NCEO NC ODA Extension 2020-2021

NCENC-oda方案侧重于与发展挑战特别相关的一系列一般性科学问题：包括植被变化和土壤湿度在内的地表状态的特征和预测；森林碳的演变和森林砍伐和退化产生的碳通量的特征；火灾的动态性质及其向大气的排放和大规模空气污染的形成；培养一支接受最新地球观测培训的研究人员和应用专家队伍。我们将解决发援会国家面临的具体问题：非洲半干旱地区作物产量易受干旱影响，在撒哈拉以南非洲保护和加强来自肯尼亚的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产生的有害空气质量所需的预报技能，以及许多非洲国家目前缺乏有效利用卫星环境观测数据的能力。该方案分为四个工作计划。相关的联合国可持续发展目标是：2(零饥饿)、3(健康和福祉)、13(气候行动)、15(陆地生命)和17(目标伙伴关系)。WP 1将通过对有效叶面积指数和土壤湿度等多个EO数据流的数据同化，改进加纳和整个撒哈拉以南非洲的作物产量建模。这项研究将产生关于准确的EO数据参数在数据模型系统中的价值的新知识，以更好地描述作物变化并提高预测技能，检查从景观到国家尺度的提升，并提高土壤水分预测技能[SGDS 2，15]。它将支持改进的TAMSAT警报系统。WP 2将扩大整个撒哈拉以南非洲因森林砍伐而产生的碳排放基线，根据合成孔径雷达、光学和激光测距(LiDAR)数据识别不同类型的森林砍伐和退化，并建立适合植树造林的地区。它将在肯尼亚测试新的数据集，以确保有效性，并继续支持肯尼亚政府的2030年远景规划，目标是到2030年将森林覆盖率从6%提高到10%。这项工作将在区域范围内确定森林参考排放水平和地上碳储量。这项研究是在REDD+政策背景下理解碳循环估计的关键。[SGDS 13、15]。WP 3将开发和演示新的数据源，这些数据源可以提高火灾事件期间大规模空气污染的预测精度。目前，预测模型使用的是对未能捕捉到动态大型森林和泥炭地火灾以及农业残渣燃烧引起的火灾的规模和可变性的火灾的估计。这项研究将改进火灾的污染物排放估计、基于EO的烟羽气溶胶提取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，共同开发和演示新系统，确定改进的特征，并培训工作人员解释复杂的EO数据。我们将在撒哈拉以南非洲地区实施WP3的火灾部分，改进碳估计，并将干旱与火灾知识结合起来。[可持续发展目标3、13]第四工作组将通过与地球观测有关的国际举措，包括地球观测小组非洲地球观测卫星系统倡议和地球观测卫星委员会能力建设和数据民主工作组，加强能力建设，以改善非洲国家和其他发援会国家对当代地球观测数据集的获取和利用。工作将包括确定与英国有关的地球观测组织项目和与非洲地球观测组织确定的需求有关的专家的范围，将WP1-3培训扩展到更广泛的发援会国家和战略能力建设，与全球地球观测组织的相关地球观测组织倡议协调工作，以及支持发援会国家获取地球观测组织数据。

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 forest resources from Kenya across sub-Saharan Africa, 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 then across sub-Saharan Africa 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]. It will support an improved TAMSAT-ALERT system.WP 2 will extend a baseline of carbon emissions from deforestation across sub-Saharan Africa, 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. It will test new datasets in Kenya to ensure validity and to continue 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 in a regional context. 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. We will implement the fire component of WP3 in sub-Saharan Africa improving carbon estimates and coupling drought with fire knowledge. [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 AfriGEO 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.