Extraction of Soil Organic Matter Information by Multi-spectral Remote Sensing Based on Diverse Landforms

Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil organic matter content in different landforms. The results showed that the spectral reflectance was nega- tively related to soil organic matter content; linear regression analysis of remove was performed throughout the bands using SPSS. When the inversion models were built based on all the bands, better fitting effect was obtained. The precision of in- version models built based on different landforms was higher than those built re- gardless landforms. Compared with the actual value, the identification level of soil organic matter content was 91 65% under the allowable error was 7%. It indicated that the extraction of soil organic matter with inversion model that was built based on different landforrrs was feasible with higher precision.

Low-dimensional multi-spectral space for color reproduction based on nonnegative constrained principal component analysis

In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.

Extracting Feature Bands for Damaged Rice Leaves by Planthoppers Using Multi-spectral Imaging Technology

[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] The experiment, using multi-spectral imaging system, acquired the multi-spectral images of damaged rice leaves from band 400 to 720 nm by interval of 5 nm. [Result] According to the principle of band index, it was calculated that the bands at 515, 510, 710, 555, 630, 535, 505, 530 and 595 nm were having high band index value with rich information and little correlation. Furthermore, the experiment used two classification methods and calcu-lated the classification accuracy higher than 90.00% for feature bands and ful bands of damaged rice leaves by planthoppers respectively. [Conclusion] It can be con-cluded that these bands can be considered as effective feature bands to identify damaged rice leaves by planthoppers quickly from a large scale of crops.

Robust key point descriptor for multi-spectral image matching

Histogram of collinear gradient-enhanced coding （HCGEC）, a robust key point descriptor for multi-spectral image matching, is proposed. The HCGEC mainly encodes rough structures within an image and suppresses detailed textural information, which is desirable in multi-spectral image matching. Experiments on two multi-spectral data sets demonstrate that the proposed descriptor can yield significantly better results than some state-of- the-art descriptors.

MULTI-SPECTRAL AND HYPERSPECTRAL IMAGE FUSION USING 3-D WAVELET TRANSFORM

Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional （3-D） feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures： Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling （RIBSR）method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution （A＆S） rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A＆S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.

Chlorophyll Content Retrieval of Rice Canopy with Multi-spectral Inversion Based on LS-SVR Algorithm

To monitor growth and predict the yield of rice over a large area, the chlorophyll contents in the rice canopy were estimated using the unmanned aerial vehicle(UAV) remote sensing technology. In this work, multi-spectral image information of the rice crop was obtained using a 6-channel multi-spectral camera mounted on a fixed wing UAV, which was flown 600 m above the ground, between 11: 00-14: 00 on a sunny day in summer. The measured chlorophyll values were collected as sample sets. The s-REP index was screened out to estimate chlorophyll contents through the analysis of six kinds of spectral indexes of chlorophyll estimated capacity. An inversion model of the chlorophyll contents was then built using the least square support vector regression(LS-SVR)algorithm, with calibration and prediction R-square values of 0.89 and 0.83, respectively. Finally, remote sensing mapping for a UAV image of the Fangzheng County Dexter Rice Planting Park was accomplished using the inversion model. The inversion and measured values were then compared using regression fitting. R-square and root-mean-square error of the fitting model were 0.79 and 2.39,respectively. The results demonstrated that accurate estimation of rice-canopy chlorophyll contents was feasible using the LS-SVR inversion model developed using the s-REP vegetation index.

Multi-Spectral and Fluorescence Imaging in Prevention of Overdose of Herbicides: The Case of Maize

Evaluation of the impact of herbicides on maize was done through multi- spectral and multi-modal imaging and multi-spectral fluorescence imaging combined with statistical methods. Spectra containing 13 wavelengths ranging from 375 nm to 940 nm were derived from multi-spectral images in transmission, reflection and scattering mode and fluorescence images obtained using high-pass filters (F450 nm, F500 nm, F550 nm, F600 nm, F650 nm) on control maize samples and maize samples treated with Herbextra herbicide were used. The appearance of the spectra allowed us to characterize the effect of the herbicide on the maize pigment concentration. The fluorescence images allowed us to track the fate of absorbed energy and through PLS-DA and SVM-DA to discriminate the two leaf categories with very low error rates for the test, i.e. 4.9% and 2% respectively. The results of this technique can be used in the context of precision agriculture.

