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.In order to advance remote sensing image classification

multi-resouce spatial database is set up by means of GIS

the thought and concept of data mining are imported

and the remote sensing image classification frame is brought forward.The concept of classification

and the index of judging splitting point on continuous valued attributes samples are defined

a new algorithm is proposed

which mines classification rules on the continuous valued attributes spatial database.A trail area is selected

the two projects are put in practice

which are based on Spectra Data

combining of Spectra data and DEM data respectively

mining classification rules

classifying remote sensing image by the way of the algorithm

and comparing their classification accuracy.Trail outcome shows that:（1） the classification accuracy of the algorithm is good;（2） integrating DEM and other correlative data into the spatial database can advance classification accuracy.The way of mining classification rules being applied to remote sensing image classification broaden the channel of knowledge discovery in logic reasoning classification based on symbol and rules

advance the capability of discovering classification rules automatically.The new algorithm mining classification rules on the continuous valued attributes enlarge the adaptability of inducing learning algorithm to the classification of the continuous valued attributes samples.