NCEO NC ODA Full

ncec国家官方发展援助方案侧重于一系列与发展挑战特别相关的一般科学问题：地表状态的特征和预测，包括植被变化和土壤湿度；森林碳的演变和森林砍伐和退化引起的碳通量的特征；火灾的动态性，它们向大气中的排放和大规模空气污染的发展；培养一批受过最先进地球观测训练的研究人员和应用专家。我们将解决发展援助委员会国家面临的具体问题：非洲半干旱地区作物产量对干旱的脆弱性，保护和加强肯尼亚森林资源以减缓气候变化的挑战，捕捉东南亚露天生物质燃烧造成的有害空气质量所需的预测技能，以及目前许多非洲国家缺乏有效利用卫星地球观测数据的能力。该课程分为四个WPs。相关的联合国可持续发展目标有：2（零饥饿）、3（良好健康和福祉）、13（气候行动）、15（陆地生命）和17（实现目标的伙伴关系）。WP 1将通过同化多个EO数据流（例如有效叶面积指数和土壤湿度）的数据，改进加纳和埃塞俄比亚的作物产量模型。该研究将产生关于数据模型系统中准确的EO数据参数价值的新知识，以更好地表征作物变化并提高预测技能，检查从景观到国家尺度的升级，并提高土壤湿度预测技能[SGDs 2,15]。WP 2将建立肯尼亚毁林造成的碳排放基线，从合成孔径雷达、光学和激光雷达（LiDAR）数据中确定不同类型的毁林和退化，并建立适合植树造林的地区，以支持肯尼亚政府的2030年愿景，该愿景旨在到2030年将森林覆盖率从6%提高到10%。这项工作将确定森林参考排放水平和地上碳储量。这项研究是理解REDD+政策背景下碳循环估算的关键。[SGDs 13,15]。WP 3将开发和展示新的数据源，以提高火灾事件期间大规模空气污染的预报准确性。目前，预测模型使用的火灾估计值无法捕捉大型动态森林和泥炭地火灾以及农业残留物燃烧引起的火灾的规模和变异性。该研究将改进火灾的污染物排放估算，基于eo的烟羽气溶胶检索和生物质燃烧羽流的自动识别。我们将与东盟国家的利益相关者合作，共同开发和展示新系统，描述改进情况，并培训员工解释复杂的EO数据[可持续发展目标3,13]。WP 4将通过与地球观测相关的国际倡议进行能力建设，包括地球观测组织（GEO） AfriGEOSS倡议和地球观测卫星委员会（ceo）能力建设和数据民主工作组，以改善非洲国家和其他发展援助委员会国家对当代地球观测数据集的获取和使用。工作将包括确定与英国相关的EO项目和与非洲eoss确定需求相关的专家的范围，将WP1-3的培训扩展到更广泛的DAC国家和战略能力建设，与GFOI和GEOGLAM的相关GEO倡议协调工作，并支持DAC国家访问EO数据。这些行动也将有利于英国的国家优先事项，例如监测由GNU伙伴关系（德国、挪威和英国）支持的项目，该伙伴关系将在2015年至2020年期间为REDD+的先行者提供50亿美元，以及生物碳基金的可持续森林景观倡议（ISFL）[可持续发展目标17]。

The NCEO NC-ODA programme is focussed on a series of generic science issues that are particularly relevant to development challenges: characterisation and forecasting of land surface state including vegetation change and soil moisture; the evolution of forest carbon and characterisation of carbon fluxes arising from deforestation and degradation; the dynamic nature of fires, their emissions into the atmosphere and the development of large-scale air pollution; the development of a cadre of researchers and applications specialists trained in state-of-the-art Earth Observation (EO).We will address specific problems faced by DAC countries: the vulnerability of crop yields in semi-arid regions in Africa to drought, the challenge of protecting and enhancing Kenya's forest resources to mitigate climate change, the forecast skill necessary to capture hazardous air quality in South-East Asia stemming from open biomass burning, and the current lack of capacity of many African nations to make effective use of satellite EO data. The programme is structured into four WPs. Relevant UN Sustainable Development Goals are: 2 (Zero hunger), 3 (Good health and well-being), 13 (Climate action), 15 (Life on Land), and 17 (Partnership for the goals).WP 1 will improve crop yield modelling in Ghana and potentially Ethiopia through data assimilation of multiple EO data streams, for example effective leaf area index and soil moisture. The research will yield new knowledge on the value of accurate EO data parameters in a data-model system, to better characterise crop change and increase predictive skill, to examine upscaling from landscape to country scale, and improve soil moisture forecast skill [SGDs 2, 15].WP 2 will establish a baseline of carbon emissions from deforestation in Kenya, identify different types of deforestation and degradation from synthetic aperture radar, optical and laser ranging (LiDAR) data, and establish areas that are suitable for afforestation to support the Vision 2030 of the Kenyan Government that aims to increase forest cover from 6 to 10 per cent by 2030. The work will establish forest reference emission levels and above-ground carbon stocks. This research is key to understanding carbon cycling estimates in a REDD+ policy context. [SGDs 13, 15].WP 3 will develop and demonstrate new data sources that can improve forecast accuracy for large-scale air pollution during fire events. Currently, forecast models use estimates of fires that fail to capture the magnitude and variability of dynamic large forest and peatland fires and fires due to agricultural residue burning. The research will improve pollutant emissions estimates from fires, EO-based retrievals of smoke plume aerosols and auto-identification of biomass-burning plumes. We will work with stakeholders in the ASEAN countries to co-develop and demonstrate new systems, characterise improvements and train staff in the interpretation of complex EO data [SDGs 3, 13]. WP 4 will build capacity through international EO-related initiatives, including the Group on Earth Observations (GEO) AfriGEOSS initiative and the Committee on Earth Observation Satellites (CEOS) Working Group on Capacity Building & Data Democracy, to improve access to and use of contemporary EO datasets in African nations and other DAC nations. Work will include scoping of UK-related EO projects and experts related to AfriGEOSS identified needs, extension of the training of WP1-3 to wider DAC countries and to strategic capacity building, co-ordinated work with the relevant GEO initiatives of GFOI and GEOGLAM, and support of access to EO data for DAC countries. These actions will also benefit UK national priorities such as the monitoring of projects supported by the GNU partnership (Germany, Norway and UK), which is making US$5 billion available between 2015 and 2020 for REDD+ early movers, and the Biocarbon Fund's Initiative for Sustainable Forest Landscapes (ISFL) [SDG 17].