Improving the ANN classification accuracy of landsat data through spectral indices and linear transformations (PCA and TCT) Aimed at LU/LC Monitoring of a River Basin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9787, Issue , 2016, Pages 420-432

  Novelli, Antonio ^a   Tarantino, Eufemia ^a   Caradonna, Grazia ^a   Apollonio, Ciro ^a   Balacco, Gabriella ^a   Piccinni, Ferruccio ^a  

^a POLITECNICO DI BARI   (Italy)

Author keywords

Artificial Neural Networks; Land Use Land Cover; Principal component analysis; River basin; Spectral indices; Tasseled cap transformation

Indexed keywords

CLASSIFICATION (OF INFORMATION); COST EFFECTIVENESS; LAND USE; LINEAR TRANSFORMATIONS; MATHEMATICAL TRANSFORMATIONS; NEURAL NETWORKS; RIVERS; VEGETATION; WATERSHEDS;

BRIGHTNESS TEMPERATURES; CLASSIFICATION METHODS; CLASSIFICATION PROCEDURE; COST-EFFECTIVE MEANS; LAND USE/LAND COVER; RIVER BASINS; SPECTRAL INDICES; TASSELED CAP TRANSFORMATION;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84978882383     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-42108-7_32     Document Type: Conference Paper

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