City edge region extraction method based on multi-source data fusion

Abstract

The invention discloses a city edge region extraction method based on multi-source data fusion, and the method comprises the steps: selecting a plurality of pieces of city edge feature data as data sources, and respectively determining a city edge region recognition index factor of each piece of city edge feature data; after data standardization processing is carried out on the urban edge area identification index factors, calculating index values and index weights of the urban edge area identification index factors, and obtaining urbanization characteristic values through calculation of the index values and the index weights; performing urban edge area mutation point identification and extraction according to the urbanization feature value to obtain an urban edge area mutation point cluster; performing spatial position and attribute feature clustering on urban edge area mutation point clusters, performing inner and outer boundary extraction on each clustering cluster, and obtaining urban edge area boundaries. By the adoption of the city edge area extraction method based on multi-source data fusion, automatic extraction of the boundary of the city edge area is achieved, and the boundary recognition precision of the edge area is improved.

Description

technical field [0001] The invention relates to the technical field of urban planning, in particular to a method for extracting urban fringe areas based on multi-source data fusion. Background technique [0002] The urban fringe area is located in the transition zone between the city and the countryside. It is the frontier of urban expansion and the most dynamic area in urban-rural construction and land replacement. Accurate identification of urban fringe areas helps to measure the degree of urbanization and its impact on the ecological environment from the perspective of urban-rural comparison. The land use simulation has important practical significance. [0003] The spatial extent of the urban fringe area was determined qualitatively in the early days, and it is more common to divide it by the distance from the central city. With the rapid development of remote sensing and GIS, the research on identifying the spatial extent of the urban fringe area by quantitative means ...

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Problems solved by technology

[0007] 2. The existing boundary recognition and extraction methods have limitations in the recognition of urban fringe areas

The above methods, the comprehensive analysis method and the threshold method are highly subjective, while the mutation detection method mainly includes two aspects: First, when calculating the mutation point, the two locations with the largest mutation are usually taken as the inner and outer parts of the urban fringe area. The boundary conforms to the idealized "urban built-up area-urban fringe area-rural hinterland" in the form of "concentric circles" of development, but the reality is that due to the impact of construction and development intensity and population agglomeration, the urban fringe area is not closed The ring shape brings the uncertainty of the number of mutation points; second, after identifying the mutation point, it usually directly connects the adjacent mutation points manually according to the principle of proximity to obtain the boundary, resulting in inaccurate boundary results, taking into account space and attributes There are fewer methods for automatically extracting boundaries from

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