The following 5 publications cited the product AfriSAR: Gridded Forest Biomass and Canopy Metrics Derived from LVIS, Gabon, 2016.
| Year | Citation |
|---|---|
| 2024 | Liu, X., C.S. Neigh, M. Pardini, and M. Forkel. 2024. Estimating forest height and above-ground biomass in tropical forests using P-band TomoSAR and GEDI observations. International Journal of Remote Sensing. 45(9):3129-3148. https://doi.org/10.1080/01431161.2024.2343134 |
| 2024 | Luo, H., C. Yue, Y. Wu, X. Zhang, C. Lu, and G. Ou. 2024. An efficient method for estimating tropical forest canopy height from airborne PolInSAR data. Ecological Indicators. 166:112566. https://doi.org/10.1016/j.ecolind.2024.112566 |
| 2023 | Choi, C., M. Pardini, J. Armston, and K.P. Papathanassiou. 2023. Forest Biomass Mapping Using Continuous InSAR and Discrete Waveform Lidar Measurements: A TanDEM-X/GEDI Test Study. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16:7675-7689. https://doi.org/10.1109/JSTARS.2023.3302026 |
| 2021 | Fatoyinbo, T., J. Armston, M. Simard, S. Saatchi, M. Denbina, M. Lavalle, M. Hofton, H. Tang, S. Marselis, N. Pinto, S. Hancock, B. Hawkins, L. Duncanson, B. Blair, C. Hansen, Y. Lou, R. Dubayah, S. Hensley, C. Silva, J.R. Poulsen, N. Labriere, N. Barbier, K. Jeffery, D. Kenfack, M. Herve, P. Bissiengou, A. Alonso, G. Moussavou, L.T.J. White, S. Lewis, and K. Hibbard. 2021. The NASA AfriSAR campaign: Airborne SAR and lidar measurements of tropical forest structure and biomass in support of current and future space missions. Remote Sensing of Environment. 264:112533. https://doi.org/10.1016/j.rse.2021.112533 |
| 2021 | Stovall, A.E.L., T. Fatoyinbo, N.M. Thomas, J. Armston, M.O. Ebanega, M. Simard, C. Trettin, R.V. Obiang Zogo, I.A. Aken, M. Debina, A.M. Me Kemoe, E.O. Assoumou, J.S. Kim, D. Lagomasino, S.K. Lee, J.C. Ndong Obame, G.D. Voubou, and C.Z. Essono. 2021. Comprehensive comparison of airborne and spaceborne SAR and LiDAR estimates of forest structure in the tallest mangrove forest on earth. Science of Remote Sensing. 4:100034. https://doi.org/10.1016/j.srs.2021.100034 |