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自然资源遥感  2024, Vol. 36 Issue (4): 165-174    DOI: 10.6046/zrzyyg.2023202
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
针对起伏异质地表的一体化成像光谱仪成像建模
崔博伦1(), 李欣1, 安宁1, 仝迟鸣1, 张家铭1, 朱军2
1.北京空间机电研究所,北京 100094
2.中国东方红卫星股份有限公司,北京 100094
Imaging modeling of integrated imaging spectrometers for undulating terrain with uneven surface feature distribution
CUI Bolun1(), LI Xin1, AN Ning1, TONG Chiming1, ZHANG Jiaming1, ZHU Jun2
1. Beijing Institute of Space Mechanics and Electricity, Beijing 100094, China
2. China Spacesat Co., Ltd., Beijing 100094, China
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摘要 

一体化成像光谱仪能够有效提升陆地生态系统监测能力,在设计研制阶段开展成像仿真是提升其效能的重要手段,针对目前成像仿真中场景建模和辐射传输模型的不足,建立了一套全链路的成像仿真模型,并利用该模型初步开展了载荷效能评价。首先,根据载荷观测目标开展了大型场景异构建模; 然后,推导了包含荧光辐射和热辐射的起伏异质地表辐射传输模型; 最后,结合光栅光谱仪成像模型,最终集成为全链路成像仿真模型。为验证起伏异质地表的邻近效应对像元日光诱导叶绿素荧光(solar-induced chlorophyll fluorescence,SIF)空间分布的影响,对比本光谱仪空间分辨率下,考虑和未考虑地形邻近效应的模拟SIFred和SIFfarred辐亮度。对于地形起伏明显且地物分布非均一的列数据,SIF辐亮度差异分别最大达到22%和52%,未考虑地形邻近效应会导致高分辨率SIF仿真的显著误差。本研究的成像建模方法能够用于异质起伏地表场景的高光谱-超光谱成像仿真,从而分析一体化成像光谱仪生态监测的复合应用的效能。

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崔博伦
李欣
安宁
仝迟鸣
张家铭
朱军
关键词 高光谱全链路仿真日光诱导叶绿素荧光陆地生态监测高光谱成像    
Abstract

Integrated imaging spectrometers can effectively improve the monitoring capability of terrestrial ecosystems. Imaging simulation in the design and development of spectrometers is identified as an important means to improve their efficiency. To overcome the shortcomings of current imaging simulation in scene modeling and radiation transport models, this study developed a full-link hyperspectral imaging simulation model. Using this model, this study conducted preliminary assessments of load efficiency. First, heterogeneous modeling for large-scale scenes was conducted according to the observation targets of loads. Then, a surface radiation transport model containing fluorescence radiation and thermal radiation was derived for undulating terrain with uneven surface feature distribution (also referred to as unevenly undulating surface). Finally, by integrating the imaging model of grating spectrometers, this study established a full-link imaging simulation model. To determine the impacts of the adjacency effect of the unevenly undulating surface on the spatial distribution of solar-induced chlorophyll fluorescence (SIF), this study compared the radiance of red and far-red SIF derived with and without considering the adjacency effect of terrain under the spatial resolution of the used integrated imaging spectrometer. For data on significantly undulating terrain with uneven surface feature distribution, the SIF radiance exhibited differences of up to maxima of 22% and 52%, respectively, and ignoring the adjacency effect led to significant errors in the high-resolution SIF simulations. The imaging modeling method developed in this study can be used for hyperspectral imaging simulation of unevenly undulating surfaces, thus allowing for analyzing the efficiency of integrated imaging spectrometers for composite applications in ecological monitoring.

Key wordshyperspectral imaging simulation    solar-induced chlorophyll fluorescence    terrestrial ecological monitoring    hyperspectral imaging
收稿日期: 2023-07-11      出版日期: 2024-12-23
ZTFLH:  TP79  
基金资助:民用航天项目(D010206)
作者简介: 崔博伦(1988-),男,博士,工程师,研究方向为高光谱载荷总体设计与定量化反演。Email: boluncui@qq.com
引用本文:   
崔博伦, 李欣, 安宁, 仝迟鸣, 张家铭, 朱军. 针对起伏异质地表的一体化成像光谱仪成像建模[J]. 自然资源遥感, 2024, 36(4): 165-174.
CUI Bolun, LI Xin, AN Ning, TONG Chiming, ZHANG Jiaming, ZHU Jun. Imaging modeling of integrated imaging spectrometers for undulating terrain with uneven surface feature distribution. Remote Sensing for Natural Resources, 2024, 36(4): 165-174.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2023202      或      https://www.gtzyyg.com/CN/Y2024/V36/I4/165
Fig.1  紧凑型一体化生态监测光谱仪全链路仿真系统
Fig.2  冠层辐射传输建模输入输出参数
Fig.3  地表场景异构数据集组成
Fig.4  大气辐射传输辐照度定义
Fig.5  不同距离像元权重系数
Fig.6  光学系统成像退化过程模型
Fig.7  模拟场景输入影像数据
大气参数 取值
大气类型 中纬度夏季
气溶胶模型 Rural
CO2浓度/ ppmv 390
太阳天顶角/(°) 45
太阳方位角/(°) 180
成像天顶角/(°) 0
成像方位角/(°) 0
海拔高度/ km 0.4
轨道高度/ km 550
光谱分辨率/ cm-1 1
Tab.1  大气辐射传输建模参数
Fig.8  高光谱通道仿真结果
Fig.9  荧光通道仿真结果
Fig.10  起伏地形不同位置光谱
Fig.11  不同模式SIFfarred入瞳辐亮度对比
Fig.12  不同模式SIFred入瞳辐亮度对比
Fig.13  SIFred和SIFfarred行分布对比
Fig.14  光谱通道数值产品
Fig.15  地形起伏区SIF分布
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