CASEarth satellite is the first space Earth science satellite produced by the Chinese Academy of Sciences.The satellite has three payloads:high-definition Thermal Infrared Spectrometer(TIS),highdefinition Glimmer Imag...CASEarth satellite is the first space Earth science satellite produced by the Chinese Academy of Sciences.The satellite has three payloads:high-definition Thermal Infrared Spectrometer(TIS),highdefinition Glimmer Imager for Urbanization(GIU),and high-definition Multispectral Imager for Inshore(MII).These payloads are used to explore the urbanization level and residential layout,the coastal ecosystem,and new methods and approaches of environmental detection during night-time and even under conditions of polar aurora and provide scientific evidence for the refined depiction of human traces.The CASEarth satellite can provide space observation data for A Project on Big Earth Data Science Engineering as well as scientific and application studies inside and outside China.展开更多
Antarctica plays an important role in research on global change,and its unique geography,ocean,climate,and environment pro-vide an ideal place for humankind to understand Earth’s evolution.Remote sensing provides an ...Antarctica plays an important role in research on global change,and its unique geography,ocean,climate,and environment pro-vide an ideal place for humankind to understand Earth’s evolution.Remote sensing provides an effective means to monitor and observe large-scale processes on the continent.Synthetic aperture radar(SAR)in particular provides the capability for all-weather Earth observation.The Sentinel-1A and Sentinel-1B SAR satellites have ideal ground coverage and imaging frequency for observing Antarctica.This study developed a dataset of 69,586 Sentinel-1 EW mode satellite images of the Antarctic ice sheet from October 2014 to December 2020.The dataset was processed with the European Space Agency Sentinel Application Platform(SNAP)and a Python batch scheduling tool on the Big Earth Data Cloud Service Platform of the Chinese Academy of Sciences Big Earth Data Science Engineering Program(CASEarth).Several data processing operations were implemented to process the raw dataset,including radiometric calibration,invalid edge removal,geocoding,data reprojection to an Antarctic projection,data compression to TIFF format,and construction of image pyramids.The dataset is avail-able at http://www.doi.org/10.11922/sciencedb.j00076.00085.展开更多
The Chinese Academy of Sciences(CAS)launched the Big Earth Data Science Engineering Program(CASEarth)in 2018,which laid the foundation for the International Research Center of Big Data for Sustainable Development Goal...The Chinese Academy of Sciences(CAS)launched the Big Earth Data Science Engineering Program(CASEarth)in 2018,which laid the foundation for the International Research Center of Big Data for Sustainable Development Goals(CBAS).Building on CASEarth’s achievements,CBAS integrates advanced digital technologies to advance the UN Sustainable Development Goals(SDGs)through five key missions:(1)developing SDG data infrastructure and information products via its SDG Big Data Platform,utilizing advanced computing,cloud services,and AI;(2)developing and launching a series of SDG satellites,including SDGSAT-1,which provides crucial Earth observation data through its Open Science Program;(3)providing new knowledge for SDG monitoring and evaluation through annual reports(Big Earth Data in Support of the Sustainable Development Goals,published since 2019)and guiding the development of big data-driven technical solutions and theoretical systems;(4)establishing a think tank for science,technology,and innovation,promoting SDGs through initiatives like the annual International Forum on Big Data for Sustainable Development Goals(FBAS)and the CBAS Fellowship Program;and(5)providing capacity development for SDGs in developing countries through international collaborations,such as the Digital Belt and Road Program(DBAR),which offers professional education and training in big data.Future CBAS efforts will focus on expanding data access,enhancing AI capabilities for SDG indicator monitoring,and strengthening international partnerships to address data gaps and ensure equitable access to technology and expertise for achieving global sustainability.展开更多
The digital transformation of our society coupled with the increasing exploitation of natural resources makes sustainability challenges more complex and dynamic than ever before.These changes will unlikely stop or eve...The digital transformation of our society coupled with the increasing exploitation of natural resources makes sustainability challenges more complex and dynamic than ever before.These changes will unlikely stop or even decelerate in the near future.There is an urgent need for a new scientific approach and an advanced form of evidence-based decisionmaking towards the benefit of society,the economy,and the environment.To understand the impacts and interrelationships between humans as a society and natural Earth system processes,we propose a new engineering discipline,Big Earth Data science.This science is called to provide the methodologies and tools to generate knowledge from diverse,numerous,and complex data sources necessary to ensure a sustainable human society essential for the preservation of planet Earth.Big Earth Data science aims at utilizing data from Earth observation and social sensing and develop theories for understanding the mechanisms of how such a social-physical system operates and evolves.The manuscript introduces the universe of discourse characterizing this new science,its foundational paradigms and methodologies,and a possible technological framework to be implemented by applying an ecosystem approach.CASEarth and GEOSS are presented as examples of international implementation attempts.Conclusions discuss important challenges and collaboration opportunities.展开更多
