In this study, we provide a detailed case study of the X-pattern of equatorial ionization anomaly(EIA) observed on the night of September 12, 2021 by the Global-scale Observations of the Limb and Disk(GOLD) mission. U...In this study, we provide a detailed case study of the X-pattern of equatorial ionization anomaly(EIA) observed on the night of September 12, 2021 by the Global-scale Observations of the Limb and Disk(GOLD) mission. Unlike most previous studies about the X-pattern observed under the severely disturbed background ionosphere, this event is observed under geomagnetically quiet and low solar activity conditions. GOLD's continuous observations reveal that the X-pattern intensity evolves with local time, while its center's longitude remains constant. The total electron content(TEC) data derived from the ground-based Global Navigation Satellite System(GNSS) network aligns well with GOLD observations in capturing the formation of the X-pattern, extending coverage to areas beyond GOLD's observational reach. Additionally, the ESA's Swarm mission show that both sides of the X-pattern can coincide with the occurrence of small-scale equatorial plasma bubbles(EPBs). To further analyze the possible drivers of the X-pattern, observations from the Ionospheric Connection Explorer(ICON) satellite were used. It shows that the latitudinal expansion(or width) between the EIA crests in two hemispheres is proportional(or inversely proportional) to the upward(or downward) plasma drift velocity, which suggests that the zonal electric field should have a notable influence on the formation of EIA X-pattern. Further simulations using the SAMI2 model support this mechanism, as the X-pattern of EIA is successfully reproduced by setting the vertical plasma drift to different values at different longitudes.展开更多
Unmanned Aerial Vehicles(UAVs)have become indispensable for intelligent traffic monitoring,particularly in low-light conditions,where traditional surveillance systems struggle.This study presents a novel deep learning...Unmanned Aerial Vehicles(UAVs)have become indispensable for intelligent traffic monitoring,particularly in low-light conditions,where traditional surveillance systems struggle.This study presents a novel deep learning-based framework for nighttime aerial vehicle detection and classification that addresses critical challenges of poor illumination,noise,and occlusions.Our pipeline integrates MSRCR enhancement with OPTICS segmentation to overcome low-light challenges,while YOLOv10 enables accurate vehicle localization.The framework employs GLOH and Dense-SIFT for discriminative feature extraction,optimized using the Whale Optimization Algorithm to enhance classification performance.A Swin Transformer-based classifier provides the final categorization,leveraging hierarchical attention mechanisms for robust performance.Extensive experimentation validates our approach,achieving detection mAP@0.5 scores of 91.5%(UAVDT)and 89.7%(VisDrone),alongside classification accuracies of 95.50%and 92.67%,respectively.These results outperform state-of-the-art methods by up to 5.10%in accuracy and 4.2%in mAP,demonstrating the framework’s effectiveness for real-time aerial surveillance and intelligent traffic management in challenging nighttime environments.展开更多
Assessing regional economic development is key for advancing towards the Sustainable Development Goals and ensuring sustainable societal progress.Traditional evaluation methods focus on basic economic metrics like pop...Assessing regional economic development is key for advancing towards the Sustainable Development Goals and ensuring sustainable societal progress.Traditional evaluation methods focus on basic economic metrics like population and capital,which may not fully reflect the complexities of economic activities.Nighttime light(NTL)has been validated as an alternative indicator for regional economic development,yet limitations persist in its evaluation.This study integrates OpenStreetMap(OSM)data and NTL data,providing a novel data integration approach for evaluating economic development.The study uses mainland of China as a case,applying ordinary least squares(OLS)and geographically weighted regression(GWR)to evaluate OSM and NTL data across provincial,municipal,and county levels.It compares OSM,NTL,and their combined use,providing key empirical insights for enhancing data fusion models.The study results reveal:(1)NTL data is more accurate for provincial-level economic activity,while OSM data excels at the county level.(2)GWR demonstrates superior capability over OLS in revealing the spatial dynamics of economic development across scales.(3)Through the integration of both datasets,it is observed that,compared to single-data modeling,the performance is enhanced at the city scale and county scale.The study demonstrates that combining OSM and NTL data effectively assesses economic development in both developed and underdeveloped areas at provincial,municipal,and county levels.The study offers a straightforward and efficient approach to data integration.The findings offer new research perspectives and scientific support for sustainable regional economic growth,particularly valuable in data-scarce,underdeveloped areas.展开更多
China’s economy has developed rapidly since its reform and opening-up.However,the different rates of development in various places due to location and policies have led to significant economic differences.Based on th...China’s economy has developed rapidly since its reform and opening-up.However,the different rates of development in various places due to location and policies have led to significant economic differences.Based on the nighttime lighting data of 281 municipal spatial units in China from 2013 to 2021,this study uses spatial autocorrelation,center of gravity shift,and standard deviation ellipse(SDE)analysis to examine the evolution of the spatial pattern of China’s municipal economy.Based on these,it uses a geographically weighted regression(GWR)model to explore the factors influencing the differences in China’s municipal economy and its spatial heterogeneity.The paper reveals the following results.First,China’s municipal economy as a whole shows a growing trend.Second,the SDE shows a“north-south”distribution pattern,and the concentration of China’s economic development has slightly increased,with a significant centripetal distribution.Third,spatial correlation shows spatial positive correlation,the degree of which is increasing,with strong spatial heterogeneity and regional agglomeration.Finally,measuring the influencing factors according to GWR,the industrial structure and education expenditure coefficients generally show a decreasing trend from the southeast coast to the northwest and inland due to the degree of transformation of industrial structure and the lagging effect of education expenditure on economic growth.Conversely,the innovation driver and urban area coefficients show a decreasing trend from the northwest inland to the southeast coast due to the law of diminishing marginal utility of innovation drivers and differences in urbanization development.Government expenditure coefficients show a higher trend in the East and a lower trend in the West due to policy favoritism and market development level.This research can serve as a theoretical reference for China to achieve high-quality development and move toward common prosperity.展开更多
Semantic segmentation of driving scene images is crucial for autonomous driving.While deep learning technology has significantly improved daytime image semantic segmentation,nighttime images pose challenges due to fac...Semantic segmentation of driving scene images is crucial for autonomous driving.While deep learning technology has significantly improved daytime image semantic segmentation,nighttime images pose challenges due to factors like poor lighting and overexposure,making it difficult to recognize small objects.To address this,we propose an Image Adaptive Enhancement(IAEN)module comprising a parameter predictor(Edip),multiple image processing filters(Mdif),and a Detail Processing Module(DPM).Edip combines image processing filters to predict parameters like exposure and hue,optimizing image quality.We adopt a novel image encoder to enhance parameter prediction accuracy by enabling Edip to handle features at different scales.DPM strengthens overlooked image details,extending the IAEN module’s functionality.After the segmentation network,we integrate a Depth Guided Filter(DGF)to refine segmentation outputs.The entire network is trained end-to-end,with segmentation results guiding parameter prediction optimization,promoting self-learning and network improvement.This lightweight and efficient network architecture is particularly suitable for addressing challenges in nighttime image segmentation.Extensive experiments validate significant performance improvements of our approach on the ACDC-night and Nightcity datasets.展开更多
