Research And Analysis On Relationship Between The Sloping Land Conversion Program And Improvement Of Ecological Environment

With the rapid development of digital informationization, huge volumes of data have been accumulated in fields of hydrology and meteorology. The accumulated data conveys rich information important to us. How to extract and make the most of the information has been an important issue for researchers. This paper took advantage of the method of time series data mining and regression analysis to analyze the relationship between the conversion of farmland to forest and the improvement of the ecological environment. The results show that it has practical significance to improve the ecological environment.Firstly, modeling was accomplished on the dynamic data of average monthly rainfall sourced from LuoChuan by the use of the auto-regressive integrated moving average(ARIMA) model. Based on the built precipitation model, fitting and prediction of the precipitation was conducted. However, since the precipitation data contains information of both inter-annual monthly variation and inter- monthly annual variation, the original auto-regressive integrated moving average(ARIMA) model, which neglects the influence of inter- monthly annual variation, can’t accurately predict precipitation. To achieve better prediction, clustering analysis of average monthly precipitation was made to extract and classify characteristic values of each month. A regression equation was made between the characteristic value and the corresponding average monthly precipitation by the use of regression analysis. Then a improved ARIMA model was built to predict characteristic values which then were interpolated into the regression equation to obtain the predicted precipitation data of every month.Secondly, a brief comparison was made between the auto-regressive integrated moving average(ARIMA) model and the improved ARIMA model. A conclusion was drawn that the improved ARIMA model co uld performs much better because the improved model takes both interannual variation and inter- monthly variation into consideration, thus preferably focusing on the characteristics of the data.Finally, a regression mode was established between the relevant data of the Sloping Land Conversion Program during 1999-2013 and amount of precipitation. The regression mode was further processed and studied to analyze the influence t he Sloping Land Conversion Program had on the amount of precipitation and local air temperature, And it plays an active role in improving the ecological environment.