The spatial information of the image and evidence theory is applied to classification of remote sensing image based on neural networks.

Auto-classification of remote sensing image is the concrete application of patternrecognition technique in remote sensing technique territory.

This paper describes the problem in the BP neural network approach and the approach of BP neural network based on vector information to the classification of remote sensing images.

Application of a classification method based on counter propagation neural network in remote sensing image classification;

To improve the accuracy of remote sensing image classification,chaos immune glgorithm is proposed.

The advantages and disadvantages in remote sensing image classification methods at present are analyzed,in cluding maximum likelihood classification((MLC);) Artificial neural networks((ANN)) classification;Logic reasoning classification based on symbol and rules.

Dynamic monitoring of land use space-time changes based on remote sensing images comprehension model——taking Longkou city for example;

The methods of ATM location selection based on GIS and remote sensing images;

Improvement of the OPTA algorithm and its application in remote sensing images thinning;