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The photoelectric amplification characteristics of Operational Linescan System(OLS) sensors on board of the Defense Meteorological Satellite Program's(DMSP) satellites make the instruments sensitive to low visible lights in the night which can distinguish the differences of light signals between urban and rural areas.Remotely sensed nighttime light...
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... According to Gottmann (2005), the urban expansion type of a single city can be divided into agglomeration type and diffusion type. Fan et al. (2013) and Dang et al. (2022) respectively analysed the spatial expansion characteristics of urban agglomerations in Bohai Rim and Guanzhong Plain by using patch landscape morphological characteristics index. Cui et al. (2022) analysed the spatial characteristics and evolution of land use change in four western urban agglomerations from 1980 to 2018 based on dynamic attitude of land use and land use transfer matrix. ...
Urban agglomeration is the strongest driving force of national economic development. The formation and development of urban agglomeration is an important feature of modern urbanization process, and it is of great significance to study its spatial expansion and development process for regional sustainable development. Based on the DMSP/OLS nighttime light remote sensing data from 2000 to 2010, this paper uses threshold method to extract the urban built-up area of the Yangtze River Delta urban agglomeration. The expansion characteristics of urban built-up area in Yangtze River Delta urban agglomeration are analysed from three aspects: expansion area, expansion intensity and expansion type. The results show that the urban agglomeration in The Yangtze River Delta is experienced a rapid urban built-up area expansion process during the decade. The proportion of urban built-up area increased from 9.95% to 15.46%, the average nighttime light intensity increased from 10.18 to 23.43, and the type of urban built-up area expansion was filling type.
... Based on previous studies and the DMSP/OLS image processing, performed continuity correction on the annual NPP-VIIRS images (Eq. (4)) (Cao et al., 2015;Fan et al., 2013). ...
In the context of rapid socioeconomic development, population mobility has become an increasingly prominent phenomenon and is profoundly influencing urban development. Therefore, when proposing strategies to rejuvenate Northeast China and promoting sustainable development in the region, it is important to explore long-term population trends and to formulate development strategies and policies accordingly. Using remote-sensing nighttime light data obtained by DMSP/OLS during 1992–2012 and NPP-VIIRS during 2012–2018 in combination with population statistics for China’s three northeastern provinces, this study estimated the population of 36 prefecture-level cities and quantitatively studied population loss trends. The results showed that: (1) the three northeastern provinces have great population mobility, presenting a multi-center “T”-shaped spatial pattern with provincial capitals being the main center and population gradually decreasing toward peripheral areas, with Liaoning > Heilongjiang > Jilin in terms of overall population; (2) from 1992 to 1996, the population of the three northeastern provinces showed a positive linear growth trend, with the population increasing by 5.64 × 10⁴ people and an average population growth rate of 2.29% over the four-year period; from 1996 to 2006, population growth slowed, with an increase of only 2.08 × 10⁴ people over 10 years, and the average growth rate dropped to 0.18%; in 2006–2011, population growth showed a negative trend, with a population loss of 0.98 × 10⁴ people and a decline rate of 0.31%; beginning in 2012, population loss was very serious, presenting a sharp linear decline, and by 2018, the population loss was as high as 4.46 × 10⁶ people. Our findings indicate that population loss will result in a series of negative effects in the region, not only affecting the population growth structure but also changing the regional population structure, and inconveniencing government management and planning.
... In recent years, many scholars have used NTL data for construction land extraction [5,6]. Liao et al. [7] and Fan et al. [8] introduced the analysis method of landscape index into urban lighting research to explore the changing characteristics of urban development spatial patterns. Wu et al. [9] divided the city NTL into multiple levels, and dynamically studies the proportion and change characteristics of different types of areas to reveal the law of urban development. ...
