程序代写代做代考 graph database Land use change in Inner London in the past 30 years

Land use change in Inner London in the past 30 years
Abstract: The process of land use change is very complex, which is one of the most significant aspects of global environmental change. With the rapid development of social economy and the advancement of urbanization, the rational use of land resources is very important. However, there are multi-source and multi-scale land use in the region, which to a certain extent makes the data form an “information island”, and it is quite difficult to build and share data, which causes the repeated construction and production of data, and even causes a huge waste of social human and material resources. Under the current management mode, the business data of each department is mostly stored and managed by different GIS platforms and different database management systems. How to integrate all kinds of multi-source and heterogeneous geospatial data under the unified data standard, so as to quickly realize the co construction and sharing of all types of data, and meet the requirements of centralized management and distributed application of achievement data Demand is the key technical problem that must be solved. This study takes the land-use change of London in the past 30 years as an example, using GIS and land-use change analysis to elaborate the land-use change in London, grasp the essential characteristics of urban growth and development, and make contributions to the future urban development.
Keywords: land use changes; database management systems; GIS

Introduction
Urban land use form is the projection of human urban settlement behavior in space and the accumulation of urban construction over time. Urbanization is one of the main driving forces of land use change in metropolitan areas of developing countries. With the expansion of urban scale, many unique social economic and ecological problems have emerged, such as traffic congestion, environmental pollution and housing shortage (Alig R J et al.,2004). As more and more residents seek better housing conditions and more living space, these problems stimulate land demand through the reconstruction of the city center, suburbanization and urban expansion. The integration of land use data is to organize all kinds of scattered land use data and resources (GIS, RS etc.) according to certain data standards, management rules and service purposes through certain technical methods and means, so as to make them coordinate with each other and realize data sharing and value-added. In this paper, through the study of land use patterns in Inner London, we explore the ways to expand urbanization patterns, reduce the shortage of land resources, and hope to grasp the essential characteristics of urban growth and development through the phenomenon.
Analysis and target setting of land use database in Inner London
Land use data status is the basic geographic information results formed under the unified national land survey. The results can comprehensively reflect the characteristics, scope and distribution of regional land use elements in a certain period. Its formation has mainly gone through three stages: the first detailed land survey, the second national land survey, and the third National land survey currently being carried out Land investigation. The span of each stage is about ten years. During this period, the results of the annual land change survey are updated incrementally at the end of each year to maintain a good current situation. As the current situation of land use can better express the characteristics of land use related elements, and as the basic survey data, its results have become one of the indispensable important data in the management of natural resources, and provide important basic data services for the national economic and social development. This chapter is mainly about the overall evaluation and analysis of the existing land use database of 12 urban areas in London (Hardy D et al.,1991). First, the data source is briefly described. Secondly, taking Arc GIS as the platform and using Map GIS K9 and other software synthetically, the land use data experiments of 12 urban areas in London were completed. Finally, the principle and objective of the experiment are put forward according to the actual situation.
Illustration of urban land use patterns in Inner London
The main contents of the diagram include the spatial distribution of construction land, road network and rail transit. The information of construction land, green land and road is extracted by manual interpretation of satellite image. With the geometric center of the city as the center and 25 kilometers as the interval, the ring is divided to make comparative analysis of the urban built-up areas. The ring is recorded as D25, D50, d75, D100 The statistical contents include the proportion of urban and rural construction land in the ring road, the density of trunk road network, etc. Among them, the road statistical analysis is mainly divided into three levels: high-speed road, the main principle of which is continuous driving of high-speed road and urban ring road not limited by traffic lights and intersections; first level road, the main road connecting regional towns and urban main road excluding the ring road; second level road, other main roads in the region and urban built-up areas. Taking London as an example (Gallent N et al.,2006), high-speed roads, including expressways and urban expressway, are classified as m and R; class I roads, including national roads, provincial roads and expressways, are classified as class a 1-digit and 2-digit class roads in the UK (Levinson D et al.,2008); class II roads, including city and county roads and other urban trunk roads, are classified as class roads in London. This chapter mainly analyzes the spatial distribution of construction land, road network and rail transit of 12 cities in London, classifies and expounds the land use situation of urban and rural areas in London, and evaluates the land use situation by combining historical information and experience.
Analysis of social and economic benefits of land use
The social benefits of land use refer to the arrangement, use and optimization of urban land in terms of quantity, quality, space and time, while the total ecological, economic and social benefits brought to the whole city are different in the degree of realization of economic, social and ecological benefits in different time and region. The benefit reflects the degree of resource allocation, which can show the resources. The realization degree of labor value and capital investment. In this sense, the higher the benefit of land use is, the more reasonable the allocation of land resources is, and the higher the value of land resources has been achieved, that is, the higher the level of intensive use of land resources. Based on the analysis of the connotation of urban land use efficiency, this chapter constructs the evaluation index system and coordination analysis model of land use efficiency from three aspects of social efficiency, economic efficiency and ecological efficiency, and takes 12 urban areas in Inner London as an example (Lowe et al.,2002). The efficiency indexes selected in this study mainly include urban land structure indexes (per capita land area, per capita land for various industries) Area(Amati M et al.,2006), per capita green space area), green space index (per capita green space area, green space rate and green area coverage rate of built-up area), economic index (per capita gross income, output value, output value and gross commodity output value, output and per capita tax paid, profit amount) and social environment condition (cultural education level, consumption level of residents, urbanization process, etc.).
Conclusion
The social, economic and ecological indexes closely related to urban land use efficiency are selected, and the evaluation index system of urban land use efficiency is established. The weight of each index is determined by improving entropy method, and the land use efficiency of 12 urban areas in Inner London is compared by using coordination model.
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