Crop change detection in conflict-affected areas of Nigeria, agricultural season 2022 (2022-09-28)

<br/> Activation date: 2022-09-28 <br/> Event type: Other <br/> <br/> Activation reason: <br/> The scope of this activation is to continue and update the analysis already performed under CEMS-FLEX activations EMSN063, EMSN083 and EMSN113, providing information about the agriculture, food security and nutrition analysis situation in Northern Nigeria, in support of the WFP officers. For the 4th edition, it was required to analyse 44 AOIs (33 to be updated and 11 newly analysed) distributed between four Nigerian States: 35 AOIs located at the north-western region and 9 AOIs at the north-eastern, near Lake Chad. Due to the inaccessibility of the region caused by on-going armed conflicts, the impact of the conflict needs to be estimated for changes in cropland (loss/gain) and affected population. The analysis was performed in between the reference years of 2010 &amp; 2022, 2017 &amp; 2022, and 2021 &amp; 2022.&nbsp;Proposed solution and resultsGeneration of NDVI-composite layers per NW and NE regions for each timestamp of analysisUpdate and verification of the populated sites layer based on freely available imagery and ancillary dataCrop change analysis per populated site based on the NDVI-composite layer between 2010 &amp; 2022, 2017 &amp; 2022, and 2021 &amp; 2022Interpolation of the population data per populated sites applying a Thiessen polygon analysisAnalysis of population affected by cropland loss/gain&nbsp;&nbsp;&nbsp; <br/> <br/>启动日期：2022-09-28 事件类型：其他 启动缘由： 本次启动的工作范围为延续并更新此前在CEMS-FLEX系列激活任务中EMSN063、EMSN083及EMSN113项下已完成的分析工作，旨在为世界粮食计划署（World Food Programme, WFP）的工作人员提供尼日利亚北部地区农业、粮食安全与营养状况的相关分析信息，以支撑其工作开展。在本次任务的第四版中，需对分布于尼日利亚四个州的44个兴趣区（Area of Interest, AOI）开展分析，其中33个为需更新的既有分析对象，11个为新增分析对象；35个兴趣区位于西北部区域，剩余9个位于东北部乍得湖附近区域。由于当前持续武装冲突导致该区域无法进入，需评估冲突对耕地（增减）及受影响人口造成的影响。本次分析采用的参考时段分别为2010年与2022年、2017年与2022年以及2021年与2022年。 拟采用方案与成果： 1. 针对各分析时间节点，为西北部（NW）与东北部（NE）区域分别生成归一化植被指数（Normalized Difference Vegetation Index, NDVI）合成图层； 2. 基于公开可用影像及辅助数据，更新并核验居民点图层； 3. 基于2010年与2022年、2017年与2022年以及2021年与2022年的NDVI合成图层，对各居民点开展耕地变化分析； 4. 采用泰森多边形（Thiessen polygon）分析法，对各居民点的人口数据进行插值处理； 5. 分析受耕地增减影响的人口情况。