Quantitative Inversion Research Of Road Vegetation Chlorophyll By Using Multispectral Remote Sensing

The leap forward development of expressway construction, have brought great convenience to human life, and promote the rapid development of regional economy, But at the same time, the expressway construction and operation has brought great negative impact to the road vegetation and human environment. During the time of road building, The occupation and destruction of farmland and woodland. In the operation process due to atmospheric pollution caused by cars, water pollution and noise pollution, making the roadside vegetation atrophy or dead and the scope of activities for animals is limited. In our country, the ecological environment of road is facing with a severe threat.The trend of roadside vegetation leaf chlorophyll content can visually reflect the changes of vegetation environment in the road area. At present, the research on the field vegetation chlorophyll is less in domestic and foreign. Because of this situation, this article take a section of highway as the research subject, and this section of highway belongs to Ping-Ru highway(from Liuyang to Liling), Hunan Province. using the ETM+ image as the data source, this article conducted a study on the quantitative inversion of the chlorophyll in road area by using empirical model and Model PRO4 SAIL separately. The contents and achievements of this study as follows:1.In Model PRO4 SAIL, firstly hold the other parameters, input different degrees of chlorophyll content, this model can simulate different spectral reflectance of vegetation. The analysis of the reflectance curve showed that, the chlorophyll is sensitive to blue, green, red band, and with the increase of the content of chlorophyll three band reflectance decreases.2. Before and after first-order differential or second-order differential of the spectral, this article analyzed the relationship between the spectral and the chlorophyll content, and analyzed the relationship between the vegetation index and the chlorophyll content. The result of these analysis showed that the treated spectral and the treated vegetation index had more relevance with the chlorophyll content than the untreated.3. Using the model of PRO4 SAIL to simulate vegetation spectral reflectance, constructed a lookup table of chlorophyll; then according to the data of lookup table inversion of the vegetation chlorophyll, and found that the result of inversion was similar to the real with a 0.8617 correlation coefficient.4. Separately analyzed the relevance between the chlorophyll content and five kinds of vegetation index in the ETM+ images, these five kinds of vegetation index included NDVI, GRVI, DVI, RVI and GNDVI. The result of analysis showed that NDVI, GRVI and GNDVI had a strong correlation with the chlorophyll content, and that inversed the chlorophyll content by using these three vegetation index could get the correlation coefficients above 0.7.5. After compared the results of inversing the chlorophyll content, this article found that the change and location of the inversed chlorophyll converged in the same tendency whether using the empirical model or using Model PRO4 SAIL.thus confirming the use of multi-spectral remote sensing to inverse the chlorophyll content has practical feasibility.