Balanced development and the reduction of inequality are central objectives of the United Nations Sustainable Development Goals(SDGs).This study explores the use of Nighttime Light(NTL)brightness and the Nighttime Lig...Balanced development and the reduction of inequality are central objectives of the United Nations Sustainable Development Goals(SDGs).This study explores the use of Nighttime Light(NTL)brightness and the Nighttime Light Development Index(NLDI)as indicators of socioeconomic development in urban centers,focusing on six Indian cities.It examines the correlation between these indices and socioeconomic inequality across affluent neighborhoods,urban slums,downtown areas,and general urban areas in 2015,2018,and 2021.The results reveal that lighting brightness in affluent areas can be lower than that in bustling downtowns,due to factors such as lower residential density.This challenges the conventional assumption that higher NTL necessarily indicates greater prosperity.This study further confirmed significant developmental disparities between well-lit downtowns and poorly illuminated peripheral slum areas,as reflected by lower NLDI scores.Notably,the results uncover a phenomenon termed“same value but different spectrum”based on a careful examination of NLDI values of urban centers and their corresponding curves.This suggests that NLDI alone may not fully capture the complexity of urban development,and that underlying development trajectories,along with on-the-ground realities,must be further examined.The findings emphasize the importance of applying NLDI for urban internal analyses.In addition,the study highlights the necessity for nuanced urban planning and targeted policy interventions specifically tailored to the unique conditions of different urban areas.展开更多
In this study,we proposed a multi-source approach for mapping local-scale population density of England.Specifically,we mapped both the working and daytime population densities by integrating the multi-source data suc...In this study,we proposed a multi-source approach for mapping local-scale population density of England.Specifically,we mapped both the working and daytime population densities by integrating the multi-source data such as residential population density,point-of-interest density,point-of-interest category mix,and nighttime light intensity.It is demonstrated that combining remote sensing and social sensing data provides a plausible way to map annual working or daytime population densities.In this paper,we trained models with England-wide data and subsequently tested these models with Wales-wide data.In addition,we further tested the models with England-wide data at a higher level of spatial granularity.Particularly,the random forest and convolutional neural network models were adopted to map population density.The estimated results and validation suggest that the three built models have high prediction accuracies at the local authority district level.It is shown that the convolutional neural network models have the greatest prediction accuracies at the local authority district level though they are most time-consuming.The models trained with the data at the local authority district level are less appropriately applicable to test data at a higher level of spatial granularity.The proposed multi-source approach performs well in mapping local-scale population density.It indicates that combining remote sensing and social sensing data is advantageous to mapping socioeconomic variables.展开更多
A dual channel difference （DCD） method is applied to detect nighttime sea fog/stratus over the Huanghai Sea using the infrared （IR） data of shortwave （3.5-4.0 μm） and longwave （10.3-11.3 μm） channels from th...A dual channel difference （DCD） method is applied to detect nighttime sea fog/stratus over the Huanghai Sea using the infrared （IR） data of shortwave （3.5-4.0 μm） and longwave （10.3-11.3 μm） channels from the Multi-functional Transport Satellite （MTSAT）-IR, i.e., shortwave minus longwave brightness temperature difference （SLTD）. Twenty-four sea fog events over the Huanghai Sea during March to July of 2006 and 2007 are chosen to determine a suitable value of SLTD for nighttime sea fog/stratus detection, and it is found that the value of-5.5-2.5℃ can be taken as a criterion. Two case examples of sea fog events are especially demonstrated in detail utilizing the criterion, and the results show that the derived sea fog/stratus coverage is quite reasonable. This coverage information is very helpful to analyze the formation and evolution of sea fog/stratus during night and can provide sea fog researchers with observational evidences for model results verification. However, more efforts are needed to further obtain vertical extent information of sea fog/stratus and attempt to discriminate between sea fog and stratus.展开更多
Evidence exists of nighttime transpiration and its potential impact on plant/water relations for species in a diversity of ecosystems. However, relevant data related to typical desert riparian forest species remains l...Evidence exists of nighttime transpiration and its potential impact on plant/water relations for species in a diversity of ecosystems. However, relevant data related to typical desert riparian forest species remains limited Accordingly, we measured sap flow velocity of Populus euphratica using the heat ratio method between 2012 and2014. Nocturnal stem sap flow was separated into nighttime and stem refilling using the ‘‘forecasted refilling''method. Nighttime transpiration was observed for each phenophase. The highest value was during the full foliation period but lowest during leaf expansion and defoliation periods. The contribution of nighttime transpiration to daytime transpiration was an average of 15% but this was comparatively higher during the defoliation period. Relationships between nighttime transpiration, vapor pressure deficits, and air temperatures were more closely associated than with wind speed in all phenophases. Moreover, we found that nighttime transpiration linearly correlated to vapour pressure deficit during the first and the full foliation periods, but nighttime transpiration showed exponential correlations to air temperatures during the same phenophases. Additionally, environmental drivers of transpiration were significantly different between nighttime and daytime(P \ 0.05). Driving forces behind nighttime transpiration were characterized by many factors, and integrated impacts between these multiple environmental factors were complex. Future studies should focus on these integrated impacts on nighttime transpiration, and the physiological mechanisms of nighttime transpiration should be investigated, given that this could also influence its occurrence and magnitude during different phenophases.展开更多
AIM:To evaluate whether weekend or nighttime admission affects prognosis of peptic ulcer bleeding despite early endoscopy.METHODS:Retrospective data collection from four referral centers,all of which had a formal out-...AIM:To evaluate whether weekend or nighttime admission affects prognosis of peptic ulcer bleeding despite early endoscopy.METHODS:Retrospective data collection from four referral centers,all of which had a formal out-of-hours emergency endoscopy service,even at weekends.A total of 388 patients with bleeding peptic ulcers who were admitted via the emergency room between January 2007 and December 2009 were enrolled.Analyzed parameters included time from patients' arrival until endoscopy,mortality,rebleeding,need for surgery and length of hospital stay.RESULTS:The weekday and weekend admission groups comprised 326 and 62 patients,respectively.There were no significant differences in baseline characteristics between the two groups,except for younger age in the weekend group.Most patients (97%) had undergone early endoscopy,which resulted in a low mortality rate regardless of point of presentation (1.8% overall vs 1.6% on the weekend).The only outcome that was worse in the weekend group was a higher rate of rebleeding (12% vs 21%,P = 0.030).However,multivariate analysis revealed nighttime admission and a high Rockall score (≥ 6) as significant independent risk factors for rebleeding,rather than weekend admission.CONCLUSION:Early endoscopy for peptic ulcer bleeding can prevent the weekend effect,and nighttime admission was identified as a novel risk factor for rebleeding,namely the nighttime effect.展开更多
