Publications

Here you can find a list of publications on BIOMASS that our project members published lately.

P-BAND RETRIEVAL

Banda, F., Giudici, D., Le Toan, T., Mariotti d’Alessandro, M., Papathanassiou, K., Quegan, S., Riembauer, G., Scipal, K., Soja, M., Tebaldini, S., Ulander, L., & Villard, L. (2020). The BIOMASS Level 2 Prototype Processor: Design and experimental results of above-ground biomass estimation. Remote Sensing, 12(6), Article 6. https://doi.org/10.3390/rs12060985

Quegan, S., Le Toan, T., Chave, J., Dall, J., Exbrayat, J.-F., Minh, D. H. T., Lomas, M., D’Alessandro, M. M., Paillou, P., Papathanassiou, K., Rocca, F., Saatchi, S., Scipal, K., Shugart, H., Smallman, T. L., Soja, M. J., Tebaldini, S., Ulander, L., Villard, L., & Williams, M. (2019). The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space. Remote Sensing of Environment, 227, 44–60. https://doi.org/10.1016/j.rse.2019.03.032

DYNAMIC VEGETATION MODELING

Wang, S., Yang, H., Koirala, S., Forkel, M., Reichstein, M., & Carvalhais, N. (2024). Understanding disturbance regimes from patterns in modeled forest biomass. Journal of Advances in Modeling Earth Systems, 16(6), e2023MS004099. https://doi.org/10.1029/2023MS004099

Zhan, C., Orth, R., Yang, H., Reichstein, M., Zaehle, S., Kauwe, M. G. D., Rammig, A., & Winkler, A. J. (2024). Estimating the CO₂ fertilization effect on extratropical forest productivity from Flux-tower observations. ESSOAr. https://www.authorea.com/doi/full/10.22541/essoar.170049207.70121877

Yang, H., Wang, S., Son, R., Lee, H., Benson, V., Zhang, W., Zhang, Y., Zhang, Y., Kattge, J., Boenisch, G., Schepaschenko, D., Karaszewski, Z., Stereńczak, K., Moreno-Martínez, Á., Nabais, C., Birnbaum, P., Vieilledent, G., Weber, U., & Carvalhais, N. (2024). Global patterns of tree wood density. Global Change Biology, 30(3), e17224. https://doi.org/10.1111/gcb.17224

Yang, H., Munson, S. M., Huntingford, C., Carvalhais, N., Knapp, A. K., Li, X., Peñuelas, J., Zscheischler, J., & Chen, A. (2023). The detection and attribution of extreme reductions in vegetation growth across the global land surface. Global Change Biology, 29(8), 2351–2362. https://doi.org/10.1111/gcb.16595

Yang, H., Ciais, P., Frappart, F., Li, X., Brandt, M., Fensholt, R., Fan, L., Saatchi, S., Besnard, S., Deng, Z., Bowring, S., & Wigneron, J.-P. (2023). Global increase in biomass carbon stock dominated by growth of northern young forests over past decade. Nature Geoscience, 16(10), 886–892. https://doi.org/10.1038/s41561-023-01274-4

Xiao, C., Zaehle, S., Yang, H., Wigneron, J.-P., Schmullius, C., & Bastos, A. (2023). Land cover and management effects on ecosystem resistance to drought stress. Earth System Dynamics, 14(6), 1211–1237. https://doi.org/10.5194/esd-14-1211-2023

Yang, H., Stereńczak, K., Karaszewski, Z., & Carvalhais, N. (2023). Similar importance of inter-tree and intra-tree variations in wood density observations in Central Europe. EGUsphere, 1–16. https://doi.org/10.5194/egusphere-2023-2691

Davies, S. J., Abiem, I., Abu Salim, K., Huth, A., Papathanassiou, K., … Zuleta, D. (2021). ForestGEO: Understanding forest diversity and dynamics through a global observatory network. Biological Conservation, 253, 108907. https://doi.org/10.1016/j.biocon.2020.108907

Singh, J., Levick, S. R., Guderle, M., & Schmullius, C. (2020). Moving from plot-based to hillslope-scale assessments of savanna vegetation structure with long-range terrestrial laser scanning (LR-TLS). International Journal of Applied Earth Observation and Geoinformation, 90, 102070. https://doi.org/10.1016/j.jag.2020.102070

Rödig, E., Knapp, N., Fischer, R., Bohn, F. J., Dubayah, R., Tang, H., & Huth, A. (2019). From small-scale forest structure to Amazon-wide carbon estimates. Nature Communications, 10, 5088. https://doi.org/10.1038/s41467-019-13063-y

Rödig, E., Cuntz, M., Rammig, A., Fischer, R., Taubert, F., & Huth, A. (2018). The importance of forest structure for carbon fluxes of the Amazon rainforest. Environmental Research Letters, 13(5), 054013. https://doi.org/10.1088/1748-9326/aabc61