New Abnormal Cervical Cell Detection Method of Multi-Spectral Pap Smears

Considering the problem of traditional cervical cancer detection method that brings high false negative rate （FNR） and high false positive rate （FPR）, a new abnormal cervical cells detection method of multi-spectral Pap smear is proposed in this thesis, on the basis of multi-spectral microscopic imaging technology and computer automotive recognition technology. At first, image in a specific wave band is segmented according to the relationship between intensity and spectrum of each pixel. Then, multi-spectral features of each pixel are extracted making use of improved cosine correlation analysis （CCA） algorithm. Combined with the characteristic of each cell＇s area, final definition is made. Experiments have proved the new approach could identify abnormal cells efficiently as well as lower FNR and FPR.

Solar Multi-Spectral Radiometric Observations of Atmospheric Optical Thickness over Passarlapudi Gas Well Blow-Out Site in India

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In Situ Atomic Reconstruction Engineering Modulating Graphene-Like MXene-Based Multifunctional Electromagnetic Devices Covering Multi-Spectrum

With the diversified development of big data,detection and precision guidance technologies,electromagnetic(EM)functional materials and devices serving multiple spectrums have become a hot topic.Exploring the multispectral response of materials is a challenging and meaningful scientific question.In this study,MXene/TiO_(2)hybrids with tunable conduction loss and polarization relaxation are fabricated by in situ atomic reconstruction engineering.More importantly,MXene/TiO_(2)hybrids exhibit adjustable spectral responses in the GHz,infrared and visible spectrums,and several EM devices are constructed based on this.An antenna array provides excellent EM energy harvesting in multiple microwave bands,with|S11|up to−63.2 dB,and can be tuned by the degree of bending.An ultra-wideband bandpass filter realizes a passband of about 5.4 GHz and effectively suppresses the transmission of EM signals in the stopband.An infrared stealth device has an emissivity of less than 0.2 in the infrared spectrum at wavelengths of 6-14μm.This work can provide new inspiration for the design and development of multifunctional,multi-spectrum EM devices.

ICESat卫星及其在南极Dome A地区的应用

概述了GLAS高度计的在轨性能,分析了其数据产品的精度。利用高精度的ICESat卫星测高数据,以及第21次中国南极科学考察内陆冰盖考察GPS的实测资料,验证了此次考察中南极内陆冰盖Dome A最高点可能区域选取的正确性,并分析了Dome A最高点位置测定的准确性。

南极Dome A地区高精度DEM的建立——顾及波形重定、坡度改正及数据融合

介绍了CryoSat-2LRM模式下优化后的OCOG、CFI和LIRT的3种波形重定算法。基于南极Dome-A昆仑站区的实测GPS数据,比较了CryoSat-2LRM模式下的3种波形重定方法,对不同波形重定算法下的测高数据进行了精度评估。结果表明优化后的OCOG算法精度最好,与GPS结果平均差值约为-0.07m,标准差约为0.60m,明显优于其他两种算法。通过比较坡度与卫星数据精度的关系,发现坡度因素对于卫星测高数据精度的影响不可忽视,在Dome A地区验证结果表明,坡度改正可使得卫星测高精度提高约38%。最后联合GPS和CryoSat-2OCOG数据,建立了南极Dome-A地区300m分辨率DEM,其精度约为0.24m。

冰雷达探测数据处理方法研究——以南极冰盖DomeA地区的数据处理为例

提出了冰雷达数据处理的流程,详细论述了冰雷达数据处理中常规修正的关键技术:静态校正、增益控制、带通滤波以及偏移处理等。以中国第24次南极科学考察(CHINARE 24)所获取的Dome A地区30 km×30 km范围冰雷达原始数据处理作为实例,提取得到了该区域冰盖内部等时层埋深以及冰盖的冰厚数据。通过插值展现了冰盖等时层以及冰岩界面的三维空间形态,结合该区域ICESat冰盖表面高程数据,构建出了Dome A地区涵盖冰盖表面、冰盖等时层以及冰岩界面形态特征的三维模型。

