Retrieving forest stand parameters from SAR backscatter data using a neural network trained by a canopy backscatter model

International Journal of Remote Sensing

Volumn 18, Issue 4, 1997, Pages 981-989

  Wang, Y ^a   Dong, D ^b  

^a EAST CAROLINA UNIVERSITY   (United States)

^b HENAN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKSCATTERING; FORESTRY; MATHEMATICAL MODELS; SYNTHETIC APERTURE RADAR;

RADAR WAVELENGTHS; STAND DENSITY;

NEURAL NETWORKS;

AIRSAR; BACKSCATTER; BACKSCATTERING; CANOPY; DIAMETER AT BREAST HEIGHT; FOREST STAND; METHOD EVALUATION; NEURAL NETWORK; PINE FOREST; PONDEROSA PINE; REMOTE SENSING; SAR; SYNTHETIC APERTURE RADAR; TRAINING;

USA, CALIFORNIA, MOUNT SHASTA;

PINACEAE; PINUS PONDEROSA;

EID: 0031103298     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/014311697218872     Document Type: Article

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