L. and Kraxner, F.. Improved estimates of biomass expansion factors for Russian forests. Forests. 2018. https://doi.org/10.3390/f9060312