NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS)

NERC 地球观测数据采集和分析服务 (NEODAAS)

• 批准号: NE/S013377/1
• 负责人: Martin Wooster
• 金额: $ 210.92万
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FS013377%2F1
• 关键词: NERC; Earth; Observation; Data; Acquisition

[Note, NEODAAS were advised to merely cut and paste from the case for support into this section] The vision for NEODAAS is to provide NERC and UKRI academic communities with flexible, responsive and innovative national capability in Earth Observation data, services and advice, which addresses key strategic research and innovation priorities and contributes to understanding of important environmental issues affecting the UK. Earth Observation (EO) is crucial for observing Earth system processes in near-real time (NRT) at synoptic scales and over long periods as the data records extend in time. The European Copernicus programme, in particular, is enabling significant advances in the field through construction of an operational system of satellite-based sensors, with new and improved capabilities. Copernicus benefits the science of the expert EO community, and has even greater potential for non EO experts who can use EO derived data and information for the first time. There is, thus, increasing demand for EO data and services, but clearly it is inefficient for all grant-holders to be generating their own EO data, while many non-EO experts do not have the skill base to do their own processing. Hence, the need for NEODAAS at Plymouth was confirmed by the NERC Facilities Evaluation Panel. Surveys by NERC Head Office and NCEO show strong demand for a value for money EO service which has demonstrably resulted in high quality science: between 2013/14 and 2017/18, NEODAAS supported 321 ISI-refereed publications (with >10k citations to all NEODAAS papers).NEODAAS services include: EO products and information including production of analysis-ready data products to meet particular UK needs (such as UK projections or bespoke algorithms); rapid-response with very fast delivery times; provision of data in formats that can be easily used by non-experts; operationalisation of algorithms produced by NERC-funded research, for wider impact in the community; and provision of advice and training in the sources and best practice in EO. NEODAAS offers a centralised service from one location, thus avoiding duplication, and providing critical mass. NEODAAS is currently a dual node facility based at Plymouth Marine Laboratory (PML) and the University of Dundee. The recommissioned service will continue work performed at PML, and will expand this by taking on certain of the work undertaken by Dundee - namely the collection of level 1 data for NRT data processing. This will be done via web/ftp downloads and PML-based EUMETCast data reception. NEODAAS will provide flexibility to meet the wide range of UK community needs, and considerable leverage in terms of exploiting PML R&D outcomes, local expertise and existing computing and processing systems. NEODAAS will support Excellent Science funded through NERC grants, NERC Centre/Survey NC, Fellowships, Doctoral Training Partnerships or Centres for Doctoral Training, direct-access proposals as well as UKRI funding opportunities, such as the GCRF and Industrial Strategy Challenge Fund (ISCF). The end-user community and the corresponding services may be split into two groups or strands:Strand 1) Services to non-EO experts who wish to make use of EO datasets and information but do not wish, or are not able to spend extensive time learning how to do data processing. These services support the wider user community, numbering potentially many 1000's, many of whom may not even be aware of it (e.g. non-EO scientists on research cruises guided by NEODAAS).Strand 2) Services to the EO Community who have EO expertise, but want specialist aid such as algorithm implementation, e.g. arising from NCEO research, in a NRT framework or would like to include their algorithms in the NEODAAS processing chain. The potential number of users is smaller, typically 100's, but the services may be more complex and bespoke in nature than those in Strand 1.

