| Records |
Author  |
Zheng, Q.; Teo, H.C.; Koh, L.P. |
| Title |
Artificial Light at Night Advances Spring Phenology in the United States |
Type |
Journal Article |
| Year |
2021 |
Publication |
Remote Sensing |
Abbreviated Journal |
Remote Sensing |
| Volume |
13 |
Issue |
3 |
Pages |
399 |
| Keywords |
Plants; Remote sensing |
| Abstract |
Plant phenology is closely related to light availability as diurnal and seasonal cycles are essential environmental cues for organizing bio-ecological processes. The natural cycles of light, however, have been dramatically disrupted by artificial light at night (ALAN) due to recent urbanization. The influence on plant phenology of ALAN and its spatial variation remain largely unknown. By analyzing satellite data on ALAN intensity across the United States, here, we showed that ALAN tended to advance the start date of the growing season (SOS), although the overall response of SOS to ALAN was relatively weak compared with other potential factors (e.g., preseason temperature). The phenological impact of ALAN showed a spatially divergent pattern, whereby ALAN mainly advanced SOS at climatically moderate regions within the United States (e.g., Virginia), while its effect was insignificant or even reversed at very cold (e.g., Minnesota) and hot regions (e.g., Florida). Such a divergent pattern was mainly attributable to its high sensitivity to chilling insufficiency, where the advancing effect on SOS was only triggered on the premise that chilling days exceeded a certain threshold. Other mechanisms may also play a part, such as the interplay among chilling, forcing and photoperiod and the difference in species life strategies. Besides, urban areas and natural ecosystems were found to suffer from similar magnitudes of influence from ALAN, albeit with a much higher baseline ALAN intensity in urban areas. Our findings shed new light on the phenological impact of ALAN and its relation to space and other environmental cues, which is beneficial to a better understanding and projection of phenology changes under a warming and urbanizing future. |
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2072-4292 |
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GFZ @ kyba @ |
Serial |
3332 |
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| Author |
Zheng, H.; Gui, Z.; Wu, H.; Song, A. |
| Title |
Developing Non-Negative Spatial Autoregressive Models for Better Exploring Relation Between Nighttime Light Images and Land Use Types |
Type |
Journal Article |
| Year |
2020 |
Publication |
Remote Sensing |
Abbreviated Journal |
Remote Sensing |
| Volume |
12 |
Issue |
5 |
Pages |
798 |
| Keywords |
Remote Sensing |
| Abstract |
Exploring the relationship between nighttime light and land use is of great significance to understanding human nighttime activities and studying socioeconomic phenomena. Models have been studied to explain the relationships, but the existing studies seldom consider the spatial autocorrelation of night light data, which leads to large regression residuals and an inaccurate regression correlation between night light and land use. In this paper, two non-negative spatial autoregressive models are proposed for the spatial lag model and spatial error model, respectively, which use a spatial adjacency matrix to calculate the spatial autocorrelation effect of light in adjacent pixels on the central pixel. The application scenarios of the two models were analyzed, and the contribution of various land use types to nighttime light in different study areas are further discussed. Experiments in Berlin, Massachusetts and Shenzhen showed that the proposed methods have better correlations with the reference data compared with the non-negative least-squares method, better reflecting the luminous situation of different land use types at night. Furthermore, the proposed model and the obtained relationship between nighttime light and land use types can be utilized for other applications of nighttime light images in the population, GDP and carbon emissions for better exploring the relationship between nighttime remote sensing brightness and socioeconomic activities. |
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2072-4292 |
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GFZ @ kyba @ |
Serial |
2848 |
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| Author |
Zhen, J.; Pei, T.; Xie, S. |
| Title |
Kriging methods with auxiliary nighttime lights data to detect potentially toxic metals concentrations in soil |
Type |
Journal Article |
| Year |
2019 |
Publication |
The Science of the Total Environment |
Abbreviated Journal |
Sci Total Environ |
| Volume |
659 |
Issue |
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Pages |
363-371 |
| Keywords |
Remote Sensing |
| Abstract |
