Regional population density simulation method based on feature vector space filter value

Abstract

A regional population density simulation method based on a feature vector space filtering value comprises the steps of obtaining a regional vector file and statistical data, selecting a feature vectorspace filtering value method, and selecting an auxiliary independent variable by taking regional night light average brightness as an independent variable; processing the remote sensing night light image according to the region vector file, and calculating region total brightness and average brightness; establishing an adjacency relation, obtaining a spatial adjacency matrix, centralizing the spatial adjacency matrix, and calculating a matrix characteristic value and a characteristic vector; and extracting a proper feature vector as a spatial influence factor of luminous brightness, adding the feature vector into an independent variable, solving a regression coefficient, obtaining a feature vector spatial filtering regression model of the population density, and realizing regional population density simulation according to the model. According to the method, the influence of spatial heterogeneity and spatial autocorrelation on population density distribution can be effectively eliminated, manual statistics is replaced by an automatic means, manpower and material resources are saved, and the method has important significance for urbanization intelligent monitoring, environmental pollution detection and other applications.

Description

technical field [0001] The invention belongs to the technical field of spatial statistical analysis service application, uses night light images as materials, and particularly relates to a method for simulating population density of a region (city level) based on a feature vector spatial filter value. Background technique [0002] Night light refers to the dazzling light emitted by human settlements and economic zones when observing the cloudless earth at night from space, and its source is mainly the popularity of lighting facilities. Due to the unique charm of night-light remote sensing images, Google Earth has included light images as one of the image layers. Scientists can conduct data mining on these images to discover social or natural laws. Compared with ordinary remote sensing satellite images, nighttime light remote sensing images can reflect more human activities, which makes them widely used in the fields of social sciences and natural sciences. [0003] A large...

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Problems solved by technology

[0008] In order to solve the shortcomings of complex population statistics, long process, long cycle, and inability to obtain quickly, as well as difficult statistics in remote areas and incomplete statistical data, the present invention uses night lights as materials, and uses the feature function spatial filtering method to analyze the regional population density. conduct a simulation

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