The United Nations 2030 Agenda for Sustainable Development provides an important framework for economic,social,and environmental action.A comprehensive indicator system to aid in the systematic implementation and moni...The United Nations 2030 Agenda for Sustainable Development provides an important framework for economic,social,and environmental action.A comprehensive indicator system to aid in the systematic implementation and monitoring of progress toward the Sustainable Development Goals(SDGs)is unfortunately limited in many countries due to lack of data.The availability of a growing amount of multi-source data and rapid advancements in big data methods and infrastructure provide unique opportunities to mitigate these data shortages and develop innovative methodologies for comparatively monitoring SDGs.Big Earth Data,a special class of big data with spatial attributes,holds tremendous potential to facilitate science,technology,and innovation toward implementing SDGs around the world.Several programs and initiatives in China have invested in Big Earth Data infrastructure and capabilities,and have successfully carried out case studies to demonstrate their utility in sustainability science.This paper presents implementations of Big Earth Data in evaluating SDG indicators,including the development of new algorithms,indicator expansion(for SDG 11.4.1)and indicator extension(for SDG 11.3.1),introduction of a biodiversity risk index as a more effective analysis method for SDG 15.5.1,and several new high-quality data products,such as global net ecosystem productivity,high-resolution global mountain green cover index,and endangered species richness.These innovations are used to present a comprehensive analysis of SDGs 2,6,11,13,14,and 15 from 2010 to 2020 in China utilizing Big Earth Data,concluding that all six SDGs are on schedule to be achieved by 2030.展开更多
A persistent challenge for the Sustainable Development Goals(SDGs)has been a lack of data for indicators to assess progress towards each goal and varying capacities among nations to con-duct these assessments.Rapid de...A persistent challenge for the Sustainable Development Goals(SDGs)has been a lack of data for indicators to assess progress towards each goal and varying capacities among nations to con-duct these assessments.Rapid developments in big data,however,are facilitating a global approach to the SDGs.Tools and data products are emerging that can be extended to and leveraged by nations that do not yet have the capacity to measure SDG indica-tors.Big Earth Data,a special class of big data,integrates multisource data within a geographic context,utilizing the principles and methodologies of the established literature on big data science,applied specifically to Earth system science.This paper discusses the research challenges related to Big Earth Data and the concerted efforts and investments required to make and mea-sure progress towards the SDGs.As an example,the Big Earth Data Science Engineering Program(CASEarth)of the Chinese Academy of Sciences is presented along with other case studies on Big Earth Data in support of the SDGs.Lastly,the paper proposes future priorities for developments in Big Earth Data,such as human resource capacity,digital infrastructure,interoperability,and envir-onmental considerations.展开更多
Earth observation community has entered into the era of big data.Family of Landsat sensors have collected massive medium resolution satellite images,which are valuable for long-term land surface monitoring.In order to...Earth observation community has entered into the era of big data.Family of Landsat sensors have collected massive medium resolution satellite images,which are valuable for long-term land surface monitoring.In order to significantly reduce the magnitude of data processing for remote sensing data users,Landsat-based Ready to Use(RTU)products have been produced.Main RTU products,including orthorectified products,land surface reflectance,land surface temperature,large-area mosaic image,and standard image map products,are described.The resulting Landsat RTU products are hosted on the RSGS earth observation data sharing web site for free download(http://ids.ceode.ac.cn/rtu/).These new products will provide consistent,standardized,multi-decadal image data for robust land cover change detection and monitoring across the Earth sciences.In the coming years,CASEarth DataBank system will be constructed,which is an intelligent data service platform for providing not only the RTU products from multi-source satellite data,but also big earth data analysis methods.展开更多
Big Earth Data refers to the multidimensional integration and association of scientific data,including geography,resources,environment,ecology,and biology.An effective data classification system and label management s...Big Earth Data refers to the multidimensional integration and association of scientific data,including geography,resources,environment,ecology,and biology.An effective data classification system and label management strategy are important foundations for long-term management of data resources.The objective of this study was to construct a classification system and realize multidimensional semantic data label management for the Big Earth Data Science Engineering Program(CASEarth).This study constructed two sets of classification and coding systems that realize classification by mapping each other;namely,the geosphere-level and Sustainable Development Goals(SDGs)indicator classifications.This technique was based on natural language processing technology and solved problems with subject-word segmentation,weight calculation,and dynamic matching.A prototype system for classification and label management was constructed based on existing CASEarth datasets of more than 1,100.Furthermore,we expect our study to provide the methodology and technical support for useroriented classification and label management services for Big Earth Data.展开更多
基金Supported by Chinese Academy of Sciences Strategic Leading Science and Technology Project(XDA19010000)。
文摘CASEarth satellite is the first space Earth science satellite produced by the Chinese Academy of Sciences.The satellite has three payloads:high-definition Thermal Infrared Spectrometer(TIS),highdefinition Glimmer Imager for Urbanization(GIU),and high-definition Multispectral Imager for Inshore(MII).These payloads are used to explore the urbanization level and residential layout,the coastal ecosystem,and new methods and approaches of environmental detection during night-time and even under conditions of polar aurora and provide scientific evidence for the refined depiction of human traces.The CASEarth satellite can provide space observation data for A Project on Big Earth Data Science Engineering as well as scientific and application studies inside and outside China.
