为克服无人机高光谱遥感发展过程中的成本昂贵、拍摄效率低下和地物分类结果不准确等制约因素的影响,自主研制出适用于多旋翼无人机搭载的国产轻小型可见光-近红外高光谱成像仪,全波段和视场在截止频率的平均故障时间(Mean Time to Fail...为克服无人机高光谱遥感发展过程中的成本昂贵、拍摄效率低下和地物分类结果不准确等制约因素的影响,自主研制出适用于多旋翼无人机搭载的国产轻小型可见光-近红外高光谱成像仪,全波段和视场在截止频率的平均故障时间(Mean Time to Failure,MTF)均高于0.83,光谱分辨率优于2.8 nm;成像仪与多旋翼无人机、电源、POS/IMU、稳定平台完成系统集成。在此基础上,以鄱阳湖南湖村和新疆杨庄岩体西北部为研究区,进行仪器试验应用。利用鄱阳湖南湖村获取数据像元曲线与ASD地面光谱仪同步实测的典型地物光谱进行对比分析,验证成像仪的光谱准确性,ASD地面光谱仪同步实测的典型地物光谱与无人机载高光谱影像同名地物光谱吻合度较高。经光谱重建和光谱角分类实验,结果表明:地物分类结果较为准确。新疆杨庄岩体西北部区段真彩色影像与航空有人机高光谱获取的CASI图像,赤铁矿识别与填图结果表明,成像仪在地质领域有较好应用效果,可用于更高比例尺的地质填图。总之,研制的轻小型可见光-近红外高光谱成像仪可为我国地质、生态环境等领域的调查提供一种新的技术手段。展开更多
In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is pr...In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is proposed for the hyperspectral remote sensing.In the proposed approach,the mineral identification is defined as the number of the minerals identified and the key imaging parameters employed include ground sample distance(GSD)and spectral resolution(SR).Certain limitations are found among parameters that are used for analyzing the imaging processes.The constraints include the industrial manufacturing level,application requirements and the quantitative relationship among the GSD,the SR and the signal-to-noise ratio(SNR).Regression analysis is used to investigate the quantitative relationship between the mineral identification and the key imaging system parameters.Then,an optimization model for the trade-off study is established by combining the regression equation with the constraints.The airborne hyperspectral image collected by Hymap is applied to evaluate the performance of the proposed approach.The experimental results reveal that the approach can achieve the evaluation of the mineral identification and the trade-off of key imaging system parameters.The error of the prediction is within one kind of mineral.展开更多
文摘为克服无人机高光谱遥感发展过程中的成本昂贵、拍摄效率低下和地物分类结果不准确等制约因素的影响,自主研制出适用于多旋翼无人机搭载的国产轻小型可见光-近红外高光谱成像仪,全波段和视场在截止频率的平均故障时间(Mean Time to Failure,MTF)均高于0.83,光谱分辨率优于2.8 nm;成像仪与多旋翼无人机、电源、POS/IMU、稳定平台完成系统集成。在此基础上,以鄱阳湖南湖村和新疆杨庄岩体西北部为研究区,进行仪器试验应用。利用鄱阳湖南湖村获取数据像元曲线与ASD地面光谱仪同步实测的典型地物光谱进行对比分析,验证成像仪的光谱准确性,ASD地面光谱仪同步实测的典型地物光谱与无人机载高光谱影像同名地物光谱吻合度较高。经光谱重建和光谱角分类实验,结果表明:地物分类结果较为准确。新疆杨庄岩体西北部区段真彩色影像与航空有人机高光谱获取的CASI图像,赤铁矿识别与填图结果表明,成像仪在地质领域有较好应用效果,可用于更高比例尺的地质填图。总之,研制的轻小型可见光-近红外高光谱成像仪可为我国地质、生态环境等领域的调查提供一种新的技术手段。
基金supported by the National National Natural Science Foundation of China(Grant Nos.61177008 and 61008047)the China Geological Survey(Grant No.1212011120227)+2 种基金the National High Technology Research and Development Program("863"Program)(Grant Nos.2012AA12A30801 and 2012YQ05250)the Program for Changjiang Scholars and Innovative Research Team(Grant No.IRT0705)the National Public Foundation of China(Grant No.201311036)
文摘In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is proposed for the hyperspectral remote sensing.In the proposed approach,the mineral identification is defined as the number of the minerals identified and the key imaging parameters employed include ground sample distance(GSD)and spectral resolution(SR).Certain limitations are found among parameters that are used for analyzing the imaging processes.The constraints include the industrial manufacturing level,application requirements and the quantitative relationship among the GSD,the SR and the signal-to-noise ratio(SNR).Regression analysis is used to investigate the quantitative relationship between the mineral identification and the key imaging system parameters.Then,an optimization model for the trade-off study is established by combining the regression equation with the constraints.The airborne hyperspectral image collected by Hymap is applied to evaluate the performance of the proposed approach.The experimental results reveal that the approach can achieve the evaluation of the mineral identification and the trade-off of key imaging system parameters.The error of the prediction is within one kind of mineral.