首页期刊导航|地球大数据(英文版)
期刊信息/Journal information
地球大数据(英文版)
地球大数据(英文版)

双月刊

地球大数据(英文版)/Journal Big Earth DataCSCD
正式出版
收录年代

    Big data in support of the Sustainable Development Goals:a celebration of the establishment of the International Research Center of Big Data for Sustainable Development Goals (CBAS)

    Huadong GuoHeide HackmannKe Gong
    259-262页

    Innovative approaches to the Sustainable Development Goals using Big Earth Data

    Huadong GuoDong LiangFang ChenZeeshan Shirazi...
    263-276页
    查看更多>>摘要: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 multi-source 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.

    Atmospheric and ecosystem big data providing key contributions in reaching United Nations' Sustainable Development Goals

    Markku KulmalaAnna LintunenIlona YlivinkkaJanne Mukkala...
    277-305页
    查看更多>>摘要:Big open data comprising comprehensive,long-term atmospheric and ecosystem in-situ observations will give us tools to meet global grand challenges and to contribute towards sustainable develop-ment.United Nations' Sustainable Development Goals (UN SDGs)provide framework for the process.We present synthesis on how Station for Measuring Earth Surface-Atmosphere Relations (SMEAR)observation network can contribute to UN SDGs.We describe SMEAR Ⅱ flagship station in Hyyti(a)l(a),Finland.With more than 1200 variables measured in an integrated manner,we can under-stand interactions and feedbacks between biosphere and atmo-sphere.This contributes towards understanding impacts of climate change to natural ecosystems and feedbacks from ecosys-tems to climate.The benefits of SMEAR concept are highlighted through outreach project in Eastern Lapland utilizing SMEARⅠ observations from V(a)rri(o) research station.In contrast to boreal environment,SMEAR concept was also deployed in Beijing.We underline the benefits of comprehensive observations to gain novel insights into complex interactions between densely popu-lated urban environment and atmosphere.Such observations enable work towards solving air quality problems and improve the quality of life inside megacities.The network of comprehensive stations with various measurements will enable science-based deci-sion making and support sustainable development by providing long-term view on spatio-temporal trends on atmospheric compo-sition and ecosystem parameters.

    Earth observation and geospatial big data management and engagement of stakeholders in Hungary to support the SDGs

    Szabolcs MihályGábor Remetey-Fül(o)ppDániel KristófAnna Czinkóczky...
    306-351页
    查看更多>>摘要:To support the monitoring and reporting processes during imple-mentation of the Sustainable Development Goals,well-developed,commonly recognized Earth observations and geospatial data,methods,innovations,committed professionals,and strong sus-tainability policies are necessary.This article informs the readers on the Earth observation and geoinformation developments and innovations,and on the engagement of profession,academy and governance to support implementation of the Sustainable Development Goals in Hungary.Description,analyses and critical assessments are given on the elements selected from Hungarian sustainable-oriented Earth observation and geospatial novelties:(a) Working Group for Sustainable Development mission and national sustainability-policy,(b) international partnerships,domestic activities and achievements,(c) status of the professional education,(d) spatial databases and services to support implementation of the sustain-able development,(e) a case study on the internationally recog-nized soil geoinformation system,(f) national Earth Observation Information System and perspectives of its applications for mon-itoring the sustainability.The article conclusion strongly advises the Hungarian realization of (a) institutionalization of the Earth observation and geospatial tools and capacity for sustainable development,(b) their use in integration with statistical data,(c) establishment of national spatial information infrastructure and (d) development and spreading of the use of big data.

    Capturing the value of biosurveillance "big data" through natural capital accounting

    David CastlePaul D.N.HebertElizabeth L.ClareIan D.Hogg...
    352-367页
    查看更多>>摘要:Global biodiversity is in crises.Recognition of the scale and pace of biodiversity loss is leading to rapid technological development in biodiversity science to identify species,their interactions,and eco-system dynamics.National and international policy developments to stimulate mitigation and remediation actions are escalating to meet the biodiversity crises.They can take advantage of biosurveil-lance "big data" as evidence for more sweeping and impactful policy measures.The critical factor is translating biosurveillance data into the value-based frameworks underpinning new policy measures.An approach to this integration process,using natural capital accounting frameworks is developed.

