Subjects: Nuclear Science and Technology >> Nuclear Detection Technology and Nuclear Electronics submitted time 2024-04-26
Abstract： [Background]: The High Energy Cosmic Radiation Detection Facility (HERD) is a flagship scientific instrument planned to be deployed on the Chinese Space Station, aiming to indirectly detect dark matter, accurately measure cosmic ray compositions, and conduct surveys of high-energy gamma-ray emissions. Among them, the silicon charge detector is one of the key components of HERD, used to measure the charges of cosmic rays ranging from hydrogen to nickel.[Purpose]: To validate and analyze the charge measurement capability of silicon charge detectors, a ground test system was designed for a prototype silicon charge detector beamline.[Methods]: The ground test system utilizes Xilinx's ZYNQ UltraScale+ MPSoC chip as the control chip, achieving functions including LVDS data reception, encoding and decoding, RS-422 control, and gigabit Ethernet data reception and storage. [Results]: The silicon charge detector beamline prototype participated in heavy ion beam experiments at the European Nuclear Research Center, with the ground test system collecting 100G of experimental data during the beamline experiments. [Conclusions]: The Ground Test system demonstrated good stability and reliability during the beam experiment, providing important technical support and data foundation for subsequent experiments of the HERD project's silicon charge detector.
Subjects: Geosciences >> Other Disciplines of Geosciences submitted time 2019-09-10 Cooperative journals: 《干旱区研究》
Abstract：当前基于中等空间分辨率时序数据的农作物种植结构提取成为研究热点，但农作物季相节律特征在不同气候背景下存在较大差异，绿洲作为干旱区具有明显小气候效应的生态景观，其农作物种植结构的遥感提取具有较强的典型性和代表性。选取宁夏河套平原绿洲典型区域，通过构建高分一号（GF-1/WFV）时间序列数据，结合不同作物耕作方式及生长物候，分析不同作物在整个生长季内的归一化植被指数（NDVI）和归一化水体指数（NDWI）的时间序列特征，构建不同决策树提取研究区农作物种植结构信息，并验证了不同方法的适用性。结果表明，对具有明显小气候效应的干旱区绿洲，利用时间分辨率和空间分辨率都较优的GF1-WFV时间序列数据，对其农作物种植结构进行遥感提取具有较强的实用性和代表性。
Subjects: Geosciences >> Other Disciplines of Geosciences submitted time 2019-09-10 Cooperative journals: 《干旱区研究》
Abstract：以宁夏红寺堡区为研究区，基于高分一号（GF-1/WFV）卫星构建葡萄生长季时间序列光谱数据，运用(Jeffreys-Matusita)(J-M)距离分析葡萄地块归一化植被指数（NDVI）时序曲线特征确定了最佳识别时相，将最佳时相的NDVI、相邻时相差值速率和曲线积分训练样本集导入Clementine数据挖掘软件中，利用C5.0决策树分类算法，并结合专家经验法构建葡萄林决策树提取模型。结果表明：构建的识别模型能够满足葡萄的识别需求，但在不同覆盖度的葡萄地块上精度有所差异；基于决策树分类的总体精度为93.71%，Kappa系数为0.91。其中，中低覆盖度葡萄林生产精度为90.82%，用户精度为88.56%；高覆盖度葡萄林生产精度为92.44%，用户精度为91.18%。
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