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本科生孔文苑、程敬宜、刘鑫等的论文在International Journal of Remote Sensing刊出
发布时间:2019-05-20 16:25:13     发布者:易真     浏览次数:

标题: Incorporating nocturnal UAV side-view images with VIIRS data for accurate population estimation: a test at the urban administrative district scale

作者: Wenyuan Kong; Jingyi Cheng; Xin Liu; Fan Zhang; Teng Fei*

来源出版物: International Journal of Remote Sensing DOI: 10.1080/01431161.2019.1615653  出版时间: 14 MAY 2019  

摘要: In contrast to daytime remote sensing used for observing the Earth, night-time light remote sensing with satellites primarily assesses human activity using urban parameters such as building lights or lighted highways to help determine population density and other habitation characteristics. One limitation to conventional night-time remote sensing is that light emitted from high-rise buildings, for example, is not easily detected because of optical geometry as satellite sensors are generally pointed in only a downward direction. Furthermore, satellite sensors often receive weak optical signals because of streetlights reflected from the Earth’s surface. As a result, accurate information on night-time human activity cannot be gathered from existing satellite remote-sensing methods. To address this, a new method for night-time remote setting is presented. Specifically, an unmanned aerial vehicle (UAV) is used to capture panoramic images of night-time light and processed to reveal side-view light spot information from urban buildings. This dataset was used to predict population density alone, and with the Visible Infrared Imaging Radiometer Suite (VIIRS) data by simple multiple linear regression. The results confirm that nocturnal UAV side-view data or VIIRS data alone can be used to estimate population density, while the combination of the two significantly increases the accuracy of population density estimation compared against estimating population density using nocturnal UAV side-view data or VIIRS data alone. This outcome suggests that multi-angular night-time remote-sensing data sources increase the accuracy of urban population density estimation. One reason for this may be that the side-view night-time data and orthophoto data infer urban population density from different agent variables: building occupancy is a proxy of side-view night-time data, while density of illuminated road network is that of orthophoto data.

文献类型:Article

语种:English

通讯作者地址:Teng Fei , School of Resource and Environmental Sciences, Wuhan University, Wuhan, China

通讯作者电子邮件地址:feiteng@whu.edu.cn

作者地址:

[Wenyuan Kong, Jingyi Cheng, Xin Liu, Teng Fei] School of Resource and Environmental Sciences, Wuhan University, Wuhan, China

[Fan Zhang] The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University (LIESMARS), Wuhan, China

影响因子:1.782


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