The appearance of nighttime light (NTL) data allows us to experience urban development from more angles. This paper uses VIIRS/DNB monthly composite data to extract the urban built-up areas of 17 cities in Shandong Province. Then the built-up area extraction results in 2012 and 2017 are compared to determine the expansion type of each city. Finally, based on the intensity of city lights, we calculated the correlation between cities to show the strength of the connections between them. We find that the NTL values of Qingdao, Jinan, Yantai, and Weifang occupy the top four in Shandong Province, and this result is consistent with economic statistics. Laiwu, Qingdao, and Weifang have shown strong spatial expansion. Based on the growth area of built-up areas and urban development patterns in the past five years, the 17 cities in Shandong Province can be divided into four types: central expansion type (Jinan), multi-core development type (Rizhao), satellite diffusion type (Weifang) and mixed type (Zibo). We have summarized the characteristics of various types. There is little change in the spatial correlation between cities in 2012 and 2017. Cities such as Jinan, Zibo, Weifang, and Qingdao are closely related to other regions. The location degree of the city is also highest in these four cities, and the north and south sides of Shandong Province are lower.
... Concentrations with significant differences are highlighted in bold. surrounding the Bohai Sea experienced rapid urbanization (Fan et al., 2013), increasing urban domestic pollution, and seriously impacting seawater quality Tong et al., 2014;Zhao et al., 2018). In addition, marine culture surrounding BHB exhibited a continual increase during 2003-2015 ( Fig. 13) and also provided a nonnegligible contribution. ...
The temporal and spatial distributions of dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and dissolved silicate (DSi), and their long-term changes were investigated in Bohai Bay (BHB) in spring, summer, and autumn (2013-2014). The high DIN values were consistently distributed in the western inshore waters, mainly determined by terrestrial factors, e.g., riverine input, while DIP and DSi were mostly distributed in the southern coastal waters, the central BHB, or near the sea port Caofeidian in northern BHB, largely related to non-terrestrial factors, e.g., sediment release. Based on the nutrient distribution, BHB could be partitioned into western and eastern parts, with −15 m depth as the separation. The long-term variations of nutrients since 2000 showed an increase in DIN and decreases in DIP and DSi. Relatively slow changes in DIN and DIP and a rapid decrease in DSi were exhibited in summer, which was associated with precipitation and sediment release.
... Liao, Wei, and Song (2012) reported on the urban spatial distribution pattern of Jiangxi Province based on the DMSP/OLS nighttime light imagery during the period 1994-2009, and concluded its development patterns, including the increasing of connectivities, in contrast to the decreasing of fragmentation degree between towns. Fan et al. (2013) focused on the spatial pattern change study in the Bohai Rim Region using DMSP/OLS nighttime imagery during the period 1992-2010. The results showed that the expansion rates in small cities are relatively higher than big cities, and meanwhile the connectivity between core cities and satellite cities is increasing. ...
City lights, fishing boats, and oil fields are the major sources of nighttime lights, therefore the nighttime light images provide a unique source to map human beings and their activities from outer space. While most of the scholars focused on application of nighttime light remote sensing in urbanization and regional development, the actual fields are much wider. This paper summarized the applications of nighttime light remote sensing into fields such as the estimation of socioeconomic parameters, monitoring urbanization, evaluation of important events, analyzing light pollution, fishery, etc. For estimation of socioeconomic parameters, the most promising progress is that Gross Domestic Product and its growth rate have been estimated with statistical data and nighttime light data using econometric models. For monitoring urbanization, urban area and its dynamics can be extracted using different classification methods, and spatial analysis has been employed to map urban agglomeration. As sharp changes of nighttime light are associated with important socioeconomic events, the images have been used to evaluate humanitarian disasters, especially in the current Syrian and Iraqi wars. Light pollution is another hotspot of nighttime light application, as the night light is related to some diseases and abnormal behavior of animals, and the nighttime light images can provide light pollution information on large scales so that it is much easier to analyze the effects of light pollutions. In each field, we listed typical cases of the applications. At last, future studies of nighttime light remote sensing have been predicted.
... The two forms of spatial expansion largely coincided with industrial relocations, as well as the construction of new economic development zones and industrial districts in the region. These findings largely echo those from the studies of the Pearl River delta, Yangtze River delta and Bohai Rim in China for the same period of time (Fan, Ma, Zhou, & Zhou, 2013;Liu et al., 2009;Wang, Wang, Li, & Dong, 2012). Actually, spatial coalescence did not just happen between each city and its surrounding areas. ...
