The unascertained attribute measurement analysis method for the evaluation of urban green space soil fertility

A synthetic evaluation method for soil fertility was investigated based on unascertained mathematical theory, attribute mathematical theory, and the unascertained attribute measurement analysis method (UAMA). A synthetic evaluation and classification of soil fertility in urban green spaces was postulated. Firstly, the evaluation indexes and their classification standards, and the grades for soil fertility status were determined for the evaluation of urban green space soil fertility. Secondly, the unascertained attribute measurement functions of each index were constructed to compute the unascertained attribute measurement value of the single index and the synthetic unascertained attribute measurement value. Finally, the evaluation of soil samples from urban green spaces was conducted using the confidence criteria to determine the status and classification of soil fertility. The UAMA method in this paper was tested based on the fuzzy comprehensive method for two soil fertility samples, and the entire-array-polygon indicator method, matter-element extension method, and improved artificial neural network method for 13 soil fertility samples. The consistency rates were 100%, 84.62%, 92.31%, and 100% between the UAMA method and fuzzy comprehensive method, entire-array-polygon indicator method, matter-element extension method, and improved artificial neural network method, respectively. Case studies indicated that the UAMA method used in this paper was feasible and reasonable, and it provided a new method for the evaluation of urban green space soil fertility.