Construction method of total urban night light quantity-urban population regression model

A regression model and construction method technology, applied in the application field of remote sensing socio-economic geology, can solve the problems of unfiltered background noise and unremoved firelight, etc., to achieve the effect of filtering background noise

Inactive Publication Date: 2018-11-13
HOHAI UNIV
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However, the product does not remove fire lights, gas burns, volcan

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  • Construction method of total urban night light quantity-urban population regression model
  • Construction method of total urban night light quantity-urban population regression model
  • Construction method of total urban night light quantity-urban population regression model

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Embodiment Construction

[0038] The present invention will be further described below in conjunction with the accompanying drawings.

[0039] Such as figure 1 As shown, a kind of urban luminous total amount of the present invention-the construction method of urban population regression model comprises the following steps:

[0040] (1) Summarize the urban population statistics data of prefecture-level cities across the country in 2016, select the urban population data of 30 prefecture-level cities as model training samples to construct the urban luminous total-urban population regression model, and then select another 30 prefecture-level cities The urban population data of the city is used as a model test sample to verify the rationality of the model;

[0041] (2) Download the Landsat-8 image with low cloud cover in 2016 from the geospatial data cloud website (the cloud cover is required to be less than 8%), and perform preprocessing to obtain the Landsat-8 preprocessed image;

[0042] (3) Download the...

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Abstract

The invention discloses a construction method of a total urban night light quantity-urban population regression model. The method includes: carrying out collection and screening of counting data of urban population of all prefecture-level cities, and determining training samples and test samples; preprocessing Landsat-8 remote-sensing images, and obtaining vector graphs of built-up areas of the training samples and the test samples through classification of support vector machines (SVMs) and clustering processing after classification; using the vector graphs of the built-up areas and a threshold method to eliminate background noises of NPP/VIIRS images, and calculating TNL (Total of Nighttime Light); and establishing the regression model for correlation analysis of total urban night lightquantity and urban population of the training samples, and making rational evaluation on the model. According to the method, on the one hand, multiple data sources are fused on an aspect of NPP-VIIRS(National Polar-orbiting Partnership/VisibleInfrared Imaging Radiaometer Suite) image denoising, and on the other hand, real-time performance and objectivity of the remote-sensing images are fully utilized, spatial distribution of urban population is reflected, and the method has important significance for prediction and evaluation of urban population data.

Description

technical field [0001] The invention belongs to the technical field of remote sensing socio-economic geography application, and in particular relates to a method for constructing a regression model of total urban night light-urban population. Background technique [0002] Population is an important factor in urban development. Scientific and effective population management is of great significance for improving the quality of the city and for the government to formulate development policies reasonably. In recent years, the pace of urbanization in China has accelerated, and a large number of people have flooded into cities. However, the continuous growth of urban population also makes the contradiction among urban population, resources and environment more and more prominent, seriously affecting the sustainable development of cities. The existing population data mainly come from the population registration data of the public security department or the census data. The update...

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Application Information

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IPC IPC(8): G06F17/18G06K9/62G06K9/54
CPCG06F17/18G06V10/20G06F18/2411
Inventor 陈嘉琪张燕魏昊陈西杰平学伟胡居荣刘海韵
Owner HOHAI UNIV
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