Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic demand and limited airspace capacity.As air traffic is associated with complex air transport systems,delays can be magni...Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic demand and limited airspace capacity.As air traffic is associated with complex air transport systems,delays can be magnified and propagated throughout these systems,resulting in the emergent behavior known as delay propagation.An understanding of delay propagation dynamics is pertinent to modern air traffic management.In this work,we present a complex network perspective of delay propagation dynamics.Specifically,we model air traffic scenarios using spatial–temporal networks with airports as the nodes.To establish the dynamic edges between the nodes,we develop a delay propagation method and apply it to a given set of air traffic schedules.Based on the constructed spatial-temporal networks,we suggest three metrics-magnitude,severity,and speed-to gauge delay propagation dynamics.To validate the effectiveness of the proposed method,we carry out case studies on domestic flights in the Southeastern Asia region(SAR)and the United States.Experiments demonstrate that the propagation magnitude in terms of the number of flights affected by delay propagation and the amount of propagated delays for the US traffic are respectively five and ten times those of the SAR.Experiments further reveal that the propagation speed for US traffic is eight times faster than that of the SAR.The delay propagation dynamics reveal that about six hub airports in the SAR have significant propagated delays,while the situation in the United States is considerably worse,with a corresponding number of around 16.This work provides a potent tool for tracing the evolution of air traffic delays.展开更多
Based on data on taxed-cropland area and on the number of households in historical documents, a probabilistic model of cropland distribution and a cropland area allocation model were designed and validated. Cropland a...Based on data on taxed-cropland area and on the number of households in historical documents, a probabilistic model of cropland distribution and a cropland area allocation model were designed and validated. Cropland areas for the years AD976, 997, 1066, and 1078 were estimated at the level of Lu（an administrative region of the Northern Song Dynasty）. The results indicated that（1） the cropland area of the whole study region for AD976, 997, 1066, and 1078 was about 468.27 million mu（a Chinese unit of area, with1 mu=666.7m2）, 495.53 million mu, 697.65 million mu, and 731.94 million mu, respectively. The fractional cropland area（FCA） increased from 10.7% to 16.8%, and the per capita cropland area decreased from 15.7 mu to 8.4 mu.（2） With regard to the cropland spatial pattern, the FCA of the southeast, north, and southwest regions of the Northern Song territory increased by 12.0%, 5.2%, and 1.2%, respectively. The FCA of some regions in the Yangtze River Plain increased to greater than 40%, and the FCA of the North China Plain increased to greater than 20%. However, the FCA of the southwest region（except for the Chengdu Plain） in the Northern Song territory was less than 6%.（3） There were 84.2% Lus whose absolute relative error was smaller than 20% in the mid Northern Song Dynasty. The validation results indicate that our models are reasonable and that the results of reconstruction are credible.展开更多
Vegetation plays an important role in global or regional environmental change.In this study,the spatial–temporal variations of NDVI and its response to climate in China and its seven sub-regions were investigated bas...Vegetation plays an important role in global or regional environmental change.In this study,the spatial–temporal variations of NDVI and its response to climate in China and its seven sub-regions were investigated based on MODIS NDVI data,ERA5-land precipitation(PRE)and temperature(TEM)data from 2001 to 2020.The inter-annual growth rate of NDVI in China was 0.0021/yr in the past 20 years.The inter-annual growth rates of NDVI in seven sub-regions had significant differences at regional or seasonal scales.The ratio of improved vegetation area to the total studied area reached about 70%.In summer,vegetation degradation was concentrated in East China and Southwest China.The vegetation in Central China and South China improved more obviously in autumn than in the other seasons.The vegetation of Northeast China had a remarkable degradation in autumn and winter,especially in winter.The influence degree of PRE(q=0.54,P<0.01)was greater than that of TEM(q=0.27,P<0.01)in the control of the spatial distribution of NDVI.The interaction influence degree q of PRE∩TEM was about 0.71 in the last 20 years.However,the PRE and TEM played different roles in vegetation growth in seven sub-regions.展开更多