Rodríguez-Veiga, P., Quegan, S., Carreiras, J., Persson, H. J., Fransson, J. E. S., Hoscilo, A., Ziółkowski, D., Stereńczak, K., Lohberger, S., Stängel, M., Berninger, A., Siegert, F., Avitabile, V., Herold, M., Mermoz, S., Bouvet, A., Le Toan, T., Carvalhais, N., Santoro, M., … Balzter, H. (2019). Forest biomass retrieval approaches from Earth observation in different biomes. International Journal of Applied Earth Observation and Geoinformation, 77, 53–68. https://doi.org/10.1016/j.jag.2018.12.008

Taubert, F., Fischer, R., Groeneveld, J., Lehmann, S., Müller, M. S., Rödig, E., Wiegand, T., & Huth, A. (2018). Global patterns of tropical forest fragmentation. Nature, 554(7693), 519–522. https://doi.org/10.1038/nature25508

Bohn, F. J., & Huth, A. (2017). The importance of forest structure to biodiversity–productivity relationships. Royal Society Open Science, 4(1), 160521. https://doi.org/10.1098/rsos.160521

SAR REMOTE SENSING

Mansour, I., Papathanassiou, K., Hänsch, R., & Hajnsek, I. (2025). Hybrid machine learning forest height estimation from TanDEM-X InSAR. IEEE Transactions on Geoscience and Remote Sensing, 63, 1–11. https://doi.org/10.1109/TGRS.2024.3520387

Qi, W., Armston, J., Choi, C., Stovall, A., Saarela, S., Pardini, M., Fatoyinbo, L., Papathanassiou, K., Pascual, A., & Dubayah, R. (2025). Mapping large-scale pantropical forest canopy height by integrating GEDI lidar and TanDEM-X InSAR data. Remote Sensing of Environment, 318, 114534. https://doi.org/10.1016/j.rse.2024.114534

Guliaev, R., Su Kim, J., Pardini, M., & Papathanassiou, K. P. (2024). On the use of tomographically derived reflectivity profiles for Pol-InSAR forest height inversion in the context of the BIOMASS mission. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–12. https://doi.org/10.1109/TGRS.2024.3497572

Pardini, M., Romero-Puig, N., Guliaev, R., & Papathanassiou, K. P. (2024). Identification of forest structure changes from L-band SAR data: A tomographic perspective. In EUSAR 2024; 15th European Conference on Synthetic Aperture Radar (pp. 748–752). IEEE. https://ieeexplore.ieee.org/abstract/document/10659479

Zheng, B., Ciais, P., Chevallier, F., Yang, H., Canadell, J. G., Chen, Y., van der Velde, I. R., Aben, I., Chuvieco, E., Davis, S. J., Deeter, M., Hong, C., Kong, Y., Li, H., Li, H., Lin, X., He, K., & Zhang, Q. (2023). Record-high CO₂ emissions from boreal fires in 2021. Science, 379(6635), 912–917. https://doi.org/10.1126/science.ade0805

Moreira, A., Prats-Iraola, P., Nannini, M., Martín-Del-Campo-Becerra, G. D., Pardini, M., Papathanassiou, K., & Reigber, A. (2023). Spaceborne multi-baseline synthetic aperture radar (SAR) imaging. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 345–348). IEEE. https://doi.org/10.1109/IGARSS52108.2023.10282342

Henniger, H., Huth, A., & Bohn, F. J. (2023). A new approach to derive productivity of tropical forests using radar remote sensing measurements. Royal Society Open Science, 10(11), 231186. https://doi.org/10.1098/rsos.231186

Choi, C., Cazcarra-Bes, V., Guliaev, R., Pardini, M., Papathanassiou, K. P., Qi, W., Armston, J., & Dubayah, R. O. (2023). Large-scale forest height mapping by combining TanDEM-X and GEDI data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 2374–2385. https://doi.org/10.1109/JSTARS.2023.3244866

Guliaev, R., Cazcarra-Bes, V., Pardini, M., & Papathanassiou, K. (2021). Forest height estimation by means of TanDEM-X InSAR and waveform lidar data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3084–3094. https://doi.org/10.1109/JSTARS.2021.3058837

Pardini, M., Cazcarra-Bes, V., & Papathanassiou, K. P. (2021). TomoSAR mapping of 3D forest structure: Contributions of L-band configurations. Remote Sensing, 13(12), Article 12. https://doi.org/10.3390/rs13122255

Ma, X., Migliavacca, M., Wirth, C., Bohn, F. J., Huth, A., Richter, R., & Mahecha, M. D. (2020). Monitoring plant functional diversity using the reflectance and echo from space. Remote Sensing, 12(8), 1248. https://doi.org/10.3390/rs12081248

