Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal varia...Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River（SRYR） during the period 2002–2011 based on data from the Advanced Microwave Scanning Radiometer for the Earth Observing System（AMSR-E）. Moreover, the trends of onset dates and durations of the soil freeze-thaw cycles under different stages were also analyzed. Results showed that the thresholds of daytime and nighttime brightness temperatures of the freeze-thaw algorithm for the SRYR were 257.59 and 261.28 K, respectively. At the spatial scale, the daily frozen surface（DFS） area and the daily surface freeze-thaw cycle surface（DFTS） area decreased by 0.08% and 0.25%, respectively, and the daily thawed surface（DTS） area increased by 0.36%. At the temporal scale, the dates of the onset of thawing and complete thawing advanced by 3.10（±1.4） and 2.46（±1.4） days, respectively; and the dates of the onset of freezing and complete freezing were delayed by 0.9（±1.4） and 1.6（±1.1） days, respectively. The duration of thawing increased by 0.72（±0.21） day/a and the duration of freezing decreased by 0.52（±0.26） day/a. In conclusion, increases in the annual minimum temperature and winter air temperature are the main factors for the advanced thawing and delayed freezing and for the increase in the duration of thawing and the decrease in the duration of freezing in the SRYR.展开更多
This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-s...This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-strip area,real time download request,and stereoscopic request) and complex satellite actions,such as observe action and data download action,are considered in this paper. Through reasonable analysis of specialties and operational constraints of agile satellites in observing process,the mission scheduling model under multiple objective conditions is constructed. A genetic algorithm combined with heuristic rules is designed to solve problem. Genetic algorithm is designed to arrange user missions and heuristic rules are used to arrange satellite actions. Experiment results suggest that our algorithm works well for the agile Earth-observing satellite scheduling problem.展开更多
The primary objective of this paper is to present a comprehensive case study on monitoring wildfires in Nakhon Nayok, Thailand, utilizing Earth observation platforms. This initiative project has been undertaken by the...The primary objective of this paper is to present a comprehensive case study on monitoring wildfires in Nakhon Nayok, Thailand, utilizing Earth observation platforms. This initiative project has been undertaken by the Excellence Center of Space Technology and Research (ECSTAR), in partnership with its spin-off startup, TeroSpace. The study aims to provide an in-depth analysis of the wildfire incidents in the region, utilizing advanced technologies such as satellite imagery and data analytics, and to identify ways to improve future wildfire management. In particular, the paper focuses on the wildfires including thermal area comparison that ravaged the land in Nakhon Nayok Province in central Thailand from March to April 18th, 2023. To conduct this study, the ECSTAR-TeroSpace analytic team utilized satellite images from Earth observation platforms: MODIS and Sentinel-2A. By presenting this case study, this paper contributes to the broader understanding of how to monitor and manage wildfires in a changing climate. The findings of this study underscore the importance of proactive and collaborative efforts in mitigating the negative impacts of wildfires in Nakhon Nayok and other regions in Thailand.展开更多
Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currentl...Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.展开更多
Humankind is facing unprecedented global environmental and social challenges in terms of food,water and energy security,resilience to natural hazards,etc.To address these challenges,international organizations have de...Humankind is facing unprecedented global environmental and social challenges in terms of food,water and energy security,resilience to natural hazards,etc.To address these challenges,international organizations have defined a list of policy actions to be achieved in a relatively short and medium-term timespan.The development and use of knowledge platforms is key in helping the decision-making process to take significant decisions(providing the best available knowledge)and avoid potentially negative impacts on society and the environment.Such knowledge platforms must build on the recent and next coming digital technologies that have transformed society–including the science and engineering sectors.Big Earth Data(BED)science aims to provide the methodologies and instruments to generate knowledge from numerous,complex,and diverse data sources.BED science requires the development of Geoscience Digital Ecosystems(GEDs),which bank on the combined use of fundamental technology units(i.e.big data,learning-driven artificial intelligence,and network-based computing platform)to enable the development of more detailed knowledge to observe and test planet Earth as a whole.This manuscript contributes to the BED science research domain,by presenting the Virtual Earth Cloud:a multi-cloud framework to support GDE implementation and generate knowledge on environmental and social sustainability.展开更多
