Vegetation Cover Inversion Based On The Experiment Of Remote Sensing

Vegetation plays an important role in the biochemic and water circles. It adjusts the exchange of substance and energy between inside and outside of vegetation. As an index of vegetation flourish degree, Vegetation cover is closely related with soil erosion and desertification. Thus, the retrieval of C by remote sensing can improve the study of global changes and vegetation remote sensing in large scales.The paper focuses on the C retrieval by remote sensing. Based on the known algorithms, a field experimental scheme is designed and accomplished. By the field experiment, the relationship between vegetation index (VI) and C is built, the known retrieval models are evaluated, and the effects of the vegetation structure, imaging conditions of vegetation and soil background are analyzed. The conclusions as follows:The relationship between vegetation index (VI ) and C are discussed and the NDVI is thought as the optimal VI for estimating C. Its precision of estimating C is better during the growth of vegetation; After evaluating the known models for C retrieval, and analyzing the uncertainties of these models, the model is considered as the best; The retrieval of C from MODIS is achieved by the model ;With the growth of vegetation, the effects of leaf area index (LAI) to the relationship between VI and C will be prominent; On the central plane, the infrared reflectivity of vegetation increases with the increase of view zenith angle, and the red reflectivity decreases slightly; On the 'hot spot', the NDVI is minimum, and it will increase around the 'hot spot' with the increase of view azimuth or solar zenith angle; At different vegetation shape and structure, the effects of viewing zenith angle to the C are different; Soil background of vegetation is very important to the C retrieval, especially during the beginning growth with much exposed soil.