Dome效应对四孔大气相干长度仪系统性能的影响

以水平方向距仪器1 000 m的卤钨灯为光源,通过同步对比实验探究了两台四孔大气相干长度仪的系统性能。实验结果表明,由它们测得的大气相干长度的大小和总体变化趋势能够较好吻合,相关性系数均在0.94以上,具有较好的一致性。在此基础上,进一步研究了Dome效应对该系统性能的影响。该效应的影响主要表现在使大气相干长度变小,其强度则由系统沿光路方向移动的距离决定。当移动距离小于15 cm时,Dome效应较弱,不会对实验结果产生明显影响;在距离从15 cm增至55 cm的过程中,其强度不断增加,并在55 cm处达到最强,此后则不再随距离的增加而变化。在整个实验过程中,实验结果的相关系数始终在0.9以上,即Dome效应对大气相干长度的总体变化趋势没有明显影响。

用雷达电磁波探测研究南极冰盖浅层散射特征：以中山站至Dome A冰盖断面为例

本研究运用双频雷达(60MHz和179MHz)获取的南极中山站—Dome A断面的雷达回波探测数据,对冰盖浅部100—700m的雷达内部反射层和接收功率变化定量计算分析表明,60MHz的雷达回波能量比179MHz衰减得更快;中山站—Dome A断面冰盖浅层700m以上的雷达反射层形成的主导原因是冰密度的变化;断面上不同测站点间同一深度的接收功率差值达到10dB,表明冰盖浅层散射存在显著差异。

基于H-Dome重构的大豆图像分割

在大豆品质检测过程中,大豆图像籽粒粘连给后续检测、分析等处理带来较大的困难。为此,提出了一种基于H-Dome重构的分水岭算法,先对二值图像进行H-Dome灰度形态重构合并极值,再对重建后的图像用距离变换得到距离图像,然后利用分水岭算法进行图像分割,最后提取分割线得到最终分离图像。该算法对籽粒的分割正确率为96.6%,分割效果较好。

DOMES—一个已开发的调度操作管理专家系统

本文介绍了东南大学与安徽省调度中心用PROLOG语言合作研制开发的调度操作管理专家系统—DOMES,它能正确开出安徽省调所必需的各类调度命令票与操作票,并已在IBM-AT-286上成功地投入运行。本文描述了DOMJJ的结构、性能与功能,介绍了其数据库与规则库,简要讨论了该专家系统的进一步扩展与作用。

Pantadome体系及其施工技术

总结Pantadome体系的结构特点和施工技术,介绍日本用该技术进行实际工程的建造方法,并与我国的相关液压施工技术进行了比较,提出了我国科技界与工程界对该技术应用的努力方向。

南极中山站-Dome A断面表层雪稳定同位素空间分布及环境影响因素分析

中山站-Dome A断面是表层雪稳定同位素组成分析的理想区域,沿线进行δ18O、δD和d的空间分布及环境影响因素研究对反映东南极地区的气候变化和物质来源具有关键意义。因而,本文基于线性回归及相关性分析方法,详细探究了断面上多种环境因素与表层雪稳定同位素分布的空间关系。结果表明,温度和地理因素与同位素比值之间有显著相关关系,且海拔是地理因素中的主要影响因素,随海拔上升表层雪的δ18O呈线性下降趋势。另外,通过断面上δ-T斜率与南极其他断面对比,发现斜率可能具有冰盖近岸和内陆地区较低的区域性特征,而造成这一现象的原因是水汽源区的改变和低温条件下水汽过饱和时的同位素动力分馏。最后,d的空间分布在沿海区域和内陆区域也有不同,推测主控因素分别是水汽源区条件和温度。

中山站至DOME-A内陆冰盖考察导航系统设计

基于GPS的导航技术作为一个很热门的研究课题,其在航空、航天以及陆上车辆导航,个人移动导航等诸多领域有着深入广泛的应用。但针对南极地区这一基础地理信息缺乏,环境特殊的科考导航系统的开发研究却极其少见。本文结合移动导航技术和南极科考的实际需求,设计了中山站至DOME-A内陆冰盖考察导航系统,对系统结构、功能进行了详细设计,最终编制完成了模拟系统。