An Artificial Neural Network for Inversion of Vegetation Parameters from Radar Backscatter Coefficients

An inverse scattering model based on an artificial neural network using the back-error propagation technique is presented in this paper. The vegetation canopy is modelled as a half-space of randoml...

[1]  Hean-Teik Chuah,et al.  A Monte Carlo method for radar backscatter from a half-space random medium , 1989 .

[2]  A. K. Fung,et al.  A scatter model for vegetation up to Ku-band , 1984 .

[3]  A. Fung,et al.  Electromagnetic wave scattering from some vegetation samples , 1988 .

[4]  L. Tsang,et al.  Radiative transfer theory for active remote sensing of a layer of small ellipsoidal scatterers. [of vegetation] , 1981 .

[5]  R. T. Savely,et al.  Future impacts of artificial neural systems on industry. , 1990, ISA transactions.

[6]  A. K. Fung,et al.  Scattering from a random layer embedded with dielectric needles , 1986 .

[7]  R. Schiffer,et al.  Light scattering by dielectric needles and disks , 1979 .

[8]  Roger H. Lang,et al.  Microwave backscattering from an anisotropic soybean canopy , 1986 .

[9]  Gary S. Brown,et al.  A theory and model for wave propagation through foliage , 1982 .

[10]  A radar backscatter model for forest stands , 1992 .

[11]  Guoqing Sun,et al.  Simulation of L-band and HH microwave backscattering from coniferous forest stands: a comparison with SIR-B data , 1988 .

[12]  F. Ulaby,et al.  Vegetation modeled as a water cloud , 1978 .

[13]  Gerald M. Edelman,et al.  Selective Neural Networks and Their Implications for Recognition Automata , 1987 .

[14]  Robert J. Marks,et al.  Inversion Of Snow Parameters From Passive Microwave Remote Sensing Measurements By A Neural Network Trained With A Multiple Scattering Model , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.

[15]  Stephen Grossberg,et al.  The ART of adaptive pattern recognition by a self-organizing neural network , 1988, Computer.

[16]  M. A. Karam,et al.  Electromagnetic scattering from a layer of finite length, randomly oriented, dielectric, circular cylinders over a rough interface with application to vegetation , 1988 .

[17]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[18]  H. T. Chuah,et al.  A multiconstituent and multilayer microwave backscatter model for a vegetative medium , 1990 .

[19]  Kunihiko Fukushima,et al.  A neural network for visual pattern recognition , 1988, Computer.

[20]  Roger Lang,et al.  Microwave Inversion of Leaf Area and Inclination Angle Distributions from Backscattered Data , 1985, IEEE Transactions on Geoscience and Remote Sensing.