Assessing the classification accuracy of multisource remote sensing data

Remote Sensing of Environment

Volumn 47, Issue 3, 1994, Pages 362-368

  Fitzgerald, R W ^a   Lees, B G ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

STATISTICAL METHODS;

DECISION TREE MODEL; KAPPA STATISTICS; MULTISOURCE REMOTE SENSING DATA;

REMOTE SENSING;

CLASSIFICATION ACCURACY; MULTISOURCE DATA; REMOTE SENSING;

EID: 0028167313     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/0034-4257(94)90103-1     Document Type: Article

References (13)

1. Neural network approaches versus statistical methods in classification of multi-source remote sensing data
2. A review of assessing the accuracy of classification of remotely sensed data
3. The environmental relationships of arboreal marsupials in a eucalypts forest: a basis for Australian wildlife management
4. Applications of neural networks to terrain classification
5. The application of neural networks to the floristic classification of remote sensing and GIS data in complex terrain
6. Application of neural networks for classification of multi-source multispectral remote sensing data
7. Artificial neural network classification using a minimal training set-comparison to conventional supervised classification
8. The measurement of observer agreement for categorical data
9. Decision tree and rule induction approach to integration of remotely sensed and GIS data in mapping vegetation in disturbed or hilly environments
10. A new method for predicting vegetation distribution using decision tree analysis in geographic information systems
11. Application of an artificial neural network to land-cover classification of Thematic Mapper imagery
12. Applying neural net technology for multi-objective land use planning