基金funded by the Chinese Academy of Sciences Strategic Priority Research Program of the Big Earth Data Science Engineering Program(CASEarth),grant numbers XDA19090000,XDA19030000,Capacity Building Project of Big Earth Data Science Data Center of the Chinese Academy of Sciences,grant number WX145XQ07-13,and National Natural Science Foundation of China,grant number 41876226。
文摘Antarctica plays an important role in research on global change,and its unique geography,ocean,climate,and environment pro-vide an ideal place for humankind to understand Earth’s evolution.Remote sensing provides an effective means to monitor and observe large-scale processes on the continent.Synthetic aperture radar(SAR)in particular provides the capability for all-weather Earth observation.The Sentinel-1A and Sentinel-1B SAR satellites have ideal ground coverage and imaging frequency for observing Antarctica.This study developed a dataset of 69,586 Sentinel-1 EW mode satellite images of the Antarctic ice sheet from October 2014 to December 2020.The dataset was processed with the European Space Agency Sentinel Application Platform(SNAP)and a Python batch scheduling tool on the Big Earth Data Cloud Service Platform of the Chinese Academy of Sciences Big Earth Data Science Engineering Program(CASEarth).Several data processing operations were implemented to process the raw dataset,including radiometric calibration,invalid edge removal,geocoding,data reprojection to an Antarctic projection,data compression to TIFF format,and construction of image pyramids.The dataset is avail-able at http://www.doi.org/10.11922/sciencedb.j00076.00085.
文摘The Chinese Academy of Sciences(CAS)launched the Big Earth Data Science Engineering Program(CASEarth)in 2018,which laid the foundation for the International Research Center of Big Data for Sustainable Development Goals(CBAS).Building on CASEarth’s achievements,CBAS integrates advanced digital technologies to advance the UN Sustainable Development Goals(SDGs)through five key missions:(1)developing SDG data infrastructure and information products via its SDG Big Data Platform,utilizing advanced computing,cloud services,and AI;(2)developing and launching a series of SDG satellites,including SDGSAT-1,which provides crucial Earth observation data through its Open Science Program;(3)providing new knowledge for SDG monitoring and evaluation through annual reports(Big Earth Data in Support of the Sustainable Development Goals,published since 2019)and guiding the development of big data-driven technical solutions and theoretical systems;(4)establishing a think tank for science,technology,and innovation,promoting SDGs through initiatives like the annual International Forum on Big Data for Sustainable Development Goals(FBAS)and the CBAS Fellowship Program;and(5)providing capacity development for SDGs in developing countries through international collaborations,such as the Digital Belt and Road Program(DBAR),which offers professional education and training in big data.Future CBAS efforts will focus on expanding data access,enhancing AI capabilities for SDG indicator monitoring,and strengthening international partnerships to address data gaps and ensure equitable access to technology and expertise for achieving global sustainability.
基金the Strategic Priority Research Program of the Chinese Academy of Sciences(grant numbers XDA19030000 and XDA19090000)the DG Research and Innovation of the European Commission(H2020 grant number 34538).
文摘The digital transformation of our society coupled with the increasing exploitation of natural resources makes sustainability challenges more complex and dynamic than ever before.These changes will unlikely stop or even decelerate in the near future.There is an urgent need for a new scientific approach and an advanced form of evidence-based decisionmaking towards the benefit of society,the economy,and the environment.To understand the impacts and interrelationships between humans as a society and natural Earth system processes,we propose a new engineering discipline,Big Earth Data science.This science is called to provide the methodologies and tools to generate knowledge from diverse,numerous,and complex data sources necessary to ensure a sustainable human society essential for the preservation of planet Earth.Big Earth Data science aims at utilizing data from Earth observation and social sensing and develop theories for understanding the mechanisms of how such a social-physical system operates and evolves.The manuscript introduces the universe of discourse characterizing this new science,its foundational paradigms and methodologies,and a possible technological framework to be implemented by applying an ecosystem approach.CASEarth and GEOSS are presented as examples of international implementation attempts.Conclusions discuss important challenges and collaboration opportunities.
