The Study Of The Normalized Vegetation Index & Meteorological Factor Change Tendency In Growth Season, On The North Slope Of Tianshan Mountain

In the Study region, by using multi-year-climate material of the north slope of the Tianshan Mountain, This article has analyzed the changing rules of season surface vegetation growth in the past 5 years and predicts the growth rules in the coming years, On the basis of calculating correlation between the vegetation index dynamic change and the meteorological factor change in the north slope of the Tianshan. The article has analyzed the dynamic change influence actuation types of the precipitation, the temperature and the vegetation index, and spatial distribution characteristics.Main conclusions are obtained as a method, two models and a premise.1,A method, which has been used to monitor the north Tianshan's slope surface vegetation growing trend for 5 years.The vegetation's growing trend does not have the obvious linear variation tendency. Regarding the vegetation growing trend computation, this article uses the method through the type spot fitting slope. Using the GIS software, this method has the function which may raise the sampling point and the type lights the Z direction value, and get rid of the big operand mathematical model. The calculated DAT data, with this method, can produce grid data directly in the RS software; avoid kinds of space calculus of interpolation method by increasing the operation result precision.Demonstrated from the statistical result, the 5 years' vegetation growth trend is better then the previous 8 years' trend, but the north slope of the Tianshan oasis had the varying degree, the high proportion, the big area degeneration, and only the lower range vegetation may improve. The vegetation's growing trend displays the partial worsening and the overall improvement characteristics.2, two models, these are the short-term forecast BP network model and the Verhulst model.The combination of BP&V (the Verhulst model) forecasts the changed trend of the surface vegetation. The method's basis:1' In the 5 years, the north slope of Tianshan's climatic change displays obvious cold & wet characteristics.2' In short time series, the climatic factors (precipitation, temperature) has the obvious linear variation characteristics, therefore the forecast theory core, using the gray forecast the system the Verhulst model, can forecast the future (1-2 years) temperature (precipitation) change, Then, the operation of artificial neural networks (BP model) obtains the vegetation index anticipated change situation in the north slope of Tianshan.Through the statistic of 200 marks, 2005 minimum forecast temperature increase is 0.064, and average increase is 0.032. The comprehensive succession analysis, the research area temperature will appear changes the warm tendency.The comprehensive climate forecast the situation, the climate of the north slope of Tianshan is occupying a climate cold wet change time.In coming several years, taking 05-06 years' forecast as the basis, the research area mountain belt forest land, the lawn degenerated tendency intensify, and to oasis belt expansion.The increase tendency of oasis and wilderness vegetation index is stable, but in the oasis local area, the surface vegetation appears the degenerated phenomenon.3, this article monitor method and the forecast model all are based on a premise.In the past 5 years, we have recognized that the response correlation between the climatic factors and the vegetation factors are stable in the slope of north Tianshan.Through the correlation examination, these response relations are basically credible.