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Publications about 'wood'
Articles in journal or book chapters
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S. B. Kim,
Mahta Moghaddam,
L. Tsang,
Mariko S. Burgin,
X. Xu,
and E. G. Njoku.
Models of L-Band Radar Backscattering Coefficients Over Global Terrain for Soil Moisture Retrieval.
IEEE Transactions on Geoscience and Remote Sensing,
52(2):1381-1396,
February 2014.
Keyword(s): Maxwell equations,
permittivity,
remote sensing by radar,
soil,
time series,
vegetation mapping,
L-band radar backscattering coefficient models,
Maxwell equations,
RMS height,
VWC,
accurate soil moisture inversion,
airborne data,
airborne observation,
bare surface,
co-pol RMS errors,
corn crop,
datacube errors,
dielectric soil constant,
distorted Born approximation framework,
double-bounce reflectivity,
double-bounce volume-surface interaction,
empirical formulae,
empirical parameters,
fast soil moisture inversion,
field-based radar data,
global land surface,
global terrain,
grass fields,
in situ observation,
independent spaceborne phased array type L-band synthetic aperture radars,
input parameters,
international geosphere-biosphere programme scheme,
land surface class simulation,
lookup tables,
major crops,
mean difference range,
numerical solutions,
physical model outputs,
real-time soil moisture inversion,
rice crop,
shrub,
single scatterer,
soil moisture active passive mission data,
soil moisture retrieval,
soil surface root mean square,
sophisticated forward model direct inversion,
soybean crop,
spaceborne Aquarius scatterometer data,
surface scattering,
theoretical models.
[Abstract]
[bibtex-entry]
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Mariko S. Burgin,
D. Clewley,
R. M. Lucas,
and Mahta Moghaddam.
A Generalized Radar Backscattering Model Based on Wave Theory for Multilayer Multispecies Vegetation.
IEEE Transactions on Geoscience and Remote Sensing,
49(12):4832-4845,
December 2011.
Keyword(s): backscatter,
radar polarimetry,
remote sensing by radar,
vegetation,
AIRSAR data,
ALOS PALSAR,
Advanced Land Observing Satellite,
Airborne Synthetic Aperture Radar data,
Australia,
NASA JPL,
NASA Jet Propulsion Laboratory,
Phased Arrayed L-band Synthetic Aperture Radar data,
Queensland,
distorted Born approximation,
generalized radar backscattering model,
microwave interaction,
multilayer multispecies vegetation,
polarimetric radar backscattering coefficients,
single species discrete scatterer model,
soil moisture,
structurally complex vegetation,
surface model,
surface roughness parameterization,
two layer crown trunk models,
wave theory,
wooded savanna sites,
Backscatter,
Data models,
Mathematical model,
Scattering,
Synthetic aperture radar,
Vegetation,
Forest scattering,
multispecies vegetation,
synthetic aperture radar (SAR) backscattering,
wave theory.
[Abstract]
[bibtex-entry]
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H. Israelsson,
L. M. H. Ulander,
J. L. H. Askne,
J. E. S. Fransson,
P.-O. Frölind,
A. Gustavsson,
and H. Hellsten.
Retrieval of forest stem volume using VHF SAR.
IEEE Trans. Geosci. Remote Sens.,
35(1):36-40,
January 1997.
Keyword(s): SAR Processing,
Forest,
Forest parameters,
biomass,
28 to 60 MHz,
CARABAS,
HF radar,
Oland,
SAR,
Sweden,
VHF radar,
airborne radar,
backscattering coefficient,
biomass,
coherent all radio band sensing,
deciduous mixed forest,
dense forest,
discrimination,
forest stem volume,
forestry,
geophysical measurement technique,
horizontal dipole array,
radar imaging,
radar remote sensing,
radar scattering,
tree trunk,
vegetation mapping,
wood,
airborne radar,
forestry,
geophysical techniques,
radar cross-sections,
radar imaging,
remote sensing by radar,
synthetic aperture radar.
[Abstract]
[bibtex-entry]
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Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to
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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.
Last modified: Fri Feb 24 14:25:36 2023
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .
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