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 t...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.展开更多
This essay combines the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)nighttime light data and the Visible Infrared Imaging Radiometer Suite(VIIRS)nighttime light data into a“synthetic...This essay combines the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)nighttime light data and the Visible Infrared Imaging Radiometer Suite(VIIRS)nighttime light data into a“synthetic DMSP”dataset,from 1992 to 2020,to retrieve the spatio-temporal variations in energy-related carbon emissions in Xinjiang,China.Then,this paper analyzes several influencing factors for spatial differentiation of carbon emissions in Xinjiang with the application of geographical detector technique.Results reveal that(1)total carbon emissions continued to grow,while the growth rate slowed down in the past five years.(2)Large regional differences exist in total carbon emissions across various regions.Total carbon emissions of these regions in descending order are the northern slope of the Tianshan(Mountains)>the southern slope of the Tianshan>the three prefectures in southern Xinjiang>the northern part of Xinjiang.(3)Economic growth,population size,and energy consumption intensity are the most important factors of spatial differentiation of carbon emissions.The interaction between economic growth and population size as well as between economic growth and energy consumption intensity also enhances the explanatory power of carbon emissions’spatial differentiation.This paper aims to help formulate differentiated carbon reduction targets and strategies for cities in different economic development stages and those with different carbon intensities so as to achieve the carbon peak goals in different steps.展开更多
Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment espec...Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment especially within built-up areas.In this study,ArcGIS 10,ENVI 4.5,and Visual FoxPro 6.0 were used to analyze the human impacts on vegetation in the built-up areas of 656Chinese cities from 1992 to 2010.Firstly,an existing algorithm was refined to extract the boundaries of the built-up areas based on the Defense Meteorological Satellite Program Operational Linescan System(DMSP_OLS)nighttime light data.This improved algorithm has the advantages of high accuracy and speed.Secondly,a mathematical model(Human impacts(HI))was constructed to measure the impacts of human factors on vegetation during rapid urbanization based on Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)and Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI.HI values greater than zero indicate relatively beneficial effects while values less than zero indicate proportionally adverse effects.The results were analyzed from four aspects:the size of cities(metropolises,large cities,medium-sized cities,and small cities),large regions(the eastern,central,western,and northeastern China),administrative divisions of China(provinces,autonomous regions,and municipalities)and vegetation zones(humid and semi-humid forest zone,semi-arid steppe zone,and arid desert zone).Finally,we discussed how human factors impacted on vegetation changes in the built-up areas.We found that urban planning policies and developmental stages impacted on vegetation changes in the built-up areas.The negative human impacts followed an inverted′U′shape,first rising and then falling with increase of urban scales.China′s national policies,social and economic development affected vegetation changes in the built-up areas.The findings can provide a scientific basis for municipal planning departments,a decision-making reference for government,and scientific guidance for sustainable development in China.展开更多
In order to suppress complex mixing noise in low-illumination images for wide-area search of nighttime sea surface,a model based on total variation(TV)and split Bregman is proposed in this paper.A fidelity term based ...In order to suppress complex mixing noise in low-illumination images for wide-area search of nighttime sea surface,a model based on total variation(TV)and split Bregman is proposed in this paper.A fidelity term based on L1 norm and a fidelity term based on L2 norm are designed considering the difference between various noise types,and the regularization mixed first-order TV and second-order TV are designed to balance the influence of details information such as texture and edge for sea surface image.The final detection result is obtained by using the high-frequency component solved from L1 norm and the low-frequency component solved from L2 norm through wavelet transform.The experimental results show that the proposed denoising model has perfect denoising performance for artificially degraded and low-illumination images,and the result of image quality assessment index for the denoising image is superior to that of the contrastive models.展开更多
Land surface temperature(LST)is an important variable for assessing climate change and related environmental impacts observed in recent decades.Regular monitoring of LST using satellite sensors such as MODIS has the a...Land surface temperature(LST)is an important variable for assessing climate change and related environmental impacts observed in recent decades.Regular monitoring of LST using satellite sensors such as MODIS has the advantage of global coverage,including topographically complex regions such as Nepal.In order to assess the climatic and environmental changes,daytime and nighttime LST trend analysis from 2000 to 2017 using Terra-MODIS monthly daytime and nighttime LST datasets at seasonal and annual scales over the territory of Nepal was performed.The magnitude of the trend was quantified using ordinary linear regression,while the statistical significance of the trend was identified by the Modified Mann—Kendall test.Our findings suggest that the nighttime LST in Nepal increased more prominently compared to the daytime LST,with more pronounced warming in the pre-monsoon and monsoon seasons.The annual nighttime LST increased at a rate of 0.05 K yr-1(p<0.01),while the daytime LST change was statistically insignificant.Spatial heterogeneity of the LST and LST change was observed both during the day and the night.The daytime LST remained fairly unchanged in large parts of Nepal,while a nighttime LST rise was dominant all across Nepal in the pre-monsoon and monsoon seasons.Our results on LST trends and their spatial distribution can facilitate a better understanding of regional climate changes.展开更多
The Tibetan Plateau(TP)is undergoing rapid urbanization.To improve urban sustainability and construct eco-logical security barriers,it is essential to quantify the spatial patterns of urbanization level on the TP,but ...The Tibetan Plateau(TP)is undergoing rapid urbanization.To improve urban sustainability and construct eco-logical security barriers,it is essential to quantify the spatial patterns of urbanization level on the TP,but the existing studies on the topic have been limited by the lack of socioeconomic data.This study aims to quantify the urbanization level on the TP in 2018 with Luojia1-01(LJ1-01)high-resolution nighttime light(NTL)data.Specifically,the compounded night light index is used to quantify spatial patterns of urbanization level at mul-tiple scales.The results showed that the TP had a low overall urbanization level with a large internal difference.The urbanization level in the northeast,southeast and south of the TP was relatively high,forming three hotspots centered in Xining City,Lhasa City and Shangri-La City,while the urbanization level in the central and western regions was relatively low.The analysis of influencing factors,based on the random forest model,showed that transportation and topography were the main factors affecting the TP’s spatial patterns of urbanization level.The comparison analysis with socioeconomic statistics and traditional NTL data showed that LJ1-01 NTL data can be used to more effectively quantify the urbanization level since it is more advantageous for reflecting the spatial extent of urban land and describing the spatial structure of socioeconomic activities within urban areas.These advantages are attributed to the high spatial resolution of the data,appropriate imaging time and unaf-fected by saturation phenomena.Thus,the proposed LJ1-01 NTL-based urbanization level measurement method has the potential for wide applications around the world,especially in less-developed regions lacking statistical data.Using this method,we refined the measurement of the TP’s urbanization level in 2018 for multiple scales including the region,basin,prefecture and county levels,which provides basic information for the further urban sustainability research on the TP.展开更多