Mixed use has been extensively applied as an urban planning principle and hinders the study of single urban functions.To address this problem,it is worth decomposing the mixed use.Inspired by the concept of spectral u...Mixed use has been extensively applied as an urban planning principle and hinders the study of single urban functions.To address this problem,it is worth decomposing the mixed use.Inspired by the concept of spectral unmixing in remote sensing applications,this paper proposes a framework for mixed-use decomposition based on big geo-data.Mixeduse decomposition in terms of human activities differs from traditional land use research,and it is more reasonable to infer the actual urban function of land.The framework consists of four steps,namely temporal activity signature extraction,urban function base curve extraction,mixeduse decomposition,and result validation.First,the temporal activity signatures(TASs)of each zone are extracted as the proxy of human activity patterns.Second,the diurnal TASs of routine activities are extracted as urban function base curves(i.e.endmembers).Third,a linear decomposition model is used to decompose the mixed use and obtain multiple results(urban function composition,dynamic activity proportions,and the mixing index).Finally,result validation strategies are concluded.This framework offers method extensibility and has few requirements for the input data.It is validated by means of a case study of Beijing,based on a social media check-in dataset.展开更多
There is a critical need to develop a means for fast,task-driven discovery of geospatial data found in geoportals.Existing geoportals,however,only provide metadata-based means for discovery,with little support for tas...There is a critical need to develop a means for fast,task-driven discovery of geospatial data found in geoportals.Existing geoportals,however,only provide metadata-based means for discovery,with little support for task-driven discovery,especially when considering spatial–temporal awareness.To address this gap,this paper presents a Case-Based Reasoning-supported Geospatial Data Discovery(CBR-GDD)method and implementation that accesses geospatial data by tasks.The advantages of the CBR-GDD approach is that it builds an analogue reasoning process that provides an internal mechanism bridging tasks and geospatial data with spatial–temporal awareness,thus providing solutions based on past tasks.The CBR-GDD approach includes a set of algorithms that were successfully implemented via three components as an extension of geoportals:ontology-enhanced knowledge base,similarity assessment model,and case retrieval nets.A set of experiments and case studies validate the CBR-GDD approach and application,and demonstrate its efficiency.展开更多
The ecological systems services or multi-functionality of paddy rice cultivation are critical to the functioning of the Earth’s life-support system.We estimated the ecosystem services value(ESV)of paddy rice during 1...The ecological systems services or multi-functionality of paddy rice cultivation are critical to the functioning of the Earth’s life-support system.We estimated the ecosystem services value(ESV)of paddy rice during 1980-2014 across China.The results indicated that the ESV of the paddy field in China showed an upward trend during this period.The share of ESV on CO_(2)sequestration was the highest,followed by ESV on temperature cooling and greenhouse gas(GHG)emission.The yield-scaled ESVs of ZonesⅡ(southern rice-upland crops rotation regions)andⅢ(southern double rice production regions)were similar and significantly higher than the ESVs of ZonesⅠ(northeastern single rice production regions)and IV(Southwest rice-upland crops rotation regions).Between 1980 and 2014,the ESV of each region increased to varying degrees,except for the ESVs of Guangxi,Zhejiang,Fujian,and Guangdong.Such effects suggest the existence of a significant spatial-temporal variation in the total amount,structure,and density of ESV of paddy fields in China,which can further guide the development of future options for the adaptation of healthy rice production in China.展开更多
