Publications about 'forest biomass'

Articles in journal or book chapters

1. Aboveground forest biomass varies across continents, ecological zones and successional stages: Refined IPCC default values for tropical and subtropical forests. Environmental Research Letters, 17(1), 2022. [bibtex-entry]



2. H. Yang, P. Ciais, J.-P. Wigneron, J. Chave, O. Cartus, X. Chen, L. Fan, J.K. Green, Y. Huang, E. Joetzjer, H. Kay, D. Makowski, F. Maignan, M. Santoro, S. Tao, L. Liu, and Y. Yao. Climatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Niño. Proceedings of the National Academy of Sciences of the United States of America, 119(26), 2022. [bibtex-entry]



3. Stefano Tebaldini, Dinh Ho Tong Minh, Mauro Mariotti d'Alessandro, Ludovic Villard, Thuy Le Toan, and Jerome Chave. The Status of Technologies to Measure Forest Biomass and Structural Properties: State of the Art in SAR Tomography of Tropical Forests. Surveys in Geophysics, May 2019. Keyword(s): SAR Processing, SAR Tomography, BIOMASS, Earth Explorer 7, EE7, Airborne radar, Array signal processing, Capon, Capon beamformer, L-band, P-band, SAR processing, SAR tomography, beamforming, Focusing, forestry, interferometry, InSAR, multibaseline, multiple signal classification, MUSIC, polarimetry, Remote Sensing, synthetic aperture radar, SAR, scattering, three-dimensional imaging, 3-D imaging, time-domain back-projection, TDBP, tomography, Vegetation, Spaceborne SAR. [Abstract] [bibtex-entry]



4. Astor T. Caicoya, Matteo Pardini, Irena Hajnsek, and Konstantinos P. Papathanassiou. Forest Above-Ground Biomass Estimation From Vertical Reflectivity Profiles at L-Band. IEEE Geosci. Remote Sens. Lett., 12(12):2379-2383, December 2015. Keyword(s): SAR Processing, SAR Tomography, L-band, Capon, forestry, vegetation mapping, L-band reflectivity profiles, SAR tomography, forest above-ground biomass estimation, forest stand densities, height measurements, root-mean-square error, vertical forest structure information, vertical radar reflectivity profiles, vertical reflectivity profiles, Biomass, Estimation, Image color analysis, L-band, Remote sensing, Synthetic aperture radar, Forest allometry, L-band, forest biomass, synthetic aperture radar (SAR) tomography, vertical forest structure, vertical reflectivity profiles. [Abstract] [bibtex-entry]



5. Marco Lavalle and Scott Hensley. Extraction of Structural and Dynamic Properties of Forests From Polarimetric-Interferometric SAR Data Affected by Temporal Decorrelation. IEEE Trans. Geosci. Remote Sens., 53(9):4752-4767, September 2015. Keyword(s): SAR Processing, Decorrelation, Temporal Decorrelation, Gaussian processes, optical radar, radar imaging, radar interferometry, radar polarimetry, synthetic aperture radar, vegetation mapping, Gaussian-statistic motion model, Harvard Forest, L-band NASA Uninhabited Aerial Vehicle Synthetic Aperture Radar, Laser Vegetation and Ice Sensor, Massachussetts, NASA lidar, RMoG model, RVoG model, USA, canopy elements, canopy motion, forest biomass estimation, forest dynamic property, forest property estimation, forest structural property, forest vertical structure, least square distance minimization, lidar-derived height, multiplicative factors, polarimetric channels, polarimetric-interferometric SAR data, polarimetric-interferometric coherence, polarimetric-interferometric radar image, random-motion-over-ground model, random-volume-over-ground model, temporal coherence, temporal decorrelation effect, tree height, volumetric coherence, volumetric decorrelation effect, wave polarization, Biomass, Coherence, Data models, Decorrelation, Radar, Vegetation, Decorrelation, interferometry, polarimetry. [Abstract] [bibtex-entry]



6. Maciej J. Soja, H.J. Persson, and Lars M.H. Ulander. Estimation of Forest Biomass From Two-Level Model Inversion of Single-Pass InSAR Data. IEEE Trans. Geosci. Remote Sens., 53(9):5083-5099, September 2015. Keyword(s): data acquisition, digital elevation models, forestry, radar interferometry, remote sensing by radar, synthetic aperture radar, vegetation, AD 2008, AD 2010, AD 2011, AD 2012, AD 2013, InSAR processing, Krycklan feature, Remningstorp feature, Swedish test site, VV-polarized TanDEM-X acquisition, aboveground biomass estimation, biomass predictor, canopy density, digital terrain model, forest biomass estimation, forest height, hemiboreal forest, northern Sweden, single-pass InSAR data, single-pass interferometric synthetic aperture radar data, southern Sweden, two-level model inversion, Biological system modeling, Biomass, Computational modeling, Correlation, Decorrelation, Estimation, Synthetic aperture radar, Aboveground biomass (AGB), TanDEM-X (TDM), canopy density, forest height, interferometric model, interferometric syntheticaperture radar (InSAR), two-level model (TLM). [Abstract] [bibtex-entry]