基金supported by the Big Earth Data Science Engineering Program of the Chinese Academy of Sciences Strategic Priority Research Program(XDA19090000 and XDA19030000)。
文摘The United Nations 2030 Agenda for Sustainable Development provides an important framework for economic,social,and environmental action.A comprehensive indicator system to aid in the systematic implementation and monitoring of progress toward the Sustainable Development Goals(SDGs)is unfortunately limited in many countries due to lack of data.The availability of a growing amount of multi-source data and rapid advancements in big data methods and infrastructure provide unique opportunities to mitigate these data shortages and develop innovative methodologies for comparatively monitoring SDGs.Big Earth Data,a special class of big data with spatial attributes,holds tremendous potential to facilitate science,technology,and innovation toward implementing SDGs around the world.Several programs and initiatives in China have invested in Big Earth Data infrastructure and capabilities,and have successfully carried out case studies to demonstrate their utility in sustainability science.This paper presents implementations of Big Earth Data in evaluating SDG indicators,including the development of new algorithms,indicator expansion(for SDG 11.4.1)and indicator extension(for SDG 11.3.1),introduction of a biodiversity risk index as a more effective analysis method for SDG 15.5.1,and several new high-quality data products,such as global net ecosystem productivity,high-resolution global mountain green cover index,and endangered species richness.These innovations are used to present a comprehensive analysis of SDGs 2,6,11,13,14,and 15 from 2010 to 2020 in China utilizing Big Earth Data,concluding that all six SDGs are on schedule to be achieved by 2030.
基金The research was supported by the Chinese Academy of Sciences Strategic Priority Research Program of the Big Earth Data Science Engineering Program(CASEarth),grant numbers[XDA19090000 and XDA19030000].
文摘A persistent challenge for the Sustainable Development Goals(SDGs)has been a lack of data for indicators to assess progress towards each goal and varying capacities among nations to con-duct these assessments.Rapid developments in big data,however,are facilitating a global approach to the SDGs.Tools and data products are emerging that can be extended to and leveraged by nations that do not yet have the capacity to measure SDG indica-tors.Big Earth Data,a special class of big data,integrates multisource data within a geographic context,utilizing the principles and methodologies of the established literature on big data science,applied specifically to Earth system science.This paper discusses the research challenges related to Big Earth Data and the concerted efforts and investments required to make and mea-sure progress towards the SDGs.As an example,the Big Earth Data Science Engineering Program(CASEarth)of the Chinese Academy of Sciences is presented along with other case studies on Big Earth Data in support of the SDGs.Lastly,the paper proposes future priorities for developments in Big Earth Data,such as human resource capacity,digital infrastructure,interoperability,and envir-onmental considerations.
基金This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA19090300]the National Key Research and Development Programs of China[grant numbers 2016YFA0600302 and 2016YFB0501502]+1 种基金the program of the National Natural Science Foundation of China[grant number 61401461]135 Strategy Planning of Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences.
文摘Earth observation community has entered into the era of big data.Family of Landsat sensors have collected massive medium resolution satellite images,which are valuable for long-term land surface monitoring.In order to significantly reduce the magnitude of data processing for remote sensing data users,Landsat-based Ready to Use(RTU)products have been produced.Main RTU products,including orthorectified products,land surface reflectance,land surface temperature,large-area mosaic image,and standard image map products,are described.The resulting Landsat RTU products are hosted on the RSGS earth observation data sharing web site for free download(http://ids.ceode.ac.cn/rtu/).These new products will provide consistent,standardized,multi-decadal image data for robust land cover change detection and monitoring across the Earth sciences.In the coming years,CASEarth DataBank system will be constructed,which is an intelligent data service platform for providing not only the RTU products from multi-source satellite data,but also big earth data analysis methods.
基金the Big Earth Science Engineering Program(CASEarth)of the Chinese Academy of Sciences[XDA19090200 and XDA19040501].
文摘Big Earth Data refers to the multidimensional integration and association of scientific data,including geography,resources,environment,ecology,and biology.An effective data classification system and label management strategy are important foundations for long-term management of data resources.The objective of this study was to construct a classification system and realize multidimensional semantic data label management for the Big Earth Data Science Engineering Program(CASEarth).This study constructed two sets of classification and coding systems that realize classification by mapping each other;namely,the geosphere-level and Sustainable Development Goals(SDGs)indicator classifications.This technique was based on natural language processing technology and solved problems with subject-word segmentation,weight calculation,and dynamic matching.A prototype system for classification and label management was constructed based on existing CASEarth datasets of more than 1,100.Furthermore,we expect our study to provide the methodology and technical support for useroriented classification and label management services for Big Earth Data.