Climate drives ecosystem processes and impacts biodiversity.Biodiversity patterns over large areas,such as Canada’s boreal,can be monitored using indirect indicators derived from remotely sensed imagery.In this paper...Climate drives ecosystem processes and impacts biodiversity.Biodiversity patterns over large areas,such as Canada’s boreal,can be monitored using indirect indicators derived from remotely sensed imagery.In this paper,we characterized the historical space–time relationships between climate and a suite of indirect indicators of biodiversity,known as the Dynamic Habitat Index(DHI)to identify where climate variability is co-occurring with changes in biodiversity indicators.We represented biodiversity using three indirect indicators generated from 1987 to 2007 National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer images.By quantifying and clustering temporal variability in climate data,we defined eight homogeneous climate variability zones,where we then analyzed the DHI.Results identified unique areas of change in climate,such as the Hudson Plains,that explain significant variations in DHI.Past variability in temperatures and growing season index had a strong influence on observed vegetation productivity and seasonality changes throughout Canada’s boreal.Variation in precipitation,for most of the area,was not associated with DHI changes.The methodology presented here enables assessment of spatial–temporal relationships between biodiversity and climate variability and characterizes distinctive zones of variation that may be used for prioritization and planning to ensure long-term biodiversity conservation in Canada.展开更多
生物质燃烧向大气中排放大量痕量气体和颗粒物,源排放清单是深入研究生物质燃烧环境气候效应的重要基础数据。利用全球火排放数据库GFED(Global Fire Emissions Database)、NCAR全球火排放清单FINN(Fire INventory from NCAR)和中国露...生物质燃烧向大气中排放大量痕量气体和颗粒物,源排放清单是深入研究生物质燃烧环境气候效应的重要基础数据。利用全球火排放数据库GFED(Global Fire Emissions Database)、NCAR全球火排放清单FINN(Fire INventory from NCAR)和中国露天生物质燃烧排放清单MEIC(Multi-resolution Emission Inventory for China),对2008~2017年中国地区生物质燃烧源排放的空间分布、季节和年际变化特征以及不同清单间的异同进行分析研究。3个清单都显示生物质燃烧释放的黑碳(BC)、有机碳(OC)、空气动力学粒径小于2.5μm的颗粒物(PM2.5)和一氧化碳(CO)在中国东北、长江和黄河下游之间地区和中国南方的排放量较高,与我国的主要农作物产地和森林地区分布一致。FINN清单排放量在华南地区与西南地区比其他两个清单高,而GFED清单排放量在长三角地区比其他两个清单排放量高。中国地区平均生物质燃烧排放量在春季出现峰值,而在不同的生物质燃烧地区峰值出现的季节不同,与各地农作物播种、收获时节和农耕习惯不同有关。2008~2017年,中国地区年平均生物质燃烧排放量的峰值主要出现在2014年,但各地区峰值出现的年份明显不同,东北、华中/东、华南和西南地区分别在2015年、2013年、2008年和2010年排放量达到最大。对于BC、OC和PM2.5,GFED和MEIC清单中的排放量比较接近,而FINN中的排放量是GFED和MEIC中的2~3倍;3个清单中CO的排放量比较接近。2014年生物质燃烧源排放与人为源排放的对比分析表明,所有物种中,生物质燃烧排放的OC和PM2.5相对于人为源排放量占比最大,3个清单中占比分别为9%~24%和5%~16%,说明生物质燃烧排放的OC和一次PM2.5是中国气溶胶的重要来源。展开更多
This article applies a Markov chain method to compute the probability of residential fire occurrence based on past fire history. Fitted with the fire incidence data gathered over a period of 10 years in Melbourne, Aus...This article applies a Markov chain method to compute the probability of residential fire occurrence based on past fire history. Fitted with the fire incidence data gathered over a period of 10 years in Melbourne, Australia,the spatially-integrated fire risk model predicts the likely occurrence of fire incidents using space and time as key model parameters. The mapped probabilities of fire occurrence across Melbourne show a city-centric spatial pattern where inner-city areas are relatively more vulnerable to a fire than outer suburbia. Fire risk reduces in a neighborhood when there is at least one fire in the last1 month. The results show that the time threshold of reduced fire risk after the fire occurrence is about 2 months.Fire risk increases when there is no fire in the last 1 month within the third-order neighborhood(within 5 km). A fire that occurs within this distance range, however, has no significant effect on reducing fire risk level within the neighborhood. The spatial–temporal dependencies of fire risk provide new empirical evidence useful for fire agencies to effectively plan and implement geo-targeted fire risk interventions and education programs to mitigate potential fire risk in areas where and when they are most needed.展开更多
基金This work was supported by SUG Research Grant M4082126.050 by the School of Mechanical and Aerospace Engineering(MAE),Nanyang Technological University(NTU),SingaporeNTU-CAAS Research Grant M4062429.052 by the ATM Research Institute,School of MAE,NTU,Singapore.