7. Scott Hensley, S. Oveisgharan, S. Saatchi, M. Simard, R. Ahmed, and Z. Haddad. An Error Model for Biomass Estimates Derived From Polarimetric Radar Backscatter. IEEE_J_GRS, 52(7):4065-4082, July 2014. Keyword(s): air pollution, carbon capture and storage, remote sensing by radar, vegetation, above ground biomass, basic imaging physics, biomass estimation accuracy, carbon flux measurement, carbon storage, disturbance quantification, ecosystem processes, error model, forest carbon inventories, forested areas, ground carbon, instrument parameter, mission parameter, notional Earth observing mission, polarimetric radar backscatter, radar polarimetric measurements, regrowth quantification, remote sensing measurements, Backscatter, Biological system modeling, Biomass, Radar measurements, Radar polarimetry, Signal to noise ratio, Backscatter error model, forest biomass, polarimetry, synthetic aperture radar (SAR). [bibtex-entry]



8. Ross F. Nelson, Peter Hyde, Patrick Johnson, Bomono Emessiene, Marc L. Imhoff, Robert Campbell, and Wilson Edwards. Investigating RaDAR-LiDAR synergy in a North Carolina pine forest. Remote Sensing of Environment, 110(1):98-108, September 2007. Keyword(s): SAR Processing, Biomass, Forest, VHFRaDAR, profiling LiDAR, biomass, RaDAR-LiDAR synergy, VHFSAR DATA, SMALL-FOOTPRINT LIDAR, AIRBORNE LASER DATA, STEM VOLUME, STAND CHARACTERISTICS, AERIAL-PHOTOGRAPHY, VEGETATION BIOMASS, CONIFEROUS FOREST, BOREAL FORESTS, SCANNER DATA. [Abstract] [bibtex-entry]



9. M. C. Dobson, F. T. Ulaby, T. LeToan, A. Beaudoin, E. S. Kasischke, and N. Christensen. Dependence of radar backscatter on coniferous forest biomass. IEEE Trans. Geosci. Remote Sens., 30(2):412-415, March 1992. Keyword(s): SAR Processing, Forest, Forest parameters, biomass, C-band, Duke, France, L-band, Landes, North Carolina, P-band, SAR data, United States, age, coniferous forest biomass, maritime pines, plantations, radar backscatter, remote sensing, backscatter, ecology, forestry, remote sensing by radar. [Abstract] [bibtex-entry]

Conference articles

1. F. Hélière, C.C. Lin, F. Fois, M. Davidson, A. Thompson, and P. Bensi. BIOMASS: A P-band SAR Earth explorer core mission candidate. In Proc. IEEE Radar Conf., pages 1-6, May 2009. Keyword(s): BIOMASS mission, Earth explorer core mission candidate, P-band, forest area, forest biomass, forest disturbances, frequency 425 MHz, global maps, synthetic aperture radar, terrestrial carbon cycle, remote sensing by radar, spaceborne radar, synthetic aperture radar. [Abstract] [bibtex-entry]



2. R.K. Raney. DESDynI adopts hybrid polarity SAR architecture. In Radar Conference, 2009 IEEE, pages 1-4, May 2009. Keyword(s): DESDynI mission, L-band synthetic aperture radar, The National Research Council's Earth Science 2007 Decadal Survey, circular polarization, forest biomass, hybrid-polarity dual-polarised SAR, quadrature-polarimetric SAR mode, terrain surface deformation, polarisation, synthetic aperture radar. [Abstract] [bibtex-entry]



3. B. Hallberg, G. Smith, A. Olofsson, and Lars M. H. Ulander. Performance Simulation of Spaceborne P-band SAR for Global Biomass Retrieval. In IGARSS '04, International Geoscience and Remote Sensing Symposium, September 2004. Keyword(s): SAR Processing, Simulation, P-Band, Biomass Retrieval, Forest. [Abstract] [bibtex-entry]

Internal reports

1. Shaun Quegan, Thuy Le Toan, Jérôme Chave, Jorgen Dall, Konstantinos P. Papathanassiou, Fabio Rocca, Lars Ulander, and Mathew Williams. Report for Mission Selection: Biomass. Technical report SP-1324/1 (3 volume series), ESA, Noordwijk, The Netherlands, May 2012. Keyword(s): BIOMASS, BIOMASS MISSION, ESA, European Space Agency, P-Band, Spaceborne SAR, SAR. [Abstract] [bibtex-entry]



2. Report of the DESDynI Applications Workshop. Technical report, Version 1, April 2009. Keyword(s): DESDynI mission, BIOMASS mission, Earth explorer core mission candidate, P-band, forest area, forest biomass, forest disturbances, global maps, synthetic aperture radar, terrestrial carbon cycle, remote sensing by radar, spaceborne radar, DESDynl mission, Deformation, Ecosystem Structure, and Dynamics of Ice, Earth Science Decadal Survey, National Research Council, biomass estimation, carbon cycle, cryosphere objectives, ecosystem function, integrated L-band InSAR, multibeam Lidar mission, solid Earth surface deformation, surface elevation changes, topography measure, vegetation structure, deformation, optical radar, radar interferometry, remote sensing by radar, topography (Earth), vegetation. [bibtex-entry]



3. Candidate Earth Explorer Core Mission BIOMASS - Report for Assessment. Technical report, ESA SP-1313/2, November 2008. Keyword(s): BIOMASS mission, Earth explorer core mission candidate, P-band, forest area, forest biomass, forest disturbances, frequency 425 MHz, global maps, synthetic aperture radar, terrestrial carbon cycle, remote sensing by radar, spaceborne radar, synthetic aperture radar. [bibtex-entry]

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This collection of SAR literature is far from being complete.
It is rather a collection of papers which I store in my literature data base. Hence, the list of publications under PUBLICATIONS OF AUTHOR'S NAME should NOT be mistaken for a complete bibliography of that author.

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