Study And Application Of The Residents Trip Survey And Forecast With Remote Sensing Images

The resident trip survey and forecasting plays an important role in the practice oftraffic planning. The survey results contribute to understand and master the law of theurban traffic for planners, and the forecasting can provide basic data demand and controlthreshold. So the resident trip survey and forecast will influence the following planningpractice. But there are some disadvantages under the present trip investigation for catchingthe valid personal travel data, such as heavy work, high cost, and poor efficiency, whichalso embodied in the land use investigation for building forecasting model with land useparameters. All above will decrease efficiency.Planners acquire the development of the city from remote sensing images, because itcan provide plentiful and historical information for planners, and it is widely used indifferent fields meanwhile. New ways are applied to the investigation such as GPS, GIS,Internet, GSM, Bluetooth, and email. This paper will discuss how to investigate, forecastand improve the efficiency with the help from the remote sensing images.In the thesis, the remote sensing images will be treated as the information source ofthe urban land use, which will be used in the investigation and forecasting. It mainlyincludes:1. Picking up the land use information of the traffic zones, and providing basic datafor the next steps.2. Categorizing the traffic zones, combined with the land use parameters, stratifiedsampling method and fuzzy clustering.3. Building the relationships between land use parameters and trip generation by themultiple regression with the results above.Based on the main points, the paper firstly analyzed the research status about theresident trip and remote sensing application from domestic and aboard, and determined theresearch context and method. Then it summarized the characteristics with the survey results,analyzed the influence factors from the aspects of micro and macro, and further explainedthe effects of land use parameters on trips such as FAR, floor area, occupied area andbuilding density. It summarized the characteristics of the urban architecture in the remotesensing images, extract the traffic zones land use parameters with the characteristicsthrough ARC GIS. Then the paper categorized the traffic zones by the fuzzy clustering withthe traffic zones land use parameters, and it got the numbers of categories. At last, it buildthe relationships between the land use parameters and trip generation by the stepwiseregression and partial least square regression models.Through the case studies, it found that the fitted values from the PLSR were better than those from the MLR, and the area of road use, the building density, the constructionarea of public facilities and residential sites were important factors for building theregression model with land use parameters in the area of urban center.