Based on a statistic analysis of spectral characteristics of such objectives as road, building, sloping

farmland, vegetation, water and shade on the SPOT 5 remote sensing image in the Baokang phosphorite ore district of

Hubei Province, this paper holds that spectral properties of these objectives have certain similarity and

difference, and it is difficult to extract the mining area and the solid waste accurately based only on a single

classification method. Making use of the decision tree classification and setting up some classification rules in

combination with the related auxiliary data from the digital elevation model and the ore-bearing strata, the authors

successfully classified the objects in the ore district into various categories. Subsequent processing of the

classification results shows that the classification precision can reach 83.4%.