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地物波谱特性是利用遥感进行建模反演和地物目标探测识别的理论基础，波谱数据库对于提高遥感应用水平有重要作用。为规范和丰富中国波谱数据库并促进其在测绘等领域的应用，依托国家科技性基础专项,建立了“测绘地物波谱本底数据库”，在数据规范编制、波谱数据采集实验与整编入库、地物波谱数据库建设和应用示范初步探索方面取得重要进展。在波谱数据采集和处理的标准规范方面，建立完善了测绘地物波谱与配套非波谱数据收集与汇总标准、测绘地物波谱和配套非波谱参数测试技术规范、测绘地物波谱库地物分类编码规范。依照项目制定的数据规范标准，对现有波谱数据进行了整编和入库，共计整编数据1.4万余条；组织实施了全国范围的典型地物波谱采集实验以及相应配套参数测量实验，主要试验类型包括典型地物波谱测量试验、定点时间序列测量试验、多尺度测量试验、全波段测量试验、参数控制测量试验和无人机观测试验等，共计获取地物波谱1.7万余条。特别是在华北和东北进行了全波段观测试验（可见光—近红外波（0.35—2.5 μm）、红外波段（3—15 μm）、微波波段（Ka、K、X、C、L波段）），获取冰雪、土壤、植被冠层、人工目标的全波段数据。为方便波谱数据的应用和共享，项目建设了包含3万余条数据的测绘地物波谱本底数据库（GOSPEL）及数据共享平台。依据地物波谱数据的类型和应用需求，形成了全波段典型地物波谱数据集、多角度光谱反射率数据集、多尺度典型地物反射率数据集、长时间系列波谱数据集等共25个特色数据集。基于测绘地物波谱本底数据库进行了地物分类、遥感机理模拟、遥感定量反演、遥感产品验证等方面的应用示范。 相似文献
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目前主要采用热红外遥感数据识别高温目标,研究发现短波红外数据也具有较好的高温目标识别能力。在高温目标混合像元中,高温地物的温度和面积是待求解的未知数,也是决定混合像元波谱特性的重要参数。首先基于能量守恒原理建立了地表高温目标混合像元的辐射能量方程,然后进行方程参数的敏感性分析。研究结果表明,高温目标面积百分比和常温地物反射率对高温地物的温度和面积反演最为敏感。以山西保德和陕西府谷研究区ETM+第7波段的数据为例进行了高温目标识别研究,所识别的火点像元辐射通量密度为背景的1.36~4.76倍。经野外验证,用马氏距离法识别高温目标的精度达到88%,表明短波红外波段的遥感数据可用于高温目标的识别。 相似文献
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遥感接收的信息反应了地物的电磁波特性。它的工作波段已远远超出了人眼有响应的可见光波段,而扩展至紫外、红外和微波等波段。因此要识别遥感图象必须依据各类地物在这些波段中的波谱特性。遥感中常用的扫描型传感器所记录的数值与地物的波谱值有定量的对应关系,因而准确地测定地物的波谱值,是定量遥感工作的基础。 由北京大学遥感技术应用研究所和物理学研制的RS-Ⅱ型四通道野外光谱仪,是为测定地物在可见光和近红外波段的反射率而设计的一种便携式野外光谱仪。它有四个光谱通道,这些通道的光谱范围与陆地卫星中的多光谱扫描仪(MSS)的四个波段的光谱范 相似文献
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《国土资源遥感》2016,(4)
信噪比(signal to noise ratio,SNR)是评价传感器性能的重要参数,是衡量传感器所获取的数字信号真实性的重要指标。SNR的高低对遥感数据能否得到有效利用具有至关重要的作用。任何传感器的指标设置都要以满足用户需求为出发点,因此有必要开展基于波谱模拟的红外成像仪SNR指标设置研究。首先运用已有地物波谱库数据,从数据模拟的角度出发,通过辐射传输模型,模拟得到入瞳辐亮度数据;然后生成并添加高斯白噪声,按照设计方给出的波谱响应函数进行波谱重采样,得到与设计传感器相同的波段;最后采用波谱特征拟合的方法,判别不同SNR条件下地物的可识别度。针对不同领域用户对地物识别的精度需求,给出相应的SNR建议,为传感器的设计提供科学合理的依据。 相似文献
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目前,高温目标遥感识别研究所采用的波段或光谱指数大多局限于定性分析,缺乏定量评价指标与筛选方法。为建立具有普适性的波段筛选原则及评判指标筛选方法,实现高温目标的有效识别,根据方差分析思想,构建可分性度量指标对高温目标与各类常温地物分别进行特征波段筛选,确定高温目标识别的若干有效波段,结合地物波谱特性构建并筛选高温目标最优识别指数。研究表明,经定量筛选综合确定的最优光谱指数能有效将高温目标与绝大多数常温地物区分开;在此基础上,再利用区分高温目标与易与其混淆的彩钢地物的最优识别指数进行二次识别,可进一步提高识别精度,高温目标2次识别精度分别为95. 4%和97. 6%。 相似文献
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核工业遥感地质发展的回顾及展望范泽民(北京核工业地质局)遥感是指从远距离、高空、以至外层空间的平台上,利用可见光、红外、微波等探测仪器,通过摄影或扫描方式,对地物反射或辐射电磁波能量信息进行接收、传输和处理,从而识别地面物体的性质和运动状态的一种现代化技术。 相似文献
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[本刊讯]由卢小平、王双亭主编的《遥感原理与方法》一书已于2012年8月由测绘出版社出版。该书系统叙述了当代遥感的理论、方法、过程、应用及最新进展和发展趋势。全书共分10章。第1章介绍了遥感的基本概念、基本过程、技术系统及其发展历程;第2章详细叙述了电磁波及其传播机理,包括电磁波及其特性、物体的发射辐射特性、地物的反射特性、大气对电磁波传输的影响、反射辐射和热辐射传输方程;第3章至第4章系统介绍了各种传感器及其成像原理和 相似文献
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Spectral library search is emerging as a viable approach for material identification and mapping by reusing spectral knowledge gained from hyperspectral remote sensing across space and time. The potential of retrieving meaningful spectral material identifications in the presence of reflectance of spectra of various material types and with various similarity metrics has been assessed in this study. Test reflectance spectra of various vegetation, minerals, soils and urban material types are identified by searching through the composite reflectance spectral library obtained by combining various institutional reflectance spectral libraries. The accuracy of material identifications under various conditions: (i) in the presence of identical, similar and dissimilar spectra; (ii) in the presence of only identical and dissimilar spectra; and (iii) in the presence of only dissimilar spectra has been assessed with several similarity metrics. Results indicate the possibility of obtaining 100% accurate material identifications by library search if the spectral library contains identical spectra. However, the