@article {829,
	title = {Inclusion of a simple multiple scattering model into a microwave canopy backscatter model},
	journal = {Remote Sensing of Environment},
	volume = {63},
	year = {1998},
	note = {JOURNAL ARTICLE; RESEARCH ARTICLE},
	month = {1998},
	pages = {101-111},
	abstract = {A simple multiple scattering model has been incorporated into a microwave canopy backscatter model for forest stands with continuous or discontinuous tree canopies. The multiple scattering model was empirically derived using available calculated multiple scattering values and Monte Carlo simulation. All orders of scattering within canopies beyond single scattering were assumed to be isotropic. Multiple scattering was divided evenly among HH, HV, VH, and VV polarizations. The corresponding single scattering term was polarization-sensitive. The effect of the multiple scattering term on modeled canopy backscatter was less at long wavelengths than at short wavelengths. At a given wavelength, the multiple scattering term affected copolarized scattering less than cross-polarized scattering. These predictions were consistent with calibrated SAR observations and with our understanding of microwave scattering in forested environment. Including multiple scattering effects improved the agreement between modeled and measured canopy backscatter particularly for cross-polarized backscatter at short wavelengths.},
	keywords = {(Aerospace and Underwater Biological Effects--General, (Biophysics--Biocybernetics (1972- )), (Ecology, (Mathematical Biology and Statistical Methods), (Radiation--Radiation and Isotope Techniques), Environmental Biology--Plant), Forest Stand, Methods), Microwave Canopy Backscatter Model, Models and Simulations, remote sensing, Research Article, Simple Multiple Scattering Model},
	author = {Wang, Y. and Paris, J. F. and Davis, F. W.}
}
@article {825,
	title = {The effects of changes in forest biomass on radar backscatter from tree canopies},
	journal = {International Journal of Remote Sensing},
	volume = {16},
	year = {1995},
	note = {JOURNAL ARTICLE; RESEARCH ARTICLE},
	month = {1995},
	pages = {503-513},
	keywords = {(Aerospace and Underwater Biological Effects--General, (Biophysics--Biocybernetics (1972- )), (Ecology, (Mathematical Biology and Statistical Methods), (Plant Physiology, Biochemistry and Biophysics--Growth, Differentiation), Coniferopsida, Environmental Biology--Plant), Gymnosperms, Mathematical Model, Methods), North Carolina, Pine, Plants, Research Article, Spermatophyta, Spermatophytes, Synthetic Aperture Radar, Usa, Vascular plants},
	author = {Wang, Y. and Davis, F. W. and Melack, J. M. and Kasischke, E. S. and Christensen, N. L., Jr.}
}
@article {828,
	title = {The effects of changes in loblolly pine biomass and soil moisture on ERS-1 SAR backscatter},
	journal = {Remote Sensing of Environment},
	volume = {49},
	year = {1994},
	note = {JOURNAL ARTICLE; RESEARCH ARTICLE},
	month = {1994},
	pages = {25-31},
	keywords = {(Aerospace and Underwater Biological Effects--General, (Biochemistry--Physiological Water Studies (1970- )), (Biophysics--Biocybernetics (1972- )), (Ecology, (Forestry and Forest Products), (Mathematical Biology and Statistical Methods), (Plant Physiology, Biochemistry and Biophysics--Growth, Differentiation), (Plant Physiology, Biochemistry and Biophysics--Water Relations), (Soil Science--Fertility and Applied Studies (1970- )), (Soil Science--Physics and Chemistry (1970- )), Coniferopsida, Environmental Biology--Plant), European Remote Sensing Satellite Synthetic Aperture Radar, Gymnosperms, Mathematical Model, Methods), North Carolina, Plants, Research Article, Spermatophytes, Usa, Vascular plants},
	author = {Wang, Y. and Kasischke, E. S. and Melack, J. M. and Davis, F. W. and Christensen, N. L., Jr.}
}
@article {722,
	title = {Regression tree analysis of satellite and terrain data to guide vegetation sampling and surveys},
	journal = {Journal of Vegetation Science},
	volume = {5},
	year = {1994},
	note = {JOURNAL ARTICLE; RESEARCH ARTICLE},
	month = {1994},
	pages = {673-686},
	abstract = {Monitoring of regional vegetation and surface biophysical properties is tightly constrained by both the quantity and quality of ground data. Stratified sampling is often used to increase sampling efficiency, but its effectiveness hinges on appropriate classification of the land surface. A good classification must he sufficiently detailed to include the important sources of spatial variability, but at the same time it should be as parsimonious as possible to conserve scarce and expensive degrees of freedom in ground data. As part of the First ISLSCP (International Satellite Land Surface Climatology Program) Field Experiment (FIFE), we used Regression Tree Analysis to derive an ecological classification of a tail grass prairie landscape. The classification is derived from digital terrain, land use, and land cover data and is based on their association with spectral vegetation indices calculated from single-date and multi-temporal satellite imagery. The regression tree analysis produced a site stratification that is similar to the a priori scheme actually used in FIFE, but is simpler and considerably more effective in reducing sample variance in surface measurements of variables such as biomass, soil moisture and Bowen Ratio. More generally, regression tree analysis is a useful technique for identifying and estimating complex hierarchical relationships in multivariate data sets.},
	keywords = {(Aerospace and Underwater Biological Effects--General, (Ecology, (General Biology--Institutions, Administration and Legislation), (Methods, Materials and Apparatus, General--Field Methods), (Methods, Materials and Apparatus, General--Photography), Angiosperms, Biophysical Properties, Ecological Classification, Environmental Biology--Bioclimatology and Biometeorology), Environmental Biology--Plant), Gramineae, International Satellite Land Surface Climatology Program, Methods), monitoring, Monocots, Plants, Research Article, Satellite Imagery, Spermatophytes, Tall Grass Prairie Landscape, Vascular plants},
	author = {Michaelsen, J. and Schimel, D. S. and Friedl, M. A. and Davis, F. W. and Dubayah, R. C.}
}