Previous studies demonstrated that DMSP-OLS stable nighttime light data are useful data source for delineating urban areas. However, the nighttime light data acquired in different years are not directly comparable, due to the variations in atmospheric condition from year to year and the periodic change in satellite sensor. This makes it difficult to use the time series nighttime light data for urban growth analysis. This paper presents a novel technique for normalizing time series DMSP/OLS nighttime light data and deriving urban detection threshold using Pseudo Invariant Features (PIFs). Our technique consists of three steps: (1) estimate an optimal threshold value for urban area detection for a reference year, when high resolution image data are available for some local areas. (2) Based on the irreversible nature of urbanization process, determine a set of PIFs, which are deemed as urban areas and did not exhibit significant change in nighttime light condition during the study period. (3) Normalize the time series DMSP-OLS data sets based on the PIFs and linear regression, determine optimal threshold values for urban area detection for all years based on the reference year threshold value, and extract urban areas accordingly. This technique was successfully applied to time series DMSP-OLS nighttime light images of the Central Liaoning region in China. Patterns of this urban agglomeration's spatial–temporal evolution from 2000 to 2010 were mapped and analyzed. The reliability and spatial accuracy of this technique were evaluated with multitemporal Landsat TM images. The technique was proved accurate and effective.
Urbanization is a complex process reflecting the growth, formation and development of cities and their systems. Measuring regional urbanization levels within a long time series may ensure healthy and harmonious urban development. Based on DMSP/OLS nighttime light data, a human—computer interactive boundary correction method was used to obtain information about built-up urban areas in the Bohai Rim region from 1992 to 2012. Consequently, a method was proposed and applied to measure urbanization levels using four measurement scale units: administrative division, land-sea location, terrain feature, and geomorphological types. Our conclusions are: 1) The extraction results based on DMSP/OLS nighttime light data showed substantial agreement with those obtained using Landsat TM/ETM+ data on spatial patterns. The overall accuracy was 97.70% on average, with an average Kappa of 0.79, indicating that the results extracted from DMSP/OLS nighttime light data were reliable and could well reflect the actual status of built-up urban areas. 2) Bohai Rim’s urbanization level has increased significantly, demonstrating a high annual growth rate from 1998 to 2006. Areas with high urbanization levels have relocated evidently from capital to coastal cities. 3) The distribution of built-up urban areas showed a certain degree of zonal variation. The urbanization level was negatively correlated with relief amplitude and altitude. A high level of urbanization was found in low altitude platforms and low altitude plains, with a gradual narrowing of the gap between these two geomorphological types. 4) The measurement method presented in this study is fast, convenient, and incorporates multiple perspectives. It would offer various directions for urban construction and provide reference values for measuring national-level urbanization.
When observing the Earth from above at night, it is clear that the human settlement and major economic regions emit glorious light. At cloud-free nights, some remote sensing satellites can record visible radiance source, including city light, fishing boat light and fire, and these nighttime cloud-free images are remotely sensed nighttime light images. Different from daytime remote sensing, nighttime light remote sensing provides a unique perspective on human social activities, thus it has been widely used for spatial data mining of socioeconomic domains. Historically, researches on nighttime light remote sensing mostly focus on urban land cover and urban expansion mapping using DMSP/OLS imagery, but the nighttime light images are not the unique remote sensing source to do these works. Through decades of development of nighttime light product, the nighttime light remote sensing application has been extended to numerous interesting and scientific study domains such as econometrics, poverty estimation, light pollution, fishery and armed conflict. Among the application cases, it is surprising to see the Gross Domestic Production (GDP) data can be corrected using the nighttime light data, and it is interesting to see mechanism of several diseases can be revealed by nighttime light images, while nighttime light are the unique remote sensing source to do the above works. As the nighttime light remote sensing has numerous applications, it is important to summarize the application of nighttime light remote sensing and its data mining fields. This paper introduced major satellite platform and sensors for observing nighttime light at first. Consequently, the paper summarized the progress of nighttime light remote sensing data mining in socioeconomic parameter estimation, urbanization monitoring, important event evaluation, environmental and healthy effects, fishery dynamic mapping, epidemiological research and natural gas flaring monitoring. Finally, future trends of nighttime light remote sensing and its data mining have been proposed from four aspects including new data source, knowledge discovery, in-situ observation, and national/global geographic conditions monitoring.
