| In the past ten years, the traffic network as the basis for city construction, has achieved a great development in our city construction,especially in the construction of the metropolis and the city group in the process, the scale of investment and construction of road mileage were greatly increased in 11 th Five Year, during the 12 th Five Year Plan period.However, the economic development of vehicle ownership is also stimulated rapid growth, there has been open year-round, such as traffic jams and road traffic rare phenomenon, roads and uneven distribution of supply and demand is becoming more prominent. To carry out the reasonable urban road network evaluation(urban agglomeration), the planning and construction of guiding network science is one of the effective measures to solve this contradiction. High resolution remote sensing images with a large amount of information, high degree of visualization, observation scope, for a wide range of urban road network technology(urban agglomeration) evaluation provides a reliable source of data.Therefore, this paper in 2012 the Ministry of transport under the support of key projects, mainly carried out the following research work:(1)First, the current urban road network construction problems were analyzed, discussed the background and significance of the research,reviewed the status of technology research, a clear research content and key issues, develop research ideas to form the full text of the research program.(2)Combing the existing road construction evaluation, from the road distribution, supply and demand, economic efficiency point of view,the establishment of 11 secondary indicators covering road network density, grade level with the road network, such as per capita GDP,formed a set of comprehensive evaluation index system of urban road network based on high-resolution remote sensing image.(3)The extraction of road width, length and other information, is the key and difficulty of developing network evalution. First, high image grayscale image processing and equalization, using median filteringdenoising, realizing the road target enhancement preprocessing. To maximum variance threshold automatically Canny operator to realize the image edge detection, on this basis, with the structure of the adaptive threshold element images achieved high marks at the beginning of extraction of road network. To take advantage of differences in straight and curved road characteristics, vector images after segmentation using template matching, object-oriented classification reprocessing of the bend,straight implements Quick Bird0.61 m road image vector information extraction. Then calculate and statistics road vector information which road length and lane, by experimental verification, path length parameter extraction accuracy reached 87.5%, and provide basic data for the next step of road network evaluation.(4)According to the road grade classification standard, the high resolution remote sensing image width road transformation, the road width, length(mileage), grades and other information into the comprehensive evaluation index system of the traffic network, the establishment of two level fuzzy comprehensive evaluation model of road network evaluation. In this regard, with Shen-guan-hui urban agglomeration, launched a road network and road network density evolution of directional evolution empirical score based on urban agglomeration road network of remote sensing images.(5)Using Arc GIS Engine, VS2008 platform, C++ language, the information extraction module, information display module, network evolution information evaluation modules are integrated, and constructs a set of urban agglomeration network evolution information evaluation system based on HRRS and GIS. |
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