A means for utilizing ancillary information in multispectral classification

Remote Sensing of Environment

Volumn 12, Issue 6, 1982, Pages 463-477

  Richards, J A ^a   Landgrebe, D A ^b   Swain, P H ^b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FORESTRY;

REMOTE SENSING;

EID: 0020330547     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/0034-4257(82)90020-7     Document Type: Article

References (17)

1. Computer-aided analysis of Skylab multispectral scanner data in mountainous terrain for land use, forestry, water resource and geologic applications
2. Digital processing of Landsat MSS and topographic data to improve capabilities for computerized mapping of forest cover types
3. Improving forest cover classification accuracy from Landsat by incorporating topographic information
4. Forest site index mapping and modeling
5. Coniferous tree species mapping using Landsat data
6. Forest cover classification from Landsat imagery: An application for image processing
7. Incorporating collateral data in Landsat classification and modeling procedures
8. Scene labeling by relaxation algorithms
9. On the accuracy of pixel labeling
10. Computer classification of remotely sensed multispectral image data by extraction and classification of homogeneous objects
11. Classification of multispectral image data by extraction and classification of homogeneous objects
12. Contextual classification of multispectral image data: An unbiased estimator for the context distribution
13. Analysis of probabilistic relaxation labeling processes
14. Some experiments on Landsat pixel classification using relaxation operators
15. Pixel labeling by supervised probabilistic relaxation
16. The use of prior probabilities in maximum likelihood classification of remotely sensed data