The multi-factor integrated classification is usually used in urban land grading evaluation. The weights of urban land
grading evaluation factors determine the evaluation results. Therefore, the method used to determine the weights of
evaluation factors is of significant importance for the evaluation result. In this paper, a new method for determining the
weights of urban land grading evaluation factors, i.e., K-means clustering and spearman rank correlation analysis, is
proposed. This method is capable of decreasing human error and enhancing the effectiveness of the automatization
process.
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