Comparing the city-size distribution at the urban agglomeration（UA） scale is important for understanding the processes of urban development. However, comparative studies of city-size distribution among China＇s thre...Comparing the city-size distribution at the urban agglomeration（UA） scale is important for understanding the processes of urban development. However, comparative studies of city-size distribution among China＇s three largest UAs, the Beijing-Tianjin-Hebei agglomeration（BTHA）, the Yangtze River Delta agglomeration（YRDA）, and the Pearl River Delta agglomeration（PRDA）, remain inadequate due to the limitation of data availability. Therefore, using urban data derived from time-series nighttime light data, the common characteristics and distinctive features of city-size distribution among the three UAs from 1992 to 2015 were compared by the Pareto regression and the rank clock method. We identified two common features. First, the city-size distribution became more even. The Pareto exponents increased by 0.17, 0.12, and 0.01 in the YRDA, BTHA, and PRDA, respectively. Second, the average ranks of small cities ascended, being 0.55, 0.08 and 0.04 in the three UAs, respectively. However, the average ranks of large and medium cities in the three UAs experienced different trajectories, which are closely related to the similarities and differences in the driving forces for the development of UAs. Place-based measures are encouraged to promote a coordinated development among cities of differing sizes in the three UAs.展开更多
Nighttime sap flow is a potentially important factor that affects whole-plant water balance and water-use efficiency （WUE）. Its functions include predawn disequilibrium between plant and soil water potentials as wel...Nighttime sap flow is a potentially important factor that affects whole-plant water balance and water-use efficiency （WUE）. Its functions include predawn disequilibrium between plant and soil water potentials as well as between the increments of oxygen supply and nutrient uptake. However, main factors that drive nighttime sap flow remain unclear, and researches related to the relationship between nighttime sap flow velocity and environmental factors are limited. Accordingly, we investigated the variations in the nighttime sap flow of Populus euphratica in a desert riparian forest of an extremely arid region, Northwest China. Results indicated that P. euphratica sap flow occurred throughout the night during the growing season because of the partial stomata opening. Nighttime sap flow for the P. euphratica forest accounted for 31%-47% of its daily sap flow during the growing season. The high value of nighttime sap flow could be the result of high stomatal conductance and could have significant implications for water budgets. Throughout the whole growing season, nighttime sap flow velocity of P. euphratica was positively correlated with the vapor pressure deficit （VPD）, air temperature and soil water content. We found that VPD and soil water content were the main driving factors for nighttime sap flow of P. euphratica.展开更多
Understanding the dynamics of urbanization is essential to the sustainable development of cities. Meanwhile the analysis of urban development can also provide scientifically and effective information for decision-maki...Understanding the dynamics of urbanization is essential to the sustainable development of cities. Meanwhile the analysis of urban development can also provide scientifically and effective information for decision-making. With the long-term Defense Meteorological Satellite Program’s Operational Linescan System(DMSP/OLS) nighttime light images, a pixel level assessment of urbanization of China from 1992 to 2013 was conducted in this study, and the spatio-temporal dynamics and future trends of urban development were fully detected. The results showed that the urbanization and urban dynamics of China experienced drastic fluctuations from 1992 to 2013, especially for those in the coastal and metropolitan areas. From a regional perspective, it was found that the urban dynamics and increasing trends in North Coast China, East Coast China and South Coast China were much more stable and significant than that in other regions. Moreover, with the sustainability estimating of nighttime light dynamics, the regional agglomeration trends of urban regions were also detected. The light intensity in nearly 50% of lighted pixels may continuously decrease in the future, indicating a severe situation of urbanization within these regions. In this study, The results revealed in this study can provided a new insight in long time urbanization detecting and is thus beneficial to the better understanding of trends and dynamics of urban development.展开更多
The research purpose is to accurately reveal the temporal and spatial law of the urban expansion of Changsha-Zhuzhou-Xiangtan, one of the seven major urban agglomeration areas in China, and provide decision-making bas...The research purpose is to accurately reveal the temporal and spatial law of the urban expansion of Changsha-Zhuzhou-Xiangtan, one of the seven major urban agglomeration areas in China, and provide decision-making basis for the future urban construction land layout and regional development policy-making. Based on the night lighting data (DMSP/OLS), this paper extracts the boundary of the urban construction land of Changsha-Zhuzhou-Xiangtan urban agglomeration from 1993 to 2017, and quantitatively studies the spatial and temporal characteristics of the expansion of the metropolitan area in the past 25 years according to the methods of spatial expansion analysis, center of gravity migration measurement, landscape pattern index, spatial autocorrelation, etc. The results show that: 1) it is scientific and feasible to extract urban agglomeration construction land by the method of auxiliary data comparison for the study of urban expansion;2) the expansion of regional space in Changsha-Zhuzhou-Xiangtan metropolitan area shows a trend of “weakening first and strengthening later”. The construction land keeps increasing, and the expansion form gradually changes from extensive type to intensive type;3) the center of gravity of the metropolitan area fluctuated and repeated in part during the past 25 years, but it was always located in the municipal district of Changsha city. The eastern region, mainly Changsha city, was still the core area of urban agglomeration expansion;4) strengthening the territorial space protection and control of ecological green core in the metropolitan area is a key measure for the high-quality development of urban agglomeration.展开更多
基金supported by the National Key R&D Program of China (Grant No. 2022YFF0503700)the special funds of Hubei Luojia Laboratory (220100011)+1 种基金Chao Xiong is supported by the ISSI-BJ project, “the electromagnetic data validation and scientific application research based on CSES satellite”ISSI/ISSI-BJ project “Multi-Scale Magnetosphere–Ionosphere–Thermosphere Interaction”。
文摘In this study, we provide a detailed case study of the X-pattern of equatorial ionization anomaly(EIA) observed on the night of September 12, 2021 by the Global-scale Observations of the Limb and Disk(GOLD) mission. Unlike most previous studies about the X-pattern observed under the severely disturbed background ionosphere, this event is observed under geomagnetically quiet and low solar activity conditions. GOLD's continuous observations reveal that the X-pattern intensity evolves with local time, while its center's longitude remains constant. The total electron content(TEC) data derived from the ground-based Global Navigation Satellite System(GNSS) network aligns well with GOLD observations in capturing the formation of the X-pattern, extending coverage to areas beyond GOLD's observational reach. Additionally, the ESA's Swarm mission show that both sides of the X-pattern can coincide with the occurrence of small-scale equatorial plasma bubbles(EPBs). To further analyze the possible drivers of the X-pattern, observations from the Ionospheric Connection Explorer(ICON) satellite were used. It shows that the latitudinal expansion(or width) between the EIA crests in two hemispheres is proportional(or inversely proportional) to the upward(or downward) plasma drift velocity, which suggests that the zonal electric field should have a notable influence on the formation of EIA X-pattern. Further simulations using the SAMI2 model support this mechanism, as the X-pattern of EIA is successfully reproduced by setting the vertical plasma drift to different values at different longitudes.
