Study on Urban Spatial Pattern Based on DMSP/OLS and NPP/VIIRS in Democratic People’s Republic of Korea

Abstract

In recent years, much attention has been given to the current situation and trend regarding economic development in the Democratic People’s Republic of Korea (DPRK), of which urbanization is an important indicator. In the present study, (i) the urbanized area is estimated using DMSP/OLS and NPP/VIIRS, (ii) the current spatial pattern and the change characteristics of typical cities are revealed, and (iii) the scale and developmental stage of major cities in the DPRK are judged through comparison. Although the DPRK is relatively closed, the financial crisis in 2008 indirectly affected its economic development, and a large gap remains between the urbanization level of the DPRK and that of China and the Republic of Korea. The large cities in the DPRK are located mainly in its eastern coastal areas and western plains, and there has been no significant expansion in Pyongyang, Chungjin, and Hamhung in the past 28 years. Although economic construction has begun again recently in the DPRK, further reform and opening are required. As the DPRK’s relations with its neighbors and countries around the world improve, its economic development and urban construction will present a new pattern.

A Spatiotemporally Constrained Interpolation Method for Missing Pixel Values in the Suomi-NPP VIIRS Monthly Composite Images: Taking Shanghai as an Example

“…Nighttime light has important application value in the research and development of remote sensing applications. As a technology different from traditional optical remote sensing or microwave remote sensing, it uses earth observation sensors to obtain visible light-near-infrared electromagnetic wave information emitted by the Earth's surface under cloudless conditions at night, providing a unique and direct perspective for human social activities [1], and is widely used in the fields of population spatialization estimation [2][3][4][5], socioeconomic evaluation [6][7][8], and ecological environment and urbanization process assessment [9][10][11][12][13][14][15]. The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership Satellite (S-NPP) provides a new generation of nighttime light remote sensing data.…”

Identifying Population Hollowing Out Regions and Their Dynamic Characteristics across Central China

“…Previous studies have attempted to infer social-economic conditions using large data, including remotely sensed data and social media data. Large data such as social media data, the points of interest (POIs) [17,18], street view pictures [19], mobile phone metadata [20], public transit smartcard data [21], and housing rent data [22] as well as the remotely sensed data have been widely used to predict socio-economic parameters such as population [23][24][25][26], electricity consumption [27,28], the built-up area detection [29,30], gross domestic product [31], poverty [32], house vacancy [33], and can be better used in the fields of describing the socio-economic conditions of urban interior space. Although the spatiotemporal resolution has been greatly improved and the cost of data acquisition has been largely reduced by the big data, using big data to determine the population hollowing out was still a big challenge.…”

Analysis and Prediction of Spatiotemporal Changes of Urban Areas Using Neural Networks

“…Urbanization is a name that denotes the natural or mechanical increase of population in urban areas, the expansion of urban areas or the transformation of predominantly rural characteristics of an area into an urban area. Urbanization is causing rapid land cover change, especially in developing countries [4]. The process of urbanization implies, above all, the development of cities, and in a broader sense, all other human settlements.…”