| 引用本文: | 刘园,Lazar Adjigogov,Franck Albinet,Gerd Dercon,余强毅,吴文斌,周清波.遥感作物制图辅助核事故农业风险决策[J].中国农业信息,2022,34(1):60-71 |
| |
|
| 摘要: |
| 【目的】 将作物时空分布数据应用于核事故农业风险决策支持系统，体现遥感作物制图在核事故农业风险决策中的重要性。【方法】 文章以大亚湾核电基地为研究案例，对其周边地区的作物轮作系统进行遥感制图；作物时空分布数据经后处理，上传至核事故农业风险决策支持系统，实现作物样本任务的自动生成，以及放射性核素浓度的时空分布模拟。【结果】 提出的遥感制图方法可以在耕地破碎、云雨繁密区识别作物轮作系统，快速、准确地提供大范围作物时空分布数据。经过处理的作物时空分布数据，能够方便地应用于决策支持系统，辅助完成特定或优先区作物样本任务点的自动生成，以及放射性核素浓度时空分布的模拟。【结论】 遥感作物制图与核事故农业风险决策支持系统相结合，可进一步提高采样的有效性，提升放射性核素空间和时间分布模拟与预测的准确性。从而帮助决策者制定核污染监测和评估策略、修复计划，科学指导农业生产的恢复。未来，有必要深入研究遥感作物制图在核事故农业风险决策中的应用，充分发挥遥感技术与数据的优势，规避核事故对农业生产带来的风险。 |
| 关键词: 大亚湾核电站 核事故 广东 谷歌地球引擎 哨兵数据 |
| DOI：10.12105/j.issn.1672-0423.20220107 |
| 分类号: |
| 基金项目:国际原子能机构协调研究项目：“放射性污染农田修复”（D15019） |
|
| Mapping cropland use dynamics for the Decision Support System for Nuclear Emergencies Affecting Food and Agriculture |
|
Liu Yuan1, Lazar Adjigogov2, Franck Albinet2, Gerd Dercon2, Yu Qiangyi1, Wu Wenbin1, Zhou Qingbo3
|
|
1.Key Laboratory of Agricultural Remote Sensing，Ministry of Agriculture and Rural Affairs/ Institute of Agricultural Resources and Regional Planning，Chinese Academy of Agricultural Sciences，Beijing 100081，China;2.Soil and Water Management & Crop Nutrition Laboratory，Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture，Seibersdorf A-2444，Austria;3.Agricultural Information Institute，Chinese Academy of Agricultural Sciences，Beijing 100081，China
|
| Abstract: |
| [Purpose] We applied cropland use maps to the Decision Support System for Nuclear Emergencies Affecting Food and Agriculture （DSS4NAFA），to demonstrate the application and significance of remote sensing based crop mapping in DSS4NAFA.[Method] Taking Daya Bay nuclear power base as a case study，we first mapped the cropland use dynamics in its surrounding areas by identifying crop rotation systems. A decision rules based model was used to identify the crop rotation systems combining Sentinel-1 Synthetic Aperture Radar and Sentinel-2 MultiSpectral satellite images. Then the cropland use maps were post-processed and uploaded to DSS4NAFA，based on which we realized the automatic assignment of crop sampling task and simulation of spatiotemporal distribution of radionuclide concentration.[Result] The proposed decision rules based model could be used to produce accurate and dynamic cropland use maps in areas with fragmented cropland and dense clouds. Spatially，the central region is dominated by vegetable and paddy systems，while the eastern region is mainly paddy and orchard systems. And vegetable systems are widely distributed in the western region. The cropland use maps post-processed can be easily applied to DSS4NAFA，and thereby assist in the automatic assignment of crop sample points，and the simulation of spatiotemporal distribution of radionuclide concentration.[Conclusion] The combination of remote sensing based crop mapping and DSS4NAFA further improves the effectiveness of sampling task assignment and spatiotemporal radionuclide concentration simulation. Thus it could help decision-makers draw up plans for nuclear pollution monitoring，evaluation，and remediation，and guide the recovery of agricultural production. In the future，it is necessary to deeply study the application of remote sensing based crop mapping in DSS4NAFA，and make full use of the advantages of remote sensing technology and data，avoiding the risk of nuclear accident to agricultural production. |
| Key words: Daya Bay nuclear power station nuclear accident Guangdong Google Earth Engine Sentinel data |