基金supported through Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R508)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘Unmanned Aerial Vehicles(UAVs)have become indispensable for intelligent traffic monitoring,particularly in low-light conditions,where traditional surveillance systems struggle.This study presents a novel deep learning-based framework for nighttime aerial vehicle detection and classification that addresses critical challenges of poor illumination,noise,and occlusions.Our pipeline integrates MSRCR enhancement with OPTICS segmentation to overcome low-light challenges,while YOLOv10 enables accurate vehicle localization.The framework employs GLOH and Dense-SIFT for discriminative feature extraction,optimized using the Whale Optimization Algorithm to enhance classification performance.A Swin Transformer-based classifier provides the final categorization,leveraging hierarchical attention mechanisms for robust performance.Extensive experimentation validates our approach,achieving detection mAP@0.5 scores of 91.5%(UAVDT)and 89.7%(VisDrone),alongside classification accuracies of 95.50%and 92.67%,respectively.These results outperform state-of-the-art methods by up to 5.10%in accuracy and 4.2%in mAP,demonstrating the framework’s effectiveness for real-time aerial surveillance and intelligent traffic management in challenging nighttime environments.
基金funded by The Third Comprehensive Scientific Investigation in Xinjiang(Grant No.2021xjkk1001)Program of National Social Science Foundation of China(Grant No.22BJL061)+1 种基金Major Project of Xinjiang Social Science Foundation(Grant No.21AZD008)The National Natural Science Foundation of China(Grant No.41461035).
文摘Assessing regional economic development is key for advancing towards the Sustainable Development Goals and ensuring sustainable societal progress.Traditional evaluation methods focus on basic economic metrics like population and capital,which may not fully reflect the complexities of economic activities.Nighttime light(NTL)has been validated as an alternative indicator for regional economic development,yet limitations persist in its evaluation.This study integrates OpenStreetMap(OSM)data and NTL data,providing a novel data integration approach for evaluating economic development.The study uses mainland of China as a case,applying ordinary least squares(OLS)and geographically weighted regression(GWR)to evaluate OSM and NTL data across provincial,municipal,and county levels.It compares OSM,NTL,and their combined use,providing key empirical insights for enhancing data fusion models.The study results reveal:(1)NTL data is more accurate for provincial-level economic activity,while OSM data excels at the county level.(2)GWR demonstrates superior capability over OLS in revealing the spatial dynamics of economic development across scales.(3)Through the integration of both datasets,it is observed that,compared to single-data modeling,the performance is enhanced at the city scale and county scale.The study demonstrates that combining OSM and NTL data effectively assesses economic development in both developed and underdeveloped areas at provincial,municipal,and county levels.The study offers a straightforward and efficient approach to data integration.The findings offer new research perspectives and scientific support for sustainable regional economic growth,particularly valuable in data-scarce,underdeveloped areas.
基金funded by the Project of Philosophy and Social Science Key Research Base−Industrial Transformation and Innovation Research Center of Zigong Municipal Federation of Social Sciences[Grant No.CZ23B02].
文摘China’s economy has developed rapidly since its reform and opening-up.However,the different rates of development in various places due to location and policies have led to significant economic differences.Based on the nighttime lighting data of 281 municipal spatial units in China from 2013 to 2021,this study uses spatial autocorrelation,center of gravity shift,and standard deviation ellipse(SDE)analysis to examine the evolution of the spatial pattern of China’s municipal economy.Based on these,it uses a geographically weighted regression(GWR)model to explore the factors influencing the differences in China’s municipal economy and its spatial heterogeneity.The paper reveals the following results.First,China’s municipal economy as a whole shows a growing trend.Second,the SDE shows a“north-south”distribution pattern,and the concentration of China’s economic development has slightly increased,with a significant centripetal distribution.Third,spatial correlation shows spatial positive correlation,the degree of which is increasing,with strong spatial heterogeneity and regional agglomeration.Finally,measuring the influencing factors according to GWR,the industrial structure and education expenditure coefficients generally show a decreasing trend from the southeast coast to the northwest and inland due to the degree of transformation of industrial structure and the lagging effect of education expenditure on economic growth.Conversely,the innovation driver and urban area coefficients show a decreasing trend from the northwest inland to the southeast coast due to the law of diminishing marginal utility of innovation drivers and differences in urbanization development.Government expenditure coefficients show a higher trend in the East and a lower trend in the West due to policy favoritism and market development level.This research can serve as a theoretical reference for China to achieve high-quality development and move toward common prosperity.
基金This work is supported in part by The National Natural Science Foundation of China(Grant Number 61971078),which provided domain expertise and computational power that greatly assisted the activityThis work was financially supported by Chongqing Municipal Education Commission Grants for-Major Science and Technology Project(Grant Number gzlcx20243175).
