基于土地定级估价信息的市场比较法研究

The Market Data Approach Based on Land Grading and Evaluation

  • 摘要: 探讨了在土地定级估价信息系统中,如何将市场比较法与基准地价体系有机地结合,充分利用土地定级和基准地价评估的成果进行宗地评估的技术和方法。通过模板建立并设计了相应的数据结构,解决了数据库结构的不确定性问题,采用聚类分析等数学方法实现了案例提取、匹配以及地价计算相应流程的算法。基于土地定级估价信息的市场比较法克服了传统市场比较法实现存在的问题,对实现宗地地价评估流程的自动化、保证评估结果的客观性具有重大意义

     

    Abstract: In this paper, the method how to use the results of land grading and evaluation to estimate the price of lot by combining the Market data approach with the system of land grading and evaluation is discussed. Market data approach is one of the most important methods of land evaluating. It conform s to the rules of substitution and analogy. Traditional process of Market data approach is realized by gathering data artificially, estimating the degree of analogy by expert experience. The influence of all factors to be modified is decided by ex pert. Because of the lack of the standard of quantity, the result of estimating is greatly controlled by person's subjectivity. In the Market data approach based on land grading and evaluation, region factors used in land grading and the factors used to modify lot price are selected by experts. Experts also give the power of region factors. According to the rules of land grading, the methods of calculating index of region factors' condition are established. Combining the statistic of land's marketing exchange material with experience of experts the modify ing system of lot's price is formed. The problem that structure of database used in the process of lot evaluation is dynamic and is designed by template and relevant dada structure. By the use of mathematics method such as analysis of classification, the data structure and algorithm of matching and collecting evaluated lot instance automatically and evaluating price of lot evaluated automatically are designed. The functions of Market data approach are realized in land grading and evaluation information system based on GIS. It overcomes the shortcomings of traditional process of Market data approach. So the results will be more scientific, objective and reasonable.

     

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