文摘Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic demand and limited airspace capacity.As air traffic is associated with complex air transport systems,delays can be magnified and propagated throughout these systems,resulting in the emergent behavior known as delay propagation.An understanding of delay propagation dynamics is pertinent to modern air traffic management.In this work,we present a complex network perspective of delay propagation dynamics.Specifically,we model air traffic scenarios using spatial–temporal networks with airports as the nodes.To establish the dynamic edges between the nodes,we develop a delay propagation method and apply it to a given set of air traffic schedules.Based on the constructed spatial-temporal networks,we suggest three metrics-magnitude,severity,and speed-to gauge delay propagation dynamics.To validate the effectiveness of the proposed method,we carry out case studies on domestic flights in the Southeastern Asia region(SAR)and the United States.Experiments demonstrate that the propagation magnitude in terms of the number of flights affected by delay propagation and the amount of propagated delays for the US traffic are respectively five and ten times those of the SAR.Experiments further reveal that the propagation speed for US traffic is eight times faster than that of the SAR.The delay propagation dynamics reveal that about six hub airports in the SAR have significant propagated delays,while the situation in the United States is considerably worse,with a corresponding number of around 16.This work provides a potent tool for tracing the evolution of air traffic delays.
基金National Natural Science Foundation of China,No.41271227 The Special Program for Basic Work of the Ministry of Science and Technology,China,No.2014FY210900
文摘Based on data on taxed-cropland area and on the number of households in historical documents, a probabilistic model of cropland distribution and a cropland area allocation model were designed and validated. Cropland areas for the years AD976, 997, 1066, and 1078 were estimated at the level of Lu（an administrative region of the Northern Song Dynasty）. The results indicated that（1） the cropland area of the whole study region for AD976, 997, 1066, and 1078 was about 468.27 million mu（a Chinese unit of area, with1 mu=666.7m2）, 495.53 million mu, 697.65 million mu, and 731.94 million mu, respectively. The fractional cropland area（FCA） increased from 10.7% to 16.8%, and the per capita cropland area decreased from 15.7 mu to 8.4 mu.（2） With regard to the cropland spatial pattern, the FCA of the southeast, north, and southwest regions of the Northern Song territory increased by 12.0%, 5.2%, and 1.2%, respectively. The FCA of some regions in the Yangtze River Plain increased to greater than 40%, and the FCA of the North China Plain increased to greater than 20%. However, the FCA of the southwest region（except for the Chengdu Plain） in the Northern Song territory was less than 6%.（3） There were 84.2% Lus whose absolute relative error was smaller than 20% in the mid Northern Song Dynasty. The validation results indicate that our models are reasonable and that the results of reconstruction are credible.
基金funded by the National Natural Science Foundation[grant number 71971002]the Anhui Provincial Natural Science Foundation[grant number 2108085QD154]+1 种基金the Major Science and Technology Project of Anhui Province[grant number 202003a06020016]the Key R&D Project of Anhui Province[grant number 202004a07020050].
文摘Vegetation plays an important role in global or regional environmental change.In this study,the spatial–temporal variations of NDVI and its response to climate in China and its seven sub-regions were investigated based on MODIS NDVI data,ERA5-land precipitation(PRE)and temperature(TEM)data from 2001 to 2020.The inter-annual growth rate of NDVI in China was 0.0021/yr in the past 20 years.The inter-annual growth rates of NDVI in seven sub-regions had significant differences at regional or seasonal scales.The ratio of improved vegetation area to the total studied area reached about 70%.In summer,vegetation degradation was concentrated in East China and Southwest China.The vegetation in Central China and South China improved more obviously in autumn than in the other seasons.The vegetation of Northeast China had a remarkable degradation in autumn and winter,especially in winter.The influence degree of PRE(q=0.54,P<0.01)was greater than that of TEM(q=0.27,P<0.01)in the control of the spatial distribution of NDVI.The interaction influence degree q of PRE∩TEM was about 0.71 in the last 20 years.However,the PRE and TEM played different roles in vegetation growth in seven sub-regions.