文摘Semantic segmentation of driving scene images is crucial for autonomous driving.While deep learning technology has significantly improved daytime image semantic segmentation,nighttime images pose challenges due to factors like poor lighting and overexposure,making it difficult to recognize small objects.To address this,we propose an Image Adaptive Enhancement(IAEN)module comprising a parameter predictor(Edip),multiple image processing filters(Mdif),and a Detail Processing Module(DPM).Edip combines image processing filters to predict parameters like exposure and hue,optimizing image quality.We adopt a novel image encoder to enhance parameter prediction accuracy by enabling Edip to handle features at different scales.DPM strengthens overlooked image details,extending the IAEN module’s functionality.After the segmentation network,we integrate a Depth Guided Filter(DGF)to refine segmentation outputs.The entire network is trained end-to-end,with segmentation results guiding parameter prediction optimization,promoting self-learning and network improvement.This lightweight and efficient network architecture is particularly suitable for addressing challenges in nighttime image segmentation.Extensive experiments validate significant performance improvements of our approach on the ACDC-night and Nightcity datasets.
基金Strategic Priority Research Program of Chinese Academy of Sciences,No.XDA20010303。
文摘Balanced development and the reduction of inequality are central objectives of the United Nations Sustainable Development Goals(SDGs).This study explores the use of Nighttime Light(NTL)brightness and the Nighttime Light Development Index(NLDI)as indicators of socioeconomic development in urban centers,focusing on six Indian cities.It examines the correlation between these indices and socioeconomic inequality across affluent neighborhoods,urban slums,downtown areas,and general urban areas in 2015,2018,and 2021.The results reveal that lighting brightness in affluent areas can be lower than that in bustling downtowns,due to factors such as lower residential density.This challenges the conventional assumption that higher NTL necessarily indicates greater prosperity.This study further confirmed significant developmental disparities between well-lit downtowns and poorly illuminated peripheral slum areas,as reflected by lower NLDI scores.Notably,the results uncover a phenomenon termed“same value but different spectrum”based on a careful examination of NLDI values of urban centers and their corresponding curves.This suggests that NLDI alone may not fully capture the complexity of urban development,and that underlying development trajectories,along with on-the-ground realities,must be further examined.The findings emphasize the importance of applying NLDI for urban internal analyses.In addition,the study highlights the necessity for nuanced urban planning and targeted policy interventions specifically tailored to the unique conditions of different urban areas.
文摘In this study,we proposed a multi-source approach for mapping local-scale population density of England.Specifically,we mapped both the working and daytime population densities by integrating the multi-source data such as residential population density,point-of-interest density,point-of-interest category mix,and nighttime light intensity.It is demonstrated that combining remote sensing and social sensing data provides a plausible way to map annual working or daytime population densities.In this paper,we trained models with England-wide data and subsequently tested these models with Wales-wide data.In addition,we further tested the models with England-wide data at a higher level of spatial granularity.Particularly,the random forest and convolutional neural network models were adopted to map population density.The estimated results and validation suggest that the three built models have high prediction accuracies at the local authority district level.It is shown that the convolutional neural network models have the greatest prediction accuracies at the local authority district level though they are most time-consuming.The models trained with the data at the local authority district level are less appropriately applicable to test data at a higher level of spatial granularity.The proposed multi-source approach performs well in mapping local-scale population density.It indicates that combining remote sensing and social sensing data is advantageous to mapping socioeconomic variables.
基金The National Natural Science Foundation of China under contract No. 40706004the National Basic Research Program ("973" program) of China under contract No. 2005CB422301+2 种基金China Meteorological Administration’s New Technology Extension Project under contract No. CMATG2008M41the National Special Fund for public Sector Research of China under contract No. GYHY200706031Shandong Provincial Meteorological Bureau Science Fund of China under contract No. 2004SDQXJ01.
文摘A dual channel difference （DCD） method is applied to detect nighttime sea fog/stratus over the Huanghai Sea using the infrared （IR） data of shortwave （3.5-4.0 μm） and longwave （10.3-11.3 μm） channels from the Multi-functional Transport Satellite （MTSAT）-IR, i.e., shortwave minus longwave brightness temperature difference （SLTD）. Twenty-four sea fog events over the Huanghai Sea during March to July of 2006 and 2007 are chosen to determine a suitable value of SLTD for nighttime sea fog/stratus detection, and it is found that the value of-5.5-2.5℃ can be taken as a criterion. Two case examples of sea fog events are especially demonstrated in detail utilizing the criterion, and the results show that the derived sea fog/stratus coverage is quite reasonable. This coverage information is very helpful to analyze the formation and evolution of sea fog/stratus during night and can provide sea fog researchers with observational evidences for model results verification. However, more efforts are needed to further obtain vertical extent information of sea fog/stratus and attempt to discriminate between sea fog and stratus.
基金financially supported by the Key Research Program of Frontier Sciences CAS(QYZDJ-SSWDQC031)Key Project of the Chinese Academy of Sciences(KZZDEW-04-05)+1 种基金the National Natural Science Foundation of China(91025024)the ‘‘Western Light’’ project of the Chinese Academy of Science
文摘Evidence exists of nighttime transpiration and its potential impact on plant/water relations for species in a diversity of ecosystems. However, relevant data related to typical desert riparian forest species remains limited Accordingly, we measured sap flow velocity of Populus euphratica using the heat ratio method between 2012 and2014. Nocturnal stem sap flow was separated into nighttime and stem refilling using the ‘‘forecasted refilling''method. Nighttime transpiration was observed for each phenophase. The highest value was during the full foliation period but lowest during leaf expansion and defoliation periods. The contribution of nighttime transpiration to daytime transpiration was an average of 15% but this was comparatively higher during the defoliation period. Relationships between nighttime transpiration, vapor pressure deficits, and air temperatures were more closely associated than with wind speed in all phenophases. Moreover, we found that nighttime transpiration linearly correlated to vapour pressure deficit during the first and the full foliation periods, but nighttime transpiration showed exponential correlations to air temperatures during the same phenophases. Additionally, environmental drivers of transpiration were significantly different between nighttime and daytime(P \ 0.05). Driving forces behind nighttime transpiration were characterized by many factors, and integrated impacts between these multiple environmental factors were complex. Future studies should focus on these integrated impacts on nighttime transpiration, and the physiological mechanisms of nighttime transpiration should be investigated, given that this could also influence its occurrence and magnitude during different phenophases.