Dubois, C., Mueller, M. M., Pathe, C., Jagdhuber, T., Cremer, F., Thiel, C., & Schmullius, C. (2020). Characterization of land cover seasonality in Sentinel-1 time series data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-3–2020, 97–104. https://doi.org/10.5194/isprs-annals-V-3-2020-97-2020

Thiel, C., Müller, M. M., Berger, C., Cremer, F., Dubois, C., Hese, S., Baade, J., Klan, F., & Pathe, C. (2020). Monitoring selective logging in a pine-dominated forest in Central Germany with repeated drone flights utilizing a low cost RTK quadcopter. Drones, 4(2), 11. https://doi.org/10.3390/drones4020011

Urban, M., Heckel, K., Berger, C., Schratz, P., Smit, I. P. J., Strydom, T., Baade, J., & Schmullius, C. (2020). Woody cover mapping in the savanna ecosystem of the Kruger National Park using Sentinel-1 C-band time series data. Koedoe, 62(1). https://doi.org/10.4102/koedoe.v62i1.1621

Fischer, R., Knapp, N., Bohn, F., & Huth, A. (2019). Remote sensing measurements of forest structure types for ecosystem service mapping. In M. Schröter, A. Bonn, S. Klotz, R. Seppelt, & C. Baessler (Eds.), Atlas of Ecosystem Services: Drivers, Risks, and Societal Responses (pp. 63–67). Springer. https://doi.org/10.1007/978-3-319-96229-0_11

Fischer, R., Knapp, N., Bohn, F., Shugart, H. H., & Huth, A. (2019). The relevance of forest structure for biomass and productivity in temperate forests: New perspectives for remote sensing. Surveys in Geophysics, 40(4), 709–734. https://doi.org/10.1007/s10712-019-09519-x

Ma, X., Mahecha, M. D., Migliavacca, M., van der Plas, F., Benavides, R., Ratcliffe, S., Kattge, J., Richter, R., Musavi, T., Baeten, L., Barnoaiea, I., Bohn, F. J., Bouriaud, O., Bussotti, F., Coppi, A., Domisch, T., Huth, A., Jaroszewicz, B., Joswig, J., … Wirth, C. (2019). Inferring plant functional diversity from space: The potential of Sentinel-2. Remote Sensing of Environment, 233, 111368. https://doi.org/10.1016/j.rse.2019.111368

Stelmaszczuk-Górska, M. A., Urbazaev, M., Schmullius, C., & Thiel, C. (2018). Estimation of above-ground biomass over boreal forests in Siberia using updated in situ, ALOS-2 PALSAR-2, and RADARSAT-2 data. Remote Sensing, 10(10), 1550. https://doi.org/10.3390/rs10101550

Tello, M., Cazcarra-Bes, V., Pardini, M., & Papathanassiou, K. (2018). Forest structure characterization from SAR tomography at L-band. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(10), 3402–3414. https://doi.org/10.1109/JSTARS.2018.2859050

Pardini, M., Tello, M., Cazcarra-Bes, V., Papathanassiou, K. P., & Hajnsek, I. (2018). L- and P-band 3-D SAR reflectivity profiles versus lidar waveforms: The AfriSAR case. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(10), 3386–3401. https://doi.org/10.1109/JSTARS.2018.2847033

Urbazaev, M., Thiel, C., Cremer, F., Dubayah, R., Migliavacca, M., Reichstein, M., & Schmullius, C. (2018). Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico. Carbon Balance and Management, 13(1). https://doi.org/10.1186/s13021-018-0093-5

Agata, H., Aneta, L., Dariusz, Z., Krzysztof, S., Marek, L., Schmullius, C., & Carsten, P. (2018). Forest aboveground biomass estimation using a combination of Sentinel-1 and Sentinel-2 data. In IGARSS 2018 – IEEE International Geoscience and Remote Sensing Symposium (pp. 9026–9029). IEEE. https://doi.org/10.1109/IGARSS.2018.8517965

Rödig, E., Cuntz, M., Heinke, J., Rammig, A., & Huth, A. (2017). Spatial heterogeneity of biomass and forest structure of the Amazon rain forest: Linking remote sensing, forest modelling and field inventory. Global Ecology and Biogeography, 26(11), 1292–1302. https://doi.org/10.1111/geb.12639

Schmullius, C., Thiel, C., Pathe, C., & Santoro, M. (2015). Radar time series for land cover and forest mapping. In C. Kuenzer, S. Dech, & W. Wagner (Eds.), Remote Sensing Time Series: Revealing Land Surface Dynamics (pp. 323–356). Springer. https://doi.org/10.1007/978-3-319-15967-6_16

Santoro, M., Schmullius, C., Pathe, C., & Schwilk, J. (2012). Pan-boreal mapping of forest growing stock volume using hyper-temporal Envisat ASAR ScanSAR backscatter data. In 2012 IEEE International Geoscience and Remote Sensing Symposium (pp. 7204–7207). IEEE. https://doi.org/10.1109/IGARSS.2012.6352000