    Living Earth:Implementing national standardised land cover classification systems for Earth Observation in support of sustainable development

    Christopher J.OwersRichard M.LucasDaniel ClewleyCarole Planque...
    368-390页
    查看更多>>摘要:Earth Observation (EO) has been recognised as a key data source for supporting the United Nations Sustainable Development Goals (SDGs).Advances in data availability and analytical capabilities have provided a wide range of users access to global coverage analysis-ready data (ARD).However,ARD does not provide the information required by national agencies tasked with coordinating the implementation of SDGs.Reliable,standardised,scalable mapping of land cover and its change over time and space facilitates informed deci-sion making,providing cohesive methods for target setting and reporting of SDGs.The aim of this study was to implement a global framework for classifying land cover.The Food and Agriculture Organisation's Land Cover Classification System(FAO LCCS) provides a global land cover taxonomy suitable to comprehensively support SDG target setting and reporting.We present a fully implemented FAO LCCS optimised for EO data;Living Earth,an open-source software package that can be readily applied using existing national EO infrastructure and satellite data.We resolve several semantic challenges of LCCS for consistent EO implementation,including modifications to environmental descriptors,inter-dependency within the mod-ular-hierarchical framework,and increased flexibility associated with limited data availability.To ensure easy adoption of Living Earth for SDG reporting,we identified key environmental descriptors to provide resource allocation recommendations for generating routinely retrieved input parameters.Living Earth provides an optimal platform for global adoption of EO4SDGs ensuring a transparent methodology that allows monitoring to be standardised for all countries.

    Spatial patterns of urban green space and its actual utilization status in China based on big data analysis

    Yiyi HuangTao LinGuoqin ZhangYongguan Zhu...
    391-409页
    查看更多>>摘要:Urban green space (UGS) is essential for sustainable urbanization and human well-being.The utilization status of UGS is closely related to the provision of ecosystem services for urban residents.Limitations on data availability,however,have led to the absence of a comprehensive approach for evaluating the actual utilization status of UGS at a large scale.Furthermore,differences in actual UGS utilization between intra-urban and peri-urban areas have not received enough attention.This study used big data analysis by combining point of interest (POI) and land use and cover change(LUCC) to quantify the spatial patterns of UGS utilization,and to evaluate the actual utilization status of UGS in 366 cities on the Chinese mainland.We also explored the differences in the actual utilization of UGS in intra-urban and peri-urban areas.The results showed that 94.01% of UGS resources in China had not been utilized.There was a clear pattern of spatial mismatch between the stock and the actual utilization of UGS,especially in the north-western region indicated by the Hu Huanyong Line.The actual utilization rate of UGS was closely related to the regional develop-ment level.There was a certain mismatch between the actual utilization and stock of intraurban green space (lUGS).The hot spots of the actual utilization rate of lUGS were in Yunnan,Guizhou,and Sichuan Provinces in southwestern China.The differ-ences in UGS actual utilization rates between lUGS and peri-urban green space (PUGS) were small in eastern China,but large in south-western and northwestern China.The actual utilization rate of lUGS in most Chinese cities was significantly larger than that of PUGS,indicating that PUGS were not well utilized.Our results provide scientific support for urban and regional planners in targeting specific areas for UGS design and development,and in optimizing future UGS planning in China.

    Mapping essential urban land use categories (EULUC) using geospatial big data:Progress,challenges,and opportunities

    Bin ChenBing XuPeng Gong
    410-441页
    查看更多>>摘要:Urban land use information that reflects socio-economic functions and human activities is critically essential for urban planning,land-scape design,environmental management,health promotion,and biodiversity conservation.Land-use maps outlining the distribution,pattern,and composition of essential urban land use categories(EULUC) have facilitated a wide spectrum of applications and further triggered new opportunities in urban studies.New and improved Earth observations,algorithms,and advanced products for extracting thematic urban information,in association with emer-ging social sensing big data and auxiliary crowdsourcing datasets,all together offer great potentials to mapping fine-resolution EULUC from regional to global scales.Here we review the advances of EULUC mapping research and practices in terms of their data,methods,and applications.Based on the historical retrospect,we summarize the challenges and limitations of current EULUC studies regarding sample collection,mixed land use problem,data and model generalization,and large-scale mapping efforts.Finally,we propose and discuss future opportunities,including cross-scale mapping,optimal integration of multi-source features,global sam-ple libraries from crowdsourcing approaches,advanced machine learning and ensembled classification strategy,open portals for data visualization and sharing,multi-temporal mapping of EULUC change,and implications in urban environmental studies,to facil-itate multi-scale fine-resolution EULUC mapping research.

    Instructions for authors

    封3页