| Humans live in a compound earth system where people interact with the natural environment.Land is the source of survival for all terrestrial creatures and a space for human existence.The Yellow River is the mother river of the Chinese nation,and the Yellow River Basin constitutes an important ecological barrier in China.Therefore,this study used eights cities along Yellow River,Henan province as a research area to explore the changes in land use and ecosystem service value.This study can provide a reference basis for the realization of the systematic management of the mountains-rivers-forests-farmlands-lakes-grasslands life community.The basic data used in the research was a total of five phases of land use data from 1995 to 2015.It mainly analyzed the changes in land quantity,structural changes,and changes in land utilization rate in the study area.This study also assessed the spatial and temporal changes of regional ecological service value.During the analysis process,with the help of SPSS mathematical statistics tools and Logistic regression model,10 driving factors that make important contributions to land use change in this study area were selected for spatial driving force analysis.The Geosos-flus model was used to simulate natural development scenarios,sustainable development scenarios,and economic development scenarios to realize the spatial pattern of land use/cover types in the study area in 2025.This study also analyzed the ecological service value and its spatial distribution in the study area in 2025.The results showed that:(1)The land use / cover types in the study area showed a strong temporal and spatial differentiation.Cultivated land and forest land are the main types of utilization in this area.During the 20 years from 1995 to 2015,the cultivated land area has been decreasing,and the forest land area has increased after a period of decreasing.During the study period,various types of transformations were intense,and most of them were converted into cultivated land and forest land,indicating that the transformation during the study period was mainly affected by agricultural and forestry development activities.(2)There have been some changes in the landscape pattern of the study area during the 20 years from 1995 to 2015.The fragmentation of regional landscapes has been declining and transforming into coarse-grained landscapes,indicating that with the development of urbanization,the spatial connectivity of the landscape in the study area has been strengthened and the landscape layout has been concentrated.(3)According to the results of the logistic regression model to explore the driving force of land use change,according to the results of the model regression coefficients,it can be seen that the different influencing factors among the six land types in the study area are mutually influential and related.Among the three influencing factors,the elevation,slope and surface fluctuation of natural factors are the main driving forces affecting land use change,and they are important factors that determine the formation and evolution of the land use spatial pattern in the study area.(4)The total value of ecosystem services declined in the study area from 1995 to 2010.The reason is that the increase in construction land area has had a negative impact on ecosystem services.The slight increase in forest area during 2010-2015 had a positive impact on the value of ecosystem services,increasing its total value.(5)The Kappa coefficient of the Geosos-flus model is 0.8761,indicating that the model has good predictive ability.The grassland with the largest land-use change rate simulated by the model from 2015 to 2025 had the largest decrease in grassland in the natural development state;construction land followed,and the largest increase in economic development.The total value of ecosystem services of different development models in the study area is: sustainable development is the first,natural development is the second,and economic development is the smallest,the third.Among the three modes,cultivated land and forest land contributed the most to the ecosystem service value. |
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