基金This work was supported by the National Key R&D Program of China[grant number 2017YFB0503602]the National Natural Science Foundation of China[grant numbers 41830645,41625003,and 41771425]Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA19040402].
文摘Mixed use has been extensively applied as an urban planning principle and hinders the study of single urban functions.To address this problem,it is worth decomposing the mixed use.Inspired by the concept of spectral unmixing in remote sensing applications,this paper proposes a framework for mixed-use decomposition based on big geo-data.Mixeduse decomposition in terms of human activities differs from traditional land use research,and it is more reasonable to infer the actual urban function of land.The framework consists of four steps,namely temporal activity signature extraction,urban function base curve extraction,mixeduse decomposition,and result validation.First,the temporal activity signatures(TASs)of each zone are extracted as the proxy of human activity patterns.Second,the diurnal TASs of routine activities are extracted as urban function base curves(i.e.endmembers).Third,a linear decomposition model is used to decompose the mixed use and obtain multiple results(urban function composition,dynamic activity proportions,and the mixing index).Finally,result validation strategies are concluded.This framework offers method extensibility and has few requirements for the input data.It is validated by means of a case study of Beijing,based on a social media check-in dataset.
基金supported by the National Key Research and Development Program of China[grant number 2016YFB0502204]Opening research fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing[grant number(16)Key04]+1 种基金Opening fund of Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation(Guangxi Teachers Education University)[grant number 2015GXESPKF02]National Natural Science Foundation of China[grant number 41401524].
文摘There is a critical need to develop a means for fast,task-driven discovery of geospatial data found in geoportals.Existing geoportals,however,only provide metadata-based means for discovery,with little support for task-driven discovery,especially when considering spatial–temporal awareness.To address this gap,this paper presents a Case-Based Reasoning-supported Geospatial Data Discovery(CBR-GDD)method and implementation that accesses geospatial data by tasks.The advantages of the CBR-GDD approach is that it builds an analogue reasoning process that provides an internal mechanism bridging tasks and geospatial data with spatial–temporal awareness,thus providing solutions based on past tasks.The CBR-GDD approach includes a set of algorithms that were successfully implemented via three components as an extension of geoportals:ontology-enhanced knowledge base,similarity assessment model,and case retrieval nets.A set of experiments and case studies validate the CBR-GDD approach and application,and demonstrate its efficiency.
基金supported by the Natural Science Foundation of Zhejiang,China(Q21C130007)the National Key Research and Development Program of China(2016YFD0300210)。
文摘The ecological systems services or multi-functionality of paddy rice cultivation are critical to the functioning of the Earth’s life-support system.We estimated the ecosystem services value(ESV)of paddy rice during 1980-2014 across China.The results indicated that the ESV of the paddy field in China showed an upward trend during this period.The share of ESV on CO_(2)sequestration was the highest,followed by ESV on temperature cooling and greenhouse gas(GHG)emission.The yield-scaled ESVs of ZonesⅡ(southern rice-upland crops rotation regions)andⅢ(southern double rice production regions)were similar and significantly higher than the ESVs of ZonesⅠ(northeastern single rice production regions)and IV(Southwest rice-upland crops rotation regions).Between 1980 and 2014,the ESV of each region increased to varying degrees,except for the ESVs of Guangxi,Zhejiang,Fujian,and Guangdong.Such effects suggest the existence of a significant spatial-temporal variation in the total amount,structure,and density of ESV of paddy fields in China,which can further guide the development of future options for the adaptation of healthy rice production in China.
基金This research was supported by GEOIDE(GEOmatics for Informed DEcisions)the Ivey Foundationand the Canada Program of The Nature Conservancy.The project was conducted at the universities of British Columbia and Victoria,and was undertaken as an extension of the‘BioSpace:Biodiversity monitoring with Earth Observation data’project jointly funded by the Canadian Space Agency(CSA)Government Related Initiatives Program(GRIP),Canadian Forest Service(CFS)Pacific Forestry Centre(PFC),and the University of British Columbia(UBC).We thank Chuck Rumsey,Steve Cumming,Kim Lisgo,Pierre Vernier,Ryan Powers and Fiona Schmiege low for support and engaging discussions throughout the project.
