论文信息 - Implementation of temporal relationships in knowledge based classification of satellite images.

Implementation of temporal relationships in knowledge based classification of satellite images.

Classification of digital satellite images involves a process similar to classification problems in artificial intelligence. In a knowledge-based classification, ancillary data and knowledge are combined with spectral information. A method of knowledge-based classification based on temporal relationships between classes is introduced. Knowledge about crop rotations is represented by means of state transition matrices. Spectral image information, information stored in a GIS, and knowledge as represented in a matrix are combined in a Baysian maximum-likelihood classification.

L. Janssen | H. Middelkoop

[1] P. H. Swain,et al. Bayesian classification in a time-varying environment , 1978 .

[2] Alan H. Strahler,et al. The Use of Prior Probabilities in Maximum Likelihood Classification , 1980 .

[3] F. B. Van der Laan. Improvement of classification results of satellite imagery using context information from a topographic map , 1988 .

[4] Jian-Kang Wu,et al. Model-based remotely-sensed imagery interpretation , 1988 .

[5] Mark Sondheim,et al. Methods for Improving Accuracy of Thematic Mapper Ground Cover Classifications , 1988 .

[6] A. Skidmore. An expert system classifies eucalypt forest types using thematic mapper data and a digital terrain model , 1989 .

[7] C. Harlow,et al. Computational image interpretation models : an overview and a perspective , 1990 .

[8] John A. Richards,et al. Knowledge-based techniques for multi-source classification , 1990 .

[9] George F. Hepner,et al. Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification , 1990 .