It is important to study the effect of land use change on ecosystem service value (ESV). Most previous studies have tended to directly use the ecosystem service equivalent value to calculate the ESV and then have compared multi period ESVs. Because of the use of different price bases, even if the value of the same ecosystem is assessed using multi period ESVs, the conclusions can be very different, which means there has to be a deviation evaluation. In order to improve the accuracy of these comparisons, we developed a Consumer price index(CPI) revised ESV coefficient method for multi period ESV computation. The upper reaches of the Huaihe River was used as a case study to estimate the spatial distribution and dynamics of ecosystem services. In this study, we used the land use and statistical yearbook data to investigate how the spatial-temporal evolution of land use structure and spatial patterns affect the ESV. The results showed that (1) the ESV generally showed an increasing trend in the study region. Between 1995 and 2005, the ESV decreased, but then increased significantly around 2010. Furthermore, the increase from 2010 to 2013 was higher than that for any other period. (2) The ESV increase was higher in mountain areas than in hilly areas, and the increase in hilly areas was higher than that in the plains, which shows a topographical gradient effect. The increase was mainly because of the contributions made by forest and water ecosystems. (3) There were significant correlations between the ESV and land use change and Aggregation index (AI) and Number of patches(NP)landscape pattern indexes. These correlations show that a reasonable model for land use development and an appropriate development rate will help enhance ecosystem services. The development process should take into account the advantages that different land types can offer so that excessive fragmentation of land type patches can be avoided. (4) A method that uses the CPI index to revise ESV coefficients means that the values more closely reflect the actual ESV and improve multi-period ecosystem service evaluation comparability and accuracy.