Estimation of Vegetation Fraction in the Upper Basin of Miyun Reservoir by Remote Sensing

Vegetation fraction is a most important index to score the vegetation coverage on the land surface. As one of the input parameters of soil loss equation for soil erosion assessment, it needs to be estimated quantificationally in regional scale. Based on the analysis of the current methods of measuring vegetation fraction (fc), this paper has developed the dimidiate pixel model for quantifying vegetation fraction from normalized difference vegetation index (NDVI=[NIR-R]/[NIR + R]), which is derive from the near red band and red band of the remotely sensed data. In the improved model, fc is calculated by the formula:fc = (NDVI-NDVIsoil)/(NDVIveg-NDVIsoil)where NDVIsoil and NDVIveg are two input parameters of the improved model, and they represent the NDVI value of pure pixel of barren soil and vegetation, respectively. According to two cases of practical requirement, the improved model gives the deducing process of such two parameters with the ancillary data of vegetation map and soil map. Then based on the division units extracted by overlaying the land cover database and soil type database, two vegetation fraction data sets in the Upper Basin of Miyun Reservoir have been estimated for each division unit from NDVI derived from Landsat TM data in spring and summer. Through validating with field-investigated data, which is obtained by calculating the vegetative proportion on the digital photography of each land cover, the average estimated accuracy of vegetation fraction of all land cover types is more than 85% in the study region. So the fc datasets are valid, and can be taken as one of the parameters to derive the soil loss volume. The result also suggests that it is feasible to use this improved model to estimate vegetation fraction from remotely sensing data.