针对地球观测领域规模最大的政府间国际组织“地球观测组织(Group on Earth Observations)”提出的“全球综合地球观测系统”这一概念,梳理了其实现和建设的现状,分析了其具有供给导向、元数据质量不高、无法直接支撑决策和行动等局限...针对地球观测领域规模最大的政府间国际组织“地球观测组织(Group on Earth Observations)”提出的“全球综合地球观测系统”这一概念,梳理了其实现和建设的现状,分析了其具有供给导向、元数据质量不高、无法直接支撑决策和行动等局限性。结合我国参加地球观测组织的计划和成果,详细阐述了面向全球服务的中国综合地球观测系统的内涵,并基于全球综合地球观测系统的优势与不足,提出了中国综合地球观测系统平台的系统架构,另外就优质数据集研制、信息专题服务以及数据应急响应3个案例阐述了中国综合地球观测系统平台的实践及成效。展开更多
Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and...Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and chemical parameters on a global scale.Earth observation data has the 4V features(volume,variety,veracity,and velocity) of big data that are suitable for climate change research.Moreover,the large amount of data available from scientific satellites plays an important role.This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research,such as synchronous satelliteeaerialeground observation experiments,which provide extremely large and abundant datasets; Earth observational sensitive factors(e.g.,glaciers,lakes,vegetation,radiation,and urbanization); and global environmental change information and simulation systems.With the era of global environment change dawning,Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking.Inevitably,Earth observation big data will encounter opportunities and challenges brought about by global climate change.展开更多
Human beings are now facing global and regional sustainable development challenges.In China, Earth observation data play a fundamental role in Earth system science research. The support given by Earth observation data...Human beings are now facing global and regional sustainable development challenges.In China, Earth observation data play a fundamental role in Earth system science research. The support given by Earth observation data is required by many studies, including those on Earth's limited natural resources, the rapid development of economic and social needs, global change, extreme events, food security, water resources, sustainable economic and urban development, and emergency response. Application operation systems in many ministries and departments in China have entered a stage of sustainable development, and the State Key Project of High-Resolution Earth Observation Systems has been progressing since 2006. Earth observation technology in China has entered a period of rapid development.展开更多
基金supported by the National Science and Technology Support Plan of China (2015BAD07B02)
文摘Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River（SRYR） during the period 2002–2011 based on data from the Advanced Microwave Scanning Radiometer for the Earth Observing System（AMSR-E）. Moreover, the trends of onset dates and durations of the soil freeze-thaw cycles under different stages were also analyzed. Results showed that the thresholds of daytime and nighttime brightness temperatures of the freeze-thaw algorithm for the SRYR were 257.59 and 261.28 K, respectively. At the spatial scale, the daily frozen surface（DFS） area and the daily surface freeze-thaw cycle surface（DFTS） area decreased by 0.08% and 0.25%, respectively, and the daily thawed surface（DTS） area increased by 0.36%. At the temporal scale, the dates of the onset of thawing and complete thawing advanced by 3.10（±1.4） and 2.46（±1.4） days, respectively; and the dates of the onset of freezing and complete freezing were delayed by 0.9（±1.4） and 1.6（±1.1） days, respectively. The duration of thawing increased by 0.72（±0.21） day/a and the duration of freezing decreased by 0.52（±0.26） day/a. In conclusion, increases in the annual minimum temperature and winter air temperature are the main factors for the advanced thawing and delayed freezing and for the increase in the duration of thawing and the decrease in the duration of freezing in the SRYR.
基金Sponsored by the National Natural Science Foundation of China(Grant No.70601035 and 70801062)
文摘This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-strip area,real time download request,and stereoscopic request) and complex satellite actions,such as observe action and data download action,are considered in this paper. Through reasonable analysis of specialties and operational constraints of agile satellites in observing process,the mission scheduling model under multiple objective conditions is constructed. A genetic algorithm combined with heuristic rules is designed to solve problem. Genetic algorithm is designed to arrange user missions and heuristic rules are used to arrange satellite actions. Experiment results suggest that our algorithm works well for the agile Earth-observing satellite scheduling problem.
