Study On The Relation Of Soil Thickness Spatial Distribution And Grassland Degradation Based On 3S

In recent years, the deteriorating ecological environment of grassland poses a great ecological security threats in northern China, and grassland degradated is the major environmenttal problems at home and abroad. The paper selected the Xiwuzhumuqin county grassland as the study area, monitored and classified the extent of degradated grassland by using the CBERS satellite data. Through the GIS, GPS technology and geostatistics methods, the Ordinary Kriging interpolation methods was adopted for processing the soil thickness test data, and the prediction map was produced which is the soil thickness spatial distribution to the study area. The research evaluated the degenerative grassland level by spatial overlay analyzing between the Remote Sensing data of degenerative grassland and soil thickness spatial distribution, and founded the analytical methods of the relation between the degradative grassland and soil thickness, ascertained the location and size of the different degradation levels at the grassland study area.This will offer the basic data for constituting the ecological environment protection strategy on the scientific management of grassland and the natural restore of degradative vegetation, and provides the technical support for the nation to formulate and implement sand sources control project.Main results and conclusions from the research are as follows:1.Through processing 277 samples of the soil thickness pre-test data and error analyzing, the results show that the kriging interpolation method is obviously better than the inverse distance weighted interpolation. So the Kriging interpolation method is selected test data interpolation. At the same time, the rearch ascertains the selecting principle of the reasonable distance between sample points in the soil thickness test. namely:To the flat region,the reasonable distance of the grassland soil test samples can be properly adjusted from the theoretic19.5m to 200m, the local area can even zoom into 500m. But hilly region, according to the complexity of the topography, the reasonable distance of the grassland soil test samples can be appropriately selected 19.5m ~ 60m, the largest do not exceed 100m.2.Dealing with 500 samples data of the soil thickness elicits the results: The data is closer to normal distribution and symmetry. The histogram shows a single peak. The data average is roughly equal with its median in value. QQ figure reconfirms that the soil thickness test data is subject to the normal distribution. So there is no need for data transformation. After extraction of the trend, the soil thickness test data shows a certain trend which can use the second-order polynomial of southwest-northeast to the best fit for its trend. The semivariogram/ covariance cloud figure shows that the soil thickness test data have the spatial autocorrelation. Because there is no data or erroneous outliers sampling points, the Ordinary Kriging interpolation can be used to create more precise soil surface.3 . Analyzing the different semi-variogram model fitting interpolation error: adopting the rational qadratic model as a semi-variance model, obtains that the mean value of the prediction is 0.012, the root-mean-square value is 7.384, the average standard deviation value is 7.426, the mean standardized value is 0.001. The property are minimum their respective. The root-mean-square standardized value is 0.987. Hence, the rational quadratic model is the best semi-variance fitting model to the soil thickness data.4.The research, comparatively analyzes the different degenerative vegetation level to grassland and the remote sensing image of the corresponding position, determines the region of interest of the different degenerative vegetation levels implements the supervised classification of the different degenerative vegetation level by ERDAS IMAGINE 8.6. Through the classification error matrix evaluation template, the classification accuracy evaluation and the field verification, receives the classification accuracy which are90.00%, 89.74% and 87.50% , kappa coefficients are 0.88, 0.88 and 0.86 on the degenerative vegetation level to grassland in 2006 ~ 2008.5.According to comparative analysis of statistical data on the average three years from 2006 to 2008,in the grassland soil thickness less than 10 cm of the study area, the moderate and severe degradation area are respectively 44.9% and 48.2% of the total area. The study area where is soil thickness of 10 ~ 20 cm, the grassland area of moderate degradation accounts for 70.3% of the total area. In the grassland soil thickness of 20 ~ 30cm of the study area, the area of moderate degradation grassland is the total area of 64.8 %. In grassland soil is greater than the thickness of 30 cm within the study area, the area of undegradation and moderate degradation grassland are respectively 32.8% and 53.3% of the total area.