文摘AIM:To evaluate whether weekend or nighttime admission affects prognosis of peptic ulcer bleeding despite early endoscopy.METHODS:Retrospective data collection from four referral centers,all of which had a formal out-of-hours emergency endoscopy service,even at weekends.A total of 388 patients with bleeding peptic ulcers who were admitted via the emergency room between January 2007 and December 2009 were enrolled.Analyzed parameters included time from patients' arrival until endoscopy,mortality,rebleeding,need for surgery and length of hospital stay.RESULTS:The weekday and weekend admission groups comprised 326 and 62 patients,respectively.There were no significant differences in baseline characteristics between the two groups,except for younger age in the weekend group.Most patients (97%) had undergone early endoscopy,which resulted in a low mortality rate regardless of point of presentation (1.8% overall vs 1.6% on the weekend).The only outcome that was worse in the weekend group was a higher rate of rebleeding (12% vs 21%,P = 0.030).However,multivariate analysis revealed nighttime admission and a high Rockall score (≥ 6) as significant independent risk factors for rebleeding,rather than weekend admission.CONCLUSION:Early endoscopy for peptic ulcer bleeding can prevent the weekend effect,and nighttime admission was identified as a novel risk factor for rebleeding,namely the nighttime effect.
基金This work was supported by the Natural Science Foundation of Hubei Province(China)[grant number 2014CFB726]a Special Fund by Surveying and Mapping and Geo-information Research in the Public Interest(China)[grant number 201512026].
文摘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.
基金The Third Xinjiang Scientific Expedition Program(2021xjkk0905)GDAS Special Project of Science and Technology Development(2020GDASYL-20200301003)+2 种基金GDAS Special Project of Science and Technology Development(2020GDASYL-20200102002)National Natural Science Foundation of China(41501144)Project of Department of Natural Resources of Guangdong Province(GDZRZYKJ2022005)。
文摘This essay combines the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)nighttime light data and the Visible Infrared Imaging Radiometer Suite(VIIRS)nighttime light data into a“synthetic DMSP”dataset,from 1992 to 2020,to retrieve the spatio-temporal variations in energy-related carbon emissions in Xinjiang,China.Then,this paper analyzes several influencing factors for spatial differentiation of carbon emissions in Xinjiang with the application of geographical detector technique.Results reveal that(1)total carbon emissions continued to grow,while the growth rate slowed down in the past five years.(2)Large regional differences exist in total carbon emissions across various regions.Total carbon emissions of these regions in descending order are the northern slope of the Tianshan(Mountains)>the southern slope of the Tianshan>the three prefectures in southern Xinjiang>the northern part of Xinjiang.(3)Economic growth,population size,and energy consumption intensity are the most important factors of spatial differentiation of carbon emissions.The interaction between economic growth and population size as well as between economic growth and energy consumption intensity also enhances the explanatory power of carbon emissions’spatial differentiation.This paper aims to help formulate differentiated carbon reduction targets and strategies for cities in different economic development stages and those with different carbon intensities so as to achieve the carbon peak goals in different steps.
基金Under the auspices of National Natural Science Foundation of China(No.41171143,40771064)Program for New Century Excellent Talents in University(No.NCET-07-0398)Fundamental Research Funds for the Central Universities(No.lzu-jbky-2012-k35)
文摘Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment especially within built-up areas.In this study,ArcGIS 10,ENVI 4.5,and Visual FoxPro 6.0 were used to analyze the human impacts on vegetation in the built-up areas of 656Chinese cities from 1992 to 2010.Firstly,an existing algorithm was refined to extract the boundaries of the built-up areas based on the Defense Meteorological Satellite Program Operational Linescan System(DMSP_OLS)nighttime light data.This improved algorithm has the advantages of high accuracy and speed.Secondly,a mathematical model(Human impacts(HI))was constructed to measure the impacts of human factors on vegetation during rapid urbanization based on Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)and Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI.HI values greater than zero indicate relatively beneficial effects while values less than zero indicate proportionally adverse effects.The results were analyzed from four aspects:the size of cities(metropolises,large cities,medium-sized cities,and small cities),large regions(the eastern,central,western,and northeastern China),administrative divisions of China(provinces,autonomous regions,and municipalities)and vegetation zones(humid and semi-humid forest zone,semi-arid steppe zone,and arid desert zone).Finally,we discussed how human factors impacted on vegetation changes in the built-up areas.We found that urban planning policies and developmental stages impacted on vegetation changes in the built-up areas.The negative human impacts followed an inverted′U′shape,first rising and then falling with increase of urban scales.China′s national policies,social and economic development affected vegetation changes in the built-up areas.The findings can provide a scientific basis for municipal planning departments,a decision-making reference for government,and scientific guidance for sustainable development in China.
基金supported by the Major Projects of the Ministry of Science and Technology(No.2016YFB0501202)the Natural Science Foundation of Jilin Province,China(No.20170101164JC)
文摘In order to suppress complex mixing noise in low-illumination images for wide-area search of nighttime sea surface,a model based on total variation(TV)and split Bregman is proposed in this paper.A fidelity term based on L1 norm and a fidelity term based on L2 norm are designed considering the difference between various noise types,and the regularization mixed first-order TV and second-order TV are designed to balance the influence of details information such as texture and edge for sea surface image.The final detection result is obtained by using the high-frequency component solved from L1 norm and the low-frequency component solved from L2 norm through wavelet transform.The experimental results show that the proposed denoising model has perfect denoising performance for artificially degraded and low-illumination images,and the result of image quality assessment index for the denoising image is superior to that of the contrastive models.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences [grant numbers XDA2006010103 and XDA19070301]the National Natural Science Foundation of China [grant numbers 41830650,91737205,91637313,and 41661144043]
文摘Land surface temperature(LST)is an important variable for assessing climate change and related environmental impacts observed in recent decades.Regular monitoring of LST using satellite sensors such as MODIS has the advantage of global coverage,including topographically complex regions such as Nepal.In order to assess the climatic and environmental changes,daytime and nighttime LST trend analysis from 2000 to 2017 using Terra-MODIS monthly daytime and nighttime LST datasets at seasonal and annual scales over the territory of Nepal was performed.The magnitude of the trend was quantified using ordinary linear regression,while the statistical significance of the trend was identified by the Modified Mann—Kendall test.Our findings suggest that the nighttime LST in Nepal increased more prominently compared to the daytime LST,with more pronounced warming in the pre-monsoon and monsoon seasons.The annual nighttime LST increased at a rate of 0.05 K yr-1(p<0.01),while the daytime LST change was statistically insignificant.Spatial heterogeneity of the LST and LST change was observed both during the day and the night.The daytime LST remained fairly unchanged in large parts of Nepal,while a nighttime LST rise was dominant all across Nepal in the pre-monsoon and monsoon seasons.Our results on LST trends and their spatial distribution can facilitate a better understanding of regional climate changes.