文摘Climate drives ecosystem processes and impacts biodiversity.Biodiversity patterns over large areas,such as Canada’s boreal,can be monitored using indirect indicators derived from remotely sensed imagery.In this paper,we characterized the historical space–time relationships between climate and a suite of indirect indicators of biodiversity,known as the Dynamic Habitat Index(DHI)to identify where climate variability is co-occurring with changes in biodiversity indicators.We represented biodiversity using three indirect indicators generated from 1987 to 2007 National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer images.By quantifying and clustering temporal variability in climate data,we defined eight homogeneous climate variability zones,where we then analyzed the DHI.Results identified unique areas of change in climate,such as the Hudson Plains,that explain significant variations in DHI.Past variability in temperatures and growing season index had a strong influence on observed vegetation productivity and seasonality changes throughout Canada’s boreal.Variation in precipitation,for most of the area,was not associated with DHI changes.The methodology presented here enables assessment of spatial–temporal relationships between biodiversity and climate variability and characterizes distinctive zones of variation that may be used for prioritization and planning to ensure long-term biodiversity conservation in Canada.
文摘生物质燃烧向大气中排放大量痕量气体和颗粒物,源排放清单是深入研究生物质燃烧环境气候效应的重要基础数据。利用全球火排放数据库GFED(Global Fire Emissions Database)、NCAR全球火排放清单FINN(Fire INventory from NCAR)和中国露天生物质燃烧排放清单MEIC(Multi-resolution Emission Inventory for China),对2008~2017年中国地区生物质燃烧源排放的空间分布、季节和年际变化特征以及不同清单间的异同进行分析研究。3个清单都显示生物质燃烧释放的黑碳(BC)、有机碳(OC)、空气动力学粒径小于2.5μm的颗粒物(PM2.5)和一氧化碳(CO)在中国东北、长江和黄河下游之间地区和中国南方的排放量较高,与我国的主要农作物产地和森林地区分布一致。FINN清单排放量在华南地区与西南地区比其他两个清单高,而GFED清单排放量在长三角地区比其他两个清单排放量高。中国地区平均生物质燃烧排放量在春季出现峰值,而在不同的生物质燃烧地区峰值出现的季节不同,与各地农作物播种、收获时节和农耕习惯不同有关。2008~2017年,中国地区年平均生物质燃烧排放量的峰值主要出现在2014年,但各地区峰值出现的年份明显不同,东北、华中/东、华南和西南地区分别在2015年、2013年、2008年和2010年排放量达到最大。对于BC、OC和PM2.5,GFED和MEIC清单中的排放量比较接近,而FINN中的排放量是GFED和MEIC中的2~3倍;3个清单中CO的排放量比较接近。2014年生物质燃烧源排放与人为源排放的对比分析表明,所有物种中,生物质燃烧排放的OC和PM2.5相对于人为源排放量占比最大,3个清单中占比分别为9%~24%和5%~16%,说明生物质燃烧排放的OC和一次PM2.5是中国气溶胶的重要来源。
文摘This article applies a Markov chain method to compute the probability of residential fire occurrence based on past fire history. Fitted with the fire incidence data gathered over a period of 10 years in Melbourne, Australia,the spatially-integrated fire risk model predicts the likely occurrence of fire incidents using space and time as key model parameters. The mapped probabilities of fire occurrence across Melbourne show a city-centric spatial pattern where inner-city areas are relatively more vulnerable to a fire than outer suburbia. Fire risk reduces in a neighborhood when there is at least one fire in the last1 month. The results show that the time threshold of reduced fire risk after the fire occurrence is about 2 months.Fire risk increases when there is no fire in the last 1 month within the third-order neighborhood(within 5 km). A fire that occurs within this distance range, however, has no significant effect on reducing fire risk level within the neighborhood. The spatial–temporal dependencies of fire risk provide new empirical evidence useful for fire agencies to effectively plan and implement geo-targeted fire risk interventions and education programs to mitigate potential fire risk in areas where and when they are most needed.