文摘The primary objective of this paper is to present a comprehensive case study on monitoring wildfires in Nakhon Nayok, Thailand, utilizing Earth observation platforms. This initiative project has been undertaken by the Excellence Center of Space Technology and Research (ECSTAR), in partnership with its spin-off startup, TeroSpace. The study aims to provide an in-depth analysis of the wildfire incidents in the region, utilizing advanced technologies such as satellite imagery and data analytics, and to identify ways to improve future wildfire management. In particular, the paper focuses on the wildfires including thermal area comparison that ravaged the land in Nakhon Nayok Province in central Thailand from March to April 18th, 2023. To conduct this study, the ECSTAR-TeroSpace analytic team utilized satellite images from Earth observation platforms: MODIS and Sentinel-2A. By presenting this case study, this paper contributes to the broader understanding of how to monitor and manage wildfires in a changing climate. The findings of this study underscore the importance of proactive and collaborative efforts in mitigating the negative impacts of wildfires in Nakhon Nayok and other regions in Thailand.
基金supported by National Natural Science Foundation of China,China(No.42004016)HuBei Natural Science Fund,China(No.2020CFB329)+1 种基金HuNan Natural Science Fund,China(No.2023JJ60559,2023JJ60560)the State Key Laboratory of Geodesy and Earth’s Dynamics self-deployment project,China(No.S21L6101)。
文摘Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.
基金The research leading to these results benefited from funding by the European Union's Horizon 2020 Framework Programme research and innovation programme[under grant agreements:n.689443(ERA-PLANET),n.777536(EOSC-hub),n.776136(EDGE),n.34538(EO Value),n.101039118(GPP)]by the European Space Agency[under ESA Contracts:n.4000123005/18/IT/CGD(DAB4EDGE)and n.4000138128/22/I/AG(DAB4GPP)]European Commission CNECT(grant n.35713).
文摘Humankind is facing unprecedented global environmental and social challenges in terms of food,water and energy security,resilience to natural hazards,etc.To address these challenges,international organizations have defined a list of policy actions to be achieved in a relatively short and medium-term timespan.The development and use of knowledge platforms is key in helping the decision-making process to take significant decisions(providing the best available knowledge)and avoid potentially negative impacts on society and the environment.Such knowledge platforms must build on the recent and next coming digital technologies that have transformed society–including the science and engineering sectors.Big Earth Data(BED)science aims to provide the methodologies and instruments to generate knowledge from numerous,complex,and diverse data sources.BED science requires the development of Geoscience Digital Ecosystems(GEDs),which bank on the combined use of fundamental technology units(i.e.big data,learning-driven artificial intelligence,and network-based computing platform)to enable the development of more detailed knowledge to observe and test planet Earth as a whole.This manuscript contributes to the BED science research domain,by presenting the Virtual Earth Cloud:a multi-cloud framework to support GDE implementation and generate knowledge on environmental and social sustainability.
文摘针对地球观测领域规模最大的政府间国际组织“地球观测组织(Group on Earth Observations)”提出的“全球综合地球观测系统”这一概念,梳理了其实现和建设的现状,分析了其具有供给导向、元数据质量不高、无法直接支撑决策和行动等局限性。结合我国参加地球观测组织的计划和成果,详细阐述了面向全球服务的中国综合地球观测系统的内涵,并基于全球综合地球观测系统的优势与不足,提出了中国综合地球观测系统平台的系统架构,另外就优质数据集研制、信息专题服务以及数据应急响应3个案例阐述了中国综合地球观测系统平台的实践及成效。
基金funded by the International Cooperation and Exchanges National Natural Science Foundation of China (41120114001)
文摘Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and chemical parameters on a global scale.Earth observation data has the 4V features(volume,variety,veracity,and velocity) of big data that are suitable for climate change research.Moreover,the large amount of data available from scientific satellites plays an important role.This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research,such as synchronous satelliteeaerialeground observation experiments,which provide extremely large and abundant datasets; Earth observational sensitive factors(e.g.,glaciers,lakes,vegetation,radiation,and urbanization); and global environmental change information and simulation systems.With the era of global environment change dawning,Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking.Inevitably,Earth observation big data will encounter opportunities and challenges brought about by global climate change.
文摘Human beings are now facing global and regional sustainable development challenges.In China, Earth observation data play a fundamental role in Earth system science research. The support given by Earth observation data is required by many studies, including those on Earth's limited natural resources, the rapid development of economic and social needs, global change, extreme events, food security, water resources, sustainable economic and urban development, and emergency response. Application operation systems in many ministries and departments in China have entered a stage of sustainable development, and the State Key Project of High-Resolution Earth Observation Systems has been progressing since 2006. Earth observation technology in China has entered a period of rapid development.