[Note NEODAAS的愿景是为NERC和UKRI学术界提供地球观测数据，服务和建议方面的灵活，响应和创新的国家能力，解决关键的战略研究和创新优先事项，并有助于理解影响英国的重要环境问题。对地观测（EO）对于在天气尺度上近实时（NRT）观测地球系统过程至关重要，并且随着数据记录的时间延长而延长。特别是欧洲哥白尼方案，通过建立一个具有新的和改进的能力的卫星传感器业务系统，使这一领域取得了重大进展。哥白尼有利于专家EO社区的科学，并有更大的潜力，为非EO专家谁可以使用EO派生的数据和信息的第一次。因此，对EO数据和服务的需求日益增加，但显然，所有赠款持有人自己生成EO数据的效率低下，而许多非EO专家没有自己处理数据的技能基础。因此，NERC设施评估小组确认普利茅斯需要NEODAAS。NERC总部和NCEO的调查显示，对物有所值的EO服务的需求强劲，这已经证明了高质量的科学：在2013/14和2017/18之间，NEODAAS支持了321篇ISI参考的出版物（所有NEODAAS论文的引用量超过10000次）。NEODAAS服务包括：EO产品和信息，包括生产可供分析的数据产品，以满足英国的特定需求（如英国的预测或定制算法）;快速反应，交付时间非常快;以非专家易于使用的格式提供数据;实施由NERC资助的研究产生的算法，以在社区中产生更广泛的影响;并在EO的来源和最佳实践方面提供咨询和培训。NEODAAS从一个地点提供集中服务，从而避免重复，并提供临界质量。NEODAAS目前是普利茅斯海洋实验室和邓迪大学的双节点设施。重新委托的服务将继续在PML进行的工作，并将通过承担邓迪进行的某些工作来扩展这项工作-即收集用于NRT数据处理的1级数据。这将通过web/ftp下载和基于PML的EUMETCast数据接收完成。NEODAAS将提供灵活性，以满足英国社区的广泛需求，并在利用PML研发成果、本地专业知识和现有计算和处理系统方面发挥相当大的作用。NEODAAS将通过NERC赠款，NERC中心/调查NC，奖学金，博士培训合作伙伴关系或博士培训中心，直接访问提案以及UKRI资助机会，如GCRF和工业战略挑战基金（ISCF），支持优秀科学。最终用户群体和相应的服务可分为两组或两股：1）为希望利用EO数据集和信息但不希望或无法花费大量时间学习如何进行数据处理的非EO专家提供服务。这些服务支持更广泛的用户社区，可能有数千人，其中许多人甚至可能不知道它（例如，在NEODAAS指导下进行研究航行的非EO科学家）。Strand 2）为EO社区提供服务，他们拥有EO专业知识，但需要专家帮助，例如算法实现，例如来自NCEO研究，或者想在NEODAAS处理链中包含他们的算法。潜在的用户数量较少，通常为100个，但服务可能比Strand 1中的服务更复杂和定制。

项目成果

Seasonal and inter-annual variability of net primary production in the NW Iberian margin (1998-2016) in relation to wind stress and sea surface temperature

伊比利亚西北部边缘（1998-2016）净初级生产的季节性和年际变化与风应力和海面温度的关系

• DOI: 10.1016/j.pocean.2019.102135
• 发表时间: 2019
• 期刊: Progress in Oceanography
• 影响因子: 4.1
• 作者: Beca-Carretero P

The 2014-2015 Lava Flow Field at Holuhraun, Iceland: Using Airborne Hyperspectral Remote Sensing for Discriminating the Lava Surface

2014-2015年冰岛Holuhraun熔岩流场：利用机载高光谱遥感判别熔岩表面

• DOI: 10.3390/rs11050476
• 发表时间: 2019
• 期刊: Remote Sensing
• 影响因子: 5
• 作者: Aufaristama M

Using repeat airborne LiDAR to map the growth of individual oil palms in Malaysian Borneo during the 2015-16 El Niño

使用重复机载激光雷达绘制 2015-16 厄尔尼诺现象期间马来西亚婆罗洲各个油棕的生长情况

• DOI: 10.1016/j.jag.2022.103117
• 发表时间: 2022
• 期刊: International Journal of Applied Earth Observation and Geoinformation
• 影响因子: 7.5
• 作者: Beese L

Seasonal plant development and meadow structure of Irish and southern Spanish seagrass populations

爱尔兰和西班牙南部海草种群的季节性植物发育和草甸结构

• DOI: 10.1016/j.aquabot.2022.103569
• 发表时间: 2022
• 期刊: Aquatic Botany
• 影响因子: 1.8
• 作者: Azcárate-García T

Multi-nested WRF simulations for studying planetary boundary layer processes on the turbulence-permitting scale in a realistic mesoscale environment

• DOI: 10.1080/16000870.2020.1761740
• 发表时间: 2020-01
• 期刊: Tellus A: Dynamic Meteorology and Oceanography
• 作者: H. Bauer;S. K. Muppa;V. Wulfmeyer;A. Behrendt;K. Warrach‐Sagi;F. Späth