發(fā)布時(shí)間：2018-04-19 20:25

  本文選題：夜間燈光數(shù)據(jù) + 常住人口��； 參考：《地球信息科學(xué)學(xué)報(bào)》2017年10期

【摘要】：精確掌握常住人口的數(shù)量和分布特征有助于明確社會(huì)發(fā)展情況、提高人口管理能力。目前人口數(shù)據(jù)主要以行政區(qū)為單元統(tǒng)計(jì),難以表現(xiàn)城市內(nèi)部的人口分布特征。然而,在城市中,受道路、公共服務(wù)設(shè)施、城市亮化燈光的影響,利用夜間燈光數(shù)據(jù)對(duì)人口回歸,精度降低。如何提高城市常住人口回歸結(jié)果的精度,值得深入研究。上海是中國(guó)的國(guó)家中心城市之一,在快速城鎮(zhèn)化進(jìn)程中上海面臨巨大人口壓力。因此,本文以上海市為研究區(qū),以NPP-VIIRS(National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite)夜間燈光數(shù)據(jù)、鄉(xiāng)鎮(zhèn)級(jí)常住人口統(tǒng)計(jì)數(shù)據(jù)為基礎(chǔ),提取商業(yè)和居住區(qū)的燈光數(shù)據(jù)來(lái)緩解交通、城市亮化區(qū)的影響,提高燈光累計(jì)值與常住人口數(shù)的相關(guān)性(相關(guān)系數(shù)從0.7032提高至0.8026)。然后,本文用空間回歸模型對(duì)上海市2013年常住人口進(jìn)行回歸,相對(duì)誤差為10.57%,并對(duì)回歸結(jié)果進(jìn)行分鄉(xiāng)(鎮(zhèn)、街道)修正。實(shí)驗(yàn)結(jié)果表明,使用空間回歸模型對(duì)常住人口回歸可以取得較高的精度,且格網(wǎng)化結(jié)果能夠彌補(bǔ)傳統(tǒng)統(tǒng)計(jì)數(shù)據(jù)空間分辨率低的缺點(diǎn),更加詳細(xì)地刻畫(huà)常住人口的圈層特征與真實(shí)分布情況。
[Abstract]:Accurate understanding of the quantity and distribution of resident population will help to clarify the social development and improve the ability of population management. At present, the population data mainly take the administrative region as the unit statistics, it is difficult to express the urban internal population distribution characteristic. However, in the city, affected by roads, public service facilities, urban lighting, the use of night lighting data to return to the population, the accuracy is reduced. How to improve the precision of urban resident population regression is worth further study. Shanghai is one of the national central cities in China. It faces huge population pressure in the process of rapid urbanization. Therefore, based on the night lighting data of NPP-VIIRS(National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite, the light data of commercial and residential areas are extracted to alleviate the impact of traffic and urban lighting areas. The correlation between the light accumulative value and the resident population was improved (the correlation coefficient was increased from 0.7032 to 0.8026). Then, this paper uses the spatial regression model to regression the resident population of Shanghai in 2013, the relative error is 10.57, and the regression result is corrected by the township (town, street). The experimental results show that the spatial regression model can achieve high precision for the permanent population regression, and the grid results can make up for the low spatial resolution of the traditional statistical data. More detailed description of the characteristics of the resident population and the true distribution of the circle.
【作者單位】： 江蘇省地理信息技術(shù)重點(diǎn)實(shí)驗(yàn)室;南京大學(xué)地理信息科學(xué)系;南京市國(guó)土資源局;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(41571378) 中國(guó)土地勘測(cè)規(guī)劃院外協(xié)項(xiàng)目(2016-63-3)
【分類(lèi)號(hào)】：C924.2

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