基金the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0405)the National Natural Science Foundation of China(Grant No.41871185&41971270)。
文摘The Tibetan Plateau(TP)is undergoing rapid urbanization.To improve urban sustainability and construct eco-logical security barriers,it is essential to quantify the spatial patterns of urbanization level on the TP,but the existing studies on the topic have been limited by the lack of socioeconomic data.This study aims to quantify the urbanization level on the TP in 2018 with Luojia1-01(LJ1-01)high-resolution nighttime light(NTL)data.Specifically,the compounded night light index is used to quantify spatial patterns of urbanization level at mul-tiple scales.The results showed that the TP had a low overall urbanization level with a large internal difference.The urbanization level in the northeast,southeast and south of the TP was relatively high,forming three hotspots centered in Xining City,Lhasa City and Shangri-La City,while the urbanization level in the central and western regions was relatively low.The analysis of influencing factors,based on the random forest model,showed that transportation and topography were the main factors affecting the TP’s spatial patterns of urbanization level.The comparison analysis with socioeconomic statistics and traditional NTL data showed that LJ1-01 NTL data can be used to more effectively quantify the urbanization level since it is more advantageous for reflecting the spatial extent of urban land and describing the spatial structure of socioeconomic activities within urban areas.These advantages are attributed to the high spatial resolution of the data,appropriate imaging time and unaf-fected by saturation phenomena.Thus,the proposed LJ1-01 NTL-based urbanization level measurement method has the potential for wide applications around the world,especially in less-developed regions lacking statistical data.Using this method,we refined the measurement of the TP’s urbanization level in 2018 for multiple scales including the region,basin,prefecture and county levels,which provides basic information for the further urban sustainability research on the TP.
基金National Natural Science Foundation of China,No.41621061,No.41501092 Talents Training Program from the Beijing Municipal Commission of Education No.201500002012G058
文摘Comparing the city-size distribution at the urban agglomeration（UA） scale is important for understanding the processes of urban development. However, comparative studies of city-size distribution among China＇s three largest UAs, the Beijing-Tianjin-Hebei agglomeration（BTHA）, the Yangtze River Delta agglomeration（YRDA）, and the Pearl River Delta agglomeration（PRDA）, remain inadequate due to the limitation of data availability. Therefore, using urban data derived from time-series nighttime light data, the common characteristics and distinctive features of city-size distribution among the three UAs from 1992 to 2015 were compared by the Pareto regression and the rank clock method. We identified two common features. First, the city-size distribution became more even. The Pareto exponents increased by 0.17, 0.12, and 0.01 in the YRDA, BTHA, and PRDA, respectively. Second, the average ranks of small cities ascended, being 0.55, 0.08 and 0.04 in the three UAs, respectively. However, the average ranks of large and medium cities in the three UAs experienced different trajectories, which are closely related to the similarities and differences in the driving forces for the development of UAs. Place-based measures are encouraged to promote a coordinated development among cities of differing sizes in the three UAs.
基金supported by the Major Research Plan of the National Natural Science Foundation of China (91025024)the Key Project of the Chinese Academy of Sciences (KZZD-EW-04-05)the West Light Foundation of the Chinese Academy of Sciences
文摘Nighttime sap flow is a potentially important factor that affects whole-plant water balance and water-use efficiency （WUE）. Its functions include predawn disequilibrium between plant and soil water potentials as well as between the increments of oxygen supply and nutrient uptake. However, main factors that drive nighttime sap flow remain unclear, and researches related to the relationship between nighttime sap flow velocity and environmental factors are limited. Accordingly, we investigated the variations in the nighttime sap flow of Populus euphratica in a desert riparian forest of an extremely arid region, Northwest China. Results indicated that P. euphratica sap flow occurred throughout the night during the growing season because of the partial stomata opening. Nighttime sap flow for the P. euphratica forest accounted for 31%-47% of its daily sap flow during the growing season. The high value of nighttime sap flow could be the result of high stomatal conductance and could have significant implications for water budgets. Throughout the whole growing season, nighttime sap flow velocity of P. euphratica was positively correlated with the vapor pressure deficit （VPD）, air temperature and soil water content. We found that VPD and soil water content were the main driving factors for nighttime sap flow of P. euphratica.
基金Under the auspices of State Scholarship Fund of China Scholarship Council(No.201706320300)。
文摘Understanding the dynamics of urbanization is essential to the sustainable development of cities. Meanwhile the analysis of urban development can also provide scientifically and effective information for decision-making. With the long-term Defense Meteorological Satellite Program’s Operational Linescan System(DMSP/OLS) nighttime light images, a pixel level assessment of urbanization of China from 1992 to 2013 was conducted in this study, and the spatio-temporal dynamics and future trends of urban development were fully detected. The results showed that the urbanization and urban dynamics of China experienced drastic fluctuations from 1992 to 2013, especially for those in the coastal and metropolitan areas. From a regional perspective, it was found that the urban dynamics and increasing trends in North Coast China, East Coast China and South Coast China were much more stable and significant than that in other regions. Moreover, with the sustainability estimating of nighttime light dynamics, the regional agglomeration trends of urban regions were also detected. The light intensity in nearly 50% of lighted pixels may continuously decrease in the future, indicating a severe situation of urbanization within these regions. In this study, The results revealed in this study can provided a new insight in long time urbanization detecting and is thus beneficial to the better understanding of trends and dynamics of urban development.
文摘The research purpose is to accurately reveal the temporal and spatial law of the urban expansion of Changsha-Zhuzhou-Xiangtan, one of the seven major urban agglomeration areas in China, and provide decision-making basis for the future urban construction land layout and regional development policy-making. Based on the night lighting data (DMSP/OLS), this paper extracts the boundary of the urban construction land of Changsha-Zhuzhou-Xiangtan urban agglomeration from 1993 to 2017, and quantitatively studies the spatial and temporal characteristics of the expansion of the metropolitan area in the past 25 years according to the methods of spatial expansion analysis, center of gravity migration measurement, landscape pattern index, spatial autocorrelation, etc. The results show that: 1) it is scientific and feasible to extract urban agglomeration construction land by the method of auxiliary data comparison for the study of urban expansion;2) the expansion of regional space in Changsha-Zhuzhou-Xiangtan metropolitan area shows a trend of “weakening first and strengthening later”. The construction land keeps increasing, and the expansion form gradually changes from extensive type to intensive type;3) the center of gravity of the metropolitan area fluctuated and repeated in part during the past 25 years, but it was always located in the municipal district of Changsha city. The eastern region, mainly Changsha city, was still the core area of urban agglomeration expansion;4) strengthening the territorial space protection and control of ecological green core in the metropolitan area is a key measure for the high-quality development of urban agglomeration.
