Quantitative Inversion And Analysis Of Highway Roadside Vegetation Ecological Correlation Factors Based On Remote Sensing

With rapid development of highway construction, the road ecological problem has gradually appeared. How to coordinate the sustainable development of economy, society and ecological environment as well as the growth of green transport are the emphasis scholars of all walks of life. Value the protection and optimization of ecological environment, while focusing on economic development and exploiting ecological resources.Vegetation plays an important role in the ecological environment; its living condition is disturbed by road construction, which has indirectly damaged the atmospheric environment and the soil environment. Thus explore the influence of road construction and operation on road vegetation ecological environment possesses important practical value for monitoring and assessing road ecological environment. This paper takes Chang-Tan section of Jing-Gang Express as subject, three representative vegetation ecological correlation factors (land use/cover variance, leaf area index, vegetation coverage) have been selected to proceed remote sensing inversion and analysis by using remote sensing image source in different scales.Land use/cover variance has become the central issue in the search of global environmental change. Vegetation is the most important part of land cover; land use variance has direct impact on survival of vegetation and environment change within the area. Research shows that the agricultural land along the road decreased and construction land increased as the construction of road; but forest land which suffered a reduction at preliminary stage of road construction would show an upward trend with the self-restoration of natural ecosystem. Environment problem is more obvious and land use variance increasing greatly in relatively developed area.Quantitative remote sensing inversion model has always been the hot topic in remote sensing research field. In research of this paper, empirical model and physical model are employed to inverse the leaf area index respectively, with exploration of quantitative remote sensing analysis method and adoption of vegetation environment correlative factors to reflect the quality of road area ecosystem, which providing a powerful technique to explore the impact and its complexity of road construction and operation on natural environment. Analysis the results and accuracies of both remote sensing interpretation method to inverse the road vegetation leaf area index by using the high resolution IKONOS images, developing an inversion method of vegetation leaf area index which is applicable to road ecosystem this particular ecoregion. According to research, physical model with greater precision showed more universality and applicability to inversion of road vegetation leaf area index than empirical model.The interfering process and intensity of road construction and operation on roadsides ecosystem can be recreated by analyzing the inversion of road vegetation coverage and time-space variable features. The results show that the main driving factor is the economic benefits from road operation, the environment factor comes second; which is in accordance with the actual area economic development.