The spatial distribution of potentially toxic metals (PTMs) has been shown to be related to anthropogenic activities. Several auxiliary variables, such as those related to remote sensing data (e.g. digital elevation models, land use, and enhanced vegetation index) and soil properties (e.g. pH, soil type and cation exchange capacity), have been used to predict the spatial distribution of soil PTMs. However, these variables are mostly focused on natural processes or a single aspect of anthropogenic activities and cannot reflect the effects of integrated anthropogenic activities. Nighttime lights (NTL) images, a representative variable of integrated anthropogenic activities, may have the potential to reflect PTMs distribution. To uncover this relationship and determine the effects on evaluation precision, the NTL was employed as an auxiliary variable to map the distribution of PTMs in the United Kingdom. In this study, areas with a digital number (DN)>/=50 and an area>30km(2) were extracted from NTL images to represent regions of high-frequency anthropogenic activities. Subsequently, the distance between the sampling points and the nearest extracted area was calculated. Barium, lead, zinc, copper, and nickel concentrations exhibited the highest correlation with this distance. Their concentrations were mapped using distance as an auxiliary variable through three different kriging methods, i.e., ordinary kriging (OK), cokriging (CK), and regression kriging (RK). The accuracy of the predictions was evaluated using the leave-one-out cross validation method. Regardless of the elements, CK and RK always exhibited lower mean absolute error and root mean square error, in contrast to OK. This indicates that using the NTL as the auxiliary variable indeed enhanced the prediction accuracy for the relevant PTMs. Additionally, RK showed superior results in most cases. Hence, we recommend RK for prediction of PTMs when using the NTL as the auxiliary variable. |
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State Key Laboratory of Geological Processes and Mineral Resources(GPMR), Faculty of Earth Sciences, China University of Geosciences, Wuhan, 430074, China |
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English |
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0048-9697 |
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PMID:30599355 |
Approved |
no |
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GFZ @ kyba @ |
Serial |
2494 |
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| Author |
Zhao,; Zhou,; Li,; Cao,; He,; Yu,; Li,; Elvidge,; Cheng,; Zhou, |
| Title |
Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives |
Type |
Journal Article |
| Year |
2019 |
Publication |
Remote Sensing |
Abbreviated Journal |
Remote Sensing |
| Volume |
11 |
Issue |
17 |
Pages |
1971 |
| Keywords |
Remote Sensing; Review |
| Abstract |
Nighttime light observations from remote sensing provide us with a timely and spatially explicit measure of human activities, and therefore enable a host of applications such as tracking urbanization and socioeconomic dynamics, evaluating armed conflicts and disasters, investigating fisheries, assessing greenhouse gas emissions and energy use, and analyzing light pollution and health effects. The new and improved sensors, algorithms, and products for nighttime lights, in association with other Earth observations and ancillary data (e.g., geo-located big data), together offer great potential for a deep understanding of human activities and related environmental consequences in a changing world. This paper reviews the advances of nighttime light sensors and products and examines the contributions of nighttime light remote sensing to perceiving the changing world from two aspects (i.e., human activities and environmental changes). Based on the historical review of the advances in nighttime light remote sensing, we summarize the challenges in current nighttime light remote sensing research and propose four strategic directions, including: Improving nighttime light data; developing a long time series of consistent nighttime light data; integrating nighttime light observations with other data and knowledge; and promoting multidisciplinary and interdisciplinary analyses of nighttime light observations. |
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2072-4292 |
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no |
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GFZ @ kyba @ |
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2677 |
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| Author |
Zhao, Z., Zhou, Y., Tan, G., & Li, J. |
| Title |
Research progress about the effect and prevention of blue light on eyes |
Type |
Journal Article |
| Year |
2018 |
Publication |
International Journal of Ophthalmology |
Abbreviated Journal |
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| Volume |
11 |
Issue |
12 |
Pages |
1999-2003 |
| Keywords |
Vision; Human Health; Review |
| Abstract |
In recent years, people have become increasingly attentive to light pollution influences on their eyes. In the visible spectrum, short-wave blue light with wavelength between 415 nm and 455 nm is closely related to eye light damage. This high energy blue light passes through the cornea and lens to the retina causing diseases such as dry eye, cataract, age-related macular degeneration, even stimulating the brain, inhibiting melatonin secretion, and enhancing adrenocortical hormone production, which will destroy the hormonal balance and directly affect sleep quality. Therefore, the effect of Blu-rays on ocular is becoming an important concern for the future. We describe blue light's effects on eye tissues, summarize the research on eye injury and its physical prevention and medical treatment. |
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IDA @ intern @ |
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2313 |
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