Hyperspectral remote sensing has become one of the research frontiers in ground object identification and classification. On the basis of reviewing the application of hyperspectral remote sensing in identification and...Hyperspectral remote sensing has become one of the research frontiers in ground object identification and classification. On the basis of reviewing the application of hyperspectral remote sensing in identification and classification of ground objects at home and abroad. The research results of identification and classification of forest tree species, grassland and urban land features were summarized. Then the researches of classification methods were summarized. Finally the prospects of hyperspectral remote sensing in ground object identification and classification were prospected.展开更多
"视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"..."视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"算法。首先,对训练图像进行TOI选取,用灰度共生矩阵模型提取TOI的纹理特征,再结合灰度特征,组成多维特征向量集,以簇内相似度最高、数据分布密度最大为准则,生成"视觉词袋"。其次,对测试图像,依据已生成的"视觉词袋",采用支持向量机(Support Vector Machine,SVM)分类器,实现SAR图像感兴趣目标的有效分类。实验结果表明,与传统的"视觉词袋"构建算法相比,该算法在分类正确率提高的同时,能够在训练图像较少的情况下达到良好的分类效果。展开更多
It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer stud...It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer studies, however, have examined the particle density, and the size and shape characteristics of particles, which may have important implications for evaluating the particle capture efficiency of plants, and identifying the particle sources. In addition, the role of different vegetation types is as yet unclear. Here, we chose three species of different vegetation types, and firstly applied an object-based classification approach to automatically identify the particles from scanning electron microscope（SEM）micrographs. We then quantified the particle capture efficiency, and the major sources of particles were identified. We found（1） Rosa xanthina Lindl（shrub species） had greater retention efficiency than Broussonetia papyrifera（broadleaf species） and Pinus bungeana Zucc.（coniferous species）, in terms of particle number and particle area cover.（2） 97.9% of the identified particles had diameter ≤10 μm, and 67.1% of them had diameter ≤2.5 μm. 89.8% of the particles had smooth boundaries, with 23.4% of them being nearly spherical.（3） 32.4%–74.1% of the particles were generated from bare soil and construction activities, and 15.5%–23.0% were mainly from vehicle exhaust and cooking fumes.展开更多
Multi-channel polarization optical technology is increasingly used for prompt monitoring of water systems.Optical devices during the assessment of water quality determine the intensity of light through the studied aqu...Multi-channel polarization optical technology is increasingly used for prompt monitoring of water systems.Optical devices during the assessment of water quality determine the intensity of light through the studied aquatic environment.Spectrophotometric devices measure the spectrum of weakening of light through the aquatic environment.Spectroellipsometric devices receive spectra in vertical and horizontal polarizations.The presented article develops an adaptive optical hardware and image system for monitoring water bodies.The system is combined.It consists of 2 parts:1)automated spectrophotometer-refractometer,and 2)adaptive spectroellipsometer.The system is equipped with a corresponding algorithmic and software,including algorithms for identifying spectral curves,databases and knowledge of spectral curves algorithms for solving reverse problems.The presented system is original since it differs from modern foreign systems by a new method of spectrophotometric and spectroellipsometric measurements,an original elemental base of polarization optics and a comprehensive mathematical approach to assessing the quality of a water body.There are no rotating polarization elements in the system.Therefore,this makes it possible to increase the signal-to-noise ratio and,as a result,improve measurement stability and simplify multichannel spectrophotometers and spectroellipsometers.The proposed system can be used in various water systems where it is necessary to assess water quality or identify the presence of a certain set of chemical elements.展开更多
文摘Hyperspectral remote sensing has become one of the research frontiers in ground object identification and classification. On the basis of reviewing the application of hyperspectral remote sensing in identification and classification of ground objects at home and abroad. The research results of identification and classification of forest tree species, grassland and urban land features were summarized. Then the researches of classification methods were summarized. Finally the prospects of hyperspectral remote sensing in ground object identification and classification were prospected.
文摘"视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"算法。首先,对训练图像进行TOI选取,用灰度共生矩阵模型提取TOI的纹理特征,再结合灰度特征,组成多维特征向量集,以簇内相似度最高、数据分布密度最大为准则,生成"视觉词袋"。其次,对测试图像,依据已生成的"视觉词袋",采用支持向量机(Support Vector Machine,SVM)分类器,实现SAR图像感兴趣目标的有效分类。实验结果表明,与传统的"视觉词袋"构建算法相比,该算法在分类正确率提高的同时,能够在训练图像较少的情况下达到良好的分类效果。
基金supported by the “One-Hundred Talents” program of the Chinese Academy of Sciences (No. N234)the National Natural Science Foundation of China(Nos. 41430638 and 41301199)the project “Major Special Project-The China High-Resolution Earth Observation System”
文摘It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer studies, however, have examined the particle density, and the size and shape characteristics of particles, which may have important implications for evaluating the particle capture efficiency of plants, and identifying the particle sources. In addition, the role of different vegetation types is as yet unclear. Here, we chose three species of different vegetation types, and firstly applied an object-based classification approach to automatically identify the particles from scanning electron microscope（SEM）micrographs. We then quantified the particle capture efficiency, and the major sources of particles were identified. We found（1） Rosa xanthina Lindl（shrub species） had greater retention efficiency than Broussonetia papyrifera（broadleaf species） and Pinus bungeana Zucc.（coniferous species）, in terms of particle number and particle area cover.（2） 97.9% of the identified particles had diameter ≤10 μm, and 67.1% of them had diameter ≤2.5 μm. 89.8% of the particles had smooth boundaries, with 23.4% of them being nearly spherical.（3） 32.4%–74.1% of the particles were generated from bare soil and construction activities, and 15.5%–23.0% were mainly from vehicle exhaust and cooking fumes.
基金Supported By The Russian Science Foundation Grant No.23-21-00115,https://rscf.ru/en/project/23-21-00115/.
文摘Multi-channel polarization optical technology is increasingly used for prompt monitoring of water systems.Optical devices during the assessment of water quality determine the intensity of light through the studied aquatic environment.Spectrophotometric devices measure the spectrum of weakening of light through the aquatic environment.Spectroellipsometric devices receive spectra in vertical and horizontal polarizations.The presented article develops an adaptive optical hardware and image system for monitoring water bodies.The system is combined.It consists of 2 parts:1)automated spectrophotometer-refractometer,and 2)adaptive spectroellipsometer.The system is equipped with a corresponding algorithmic and software,including algorithms for identifying spectral curves,databases and knowledge of spectral curves algorithms for solving reverse problems.The presented system is original since it differs from modern foreign systems by a new method of spectrophotometric and spectroellipsometric measurements,an original elemental base of polarization optics and a comprehensive mathematical approach to assessing the quality of a water body.There are no rotating polarization elements in the system.Therefore,this makes it possible to increase the signal-to-noise ratio and,as a result,improve measurement stability and simplify multichannel spectrophotometers and spectroellipsometers.The proposed system can be used in various water systems where it is necessary to assess water quality or identify the presence of a certain set of chemical elements.
