Effects Of Vegetation Cover On Soil Erosion Modulus Calculation

Vegetation is the most active and important factor in the terrestrial ecosystems, which effects the ecological climate and hydrology of region, and also play an important role in the degradation of land and the dynamic monitoring of soil erosion. The coverage of vegetation is comprehensive quantitative indicators showing that the condition of the vegetative coverage, it is an important and critical component of the ecological climate, hydrology, soil erosion and other models, and is also an influencing factor. Northeastern Black Soil region is the most valuable resource in Black in our country, and is one of the important bases of the commodity grain. For a long time, the irrational exploitation of land and water resources leads to the thinning of the black soil, to the declining of the land productivity, and to the deteriorating of the ecological environment. The northeast black Land as one of the national soil erosion in key administration areas is enrolled in the dynamic monitoring of the national soil erosion and the implementary plan of the announcement project in order to protect and use the black soil resources effectively and efficiently.This thesis choose Bin locating in the key governance project in Northeast black soil region to discuss, aims to analyze and investigate the affectation of the estimation of the vegetation's coverage to the estimation of soil erosion modulus in different time scales and spatial scales through the coverage of vegetation of the remote sensing quantitative estimation and the quantitative estimation of soil erosion models in different spatial and temporal scales. During the study, the estimated models of vegetation coverage use pixel two-division model and the results of estimating will be inspected basing on the data of the field surveys. The modulus of soil erosion will be estimated by using Universal Soil Loss Equation (USLE). This thesis will analyze the feasibility of the remote sensing of NDVI data on the quantitative estimation of soil erosion in different spatial and temporal scales through comparing the dynamic monitoring of soil erosion in Bin County with the monitoring results of the announcement of the project. And Using MODIS-NDVI remote sensing images with high temporal resolution to construct NDVI long time series data and predicting the spatial distribution and changing trends of vegetation, vegetation coverage and management's factors from 2000 to 2014. The results of researching in this paper are as follows:(1) We can get some information that both the changing trends and the range of values are consistent through analyzing the curve of the seasonal variation about the values of vegetation coverage by measuring in the field and the estimation of vegetation coverage, which indicates that the inversion of MODIS-NDVI about the vegetation coverage is accurate in totally. The inversion of woodland and practical values is closest from July to August; the inversion of farmland is closest to the measured values in August.(2) MODIS data sources estimate the value of the vegetation coverage is higher than the estimation of LANDSAT data sources slightly. The area being covered by the type of grass, the inversion of the MODIS about the value of vegetation coverage less than the value of inversed by LANDSAT; in the agricultural land, the value of vegetation coverage from MODIS higher than value of the inversion in LANDSAT; and in the waters, the facilities of irrigation and urban land use type area, the inversion of vegetation coverage from MODIS are much higher than the value of inversion in LANDSAT, which has a wide gap.(3) Under the inversion of vegetation coverage in MODIS, there is a little difference between the value of the inversion and the practical value in August; we can consider the vegetation coverage in August to replace the vegetation coverage in the whole year. The vegetation coverage is middle and high in Bin County.(4) The values of C are varied distinctly in the overall types of land based on the estimation of vegetation coverage in MODIS and LANDSAT:forest grass<farmland <Towns<Waters and the facilities of irrigation. The result is appropriate to the features of Factor C in the distribution of actual space. Deriving the data of formulas between the studying area NDVI and Factor C according to the estimated value of C, this is adaptive by testing.(5) the classification chart of the intensity about soil erosion shows that results of erosion in MODIS-months is significantly less than the other calculated values and monitored values, the data about the result of erosion in the plain area in Bin MODIS season, year and LANDSAT is significantly less than the monitoring value calculated. MODIS data sources in different time scales calculate soil erosion area in Bin County having certain rules:Monthly<Quarter<Year, the quarter is close to the year. The classification of soil erosion shows:very strong grade<strong<severe<medium<mild, soil erosion in Bin is mild and medium mainly. The acreage of the modulus of soil erosion counted by the data of 30m resolution is larger than the total area of erosion calculated according to 250m spatial resolution, from the classification of erosion area to see, other grades have a little difference in addition to the obvious difference among the mild erosion area. Eroded area counted by LANDSAT is close the monitoring results. From the view of the total amount of erosion and the modulus of average erosion, the results from MODIS, LANDS AT is half of the monitoring values, there is a difference between the results calculated by MODIS, LANDSAT and the monitoring values.(6) Estimating the time in series in Bin 15a MODIS-NDVI from 2000 to 2014, the analysis shows that the variation trend of the biggest NDVI in vegetation is increasing in Bin 15a, the vegetation coverage is improved; the coefficient of the whole spatial variation is small, the most amount of area is under 0.1 except town, large area of waters. The area where the changing values of Factor C is decreasing accounts for 46.89%; the area where the changing values of Factor C is increasing accounts for 39.84% among 15a.