Study On Estimated Methods Of Building FAR Of Shanghai Central Urban Area Based On QB Satellite Image

Nowadays, surveying the status of urban construction is becoming an important task of urban developing and planning. Among a great deal of urban spatial information, building FAR(Floor Area Ratio) is one of the most important, it is the basis of urban spatial environment evaluation, urban planning, layout and developing potential.Many people have found some methods to measure FAR based on RS and GIS. But up-to-date, nobody has measured building FAR of a whole big city because of the building's complexity and the enormous data. Along with the rapid development of aeronautics and sensor, there is a great progress about satellite image's resolution. Currently it is a research hotpot of GIS to distinguish and detect city's all kings of information from RS images. AS QuickBird images being data source and Shanghai central urban area being the region of test, this study analyzes building's styles and QuickBird images' characters of Shanghai central urban area, then make correspond methods to estimate building FAR of different building types based on the characters of various building. Among these, because building shade and building height have a linear relation, the author construct a relation model between building shade area and building sum area to estimate multi-storey building's FAR, and construct a relation model between building shade length and building height to estimate high-rise building's FAR. By checking the result, we draw a conclusion that these methods can estimate rapidly the building's FAR and the precision is very high.There are six chapters in this thesis. The first chapter is Introduction, which illustrates the background of the subject, purpose of the research, the actuality and trends in the world, the main technology route of my own research; The second chapter is Introduction of RS Image, which introduces the development history of RS image especially the QuickBird satellite image. Then analyzes the character of QB images of Shanghai central urban area; The third chapter is Detecting of Vector Data, which shows the manual vectorization to detect the information we need in ArcMap software, another, building shade is been auto-detected in PhotoShop software and been auto-vectored in ArcMap software; The fourth chapter is Estimation of Building FAR, which analyzes the character of various building, makes different methods to detect building FAR of various building, at last detects the building FAR of the whole urban area of Shanghai as block being detective unit; The fifth chapter is Checking of Precision, which analyzes the estimated precision by contrasting the FAR value...