presence of a large number of similar spectra, despite the presence of identical spectra, is found to increase false positives, thereby reducing the accuracy of retrievals to 82% at best. Further, the accuracy of material identifications in the presence of similar spectra is similarity metric-dependent and varied from about 52% (obtained from Binary Encoding) to 82% (obtained from Normalized Spectral Similarity Score). Overall, results support the possibility of using independent reflectance spectral libraries for material identification while calling for robust spectral similarity metrics. 相似文献
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Yuanjin Xu Zhenfei Zhang Guangdao Hu 《Journal of the Indian Society of Remote Sensing》2010,38(2):169-178
In order to accurately identify ground objects in the hyperspectral imagery by spectral matching, it is important to analyze
the absorption-band parameters. This paper presents a new spectral matching method which is based mainly on analysis of the
absorption-band position. A measured spectrum of a ground object can be subject to shifts from its real wavelength position;
meanwhile an absorption band in the spectrum can also be shifted relatively. Both these shifts are due to the environmental
effects. Our spectral matching method stresses the quantification of the total shift of the absorption-band position, thus
to get a possible offset range of the measured absorption bands. This offset range is taken as a constraint on the matching
process. The pixel spectrum in the image is then compared to each known reference spectrum in a spectral library previously
built, so that the ground object corresponding to the reference spectrum is identified. A case study is conducted in Pulang
Porphyry Copper deposit, Zhongdian county, Yunnan, China. Five types of ground objects were studied and it is shown that our
methods can get more accurate identification results than the approach which does not consider the shift ranges. 相似文献
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基于线性混合模型的端元提取方法综述 总被引：3，自引：1，他引：2
混合像元是遥感领域研究的热点,而基于线性混合模型的光谱解混合技术正在越来越广泛地应用在光谱数据分析和遥感地物量化中,这项技术的关键就在于确定端元光谱。本文归纳了目前几种比较成熟的端元提取算法,分析了它们的主要思想和存在的优缺点,最后介绍了端元提取技术的应用及其发展趋势。 相似文献
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Rama Rao Nidamanuri 《国际地球制图》2016,31(8):845-859
Modern hyperspectral imaging and non-imaging spectroradiometer has the capability to acquire high-resolution spectral reflectance data required for surface materials identification and mapping. Spectral similarity metrics, due to their mathematical simplicity and insensitiveness to the number of reference labelled spectra, have been increasingly used for material mapping by labelling reflectance spectra in hyperspectral data labelling. For a particular hyperspectral data set, the accuracy of spectral labelling depends considerably upon the degree of unambiguous spectral matching achieved by the spectral similarity metric used. In this work, we propose a new methodology for quantifying spectral similarity for hyperspectral data labelling for surface materials identification. Developed adopting the multiple classifier system architecture, the proposed methodology unifies into a single framework the differential performances of eight different spectral similarity metrics for the quantification of spectral matching for surface materials. The proposed methodology has been implemented on two types of hyperspectral data viz. image (airborne hyperspectral images) and non-image (library spectra) for numerous surface materials identification. Further, the performance of the proposed methodology has been compared with the support vector machines (SVM) approach, and with all the base spectral similarity metrics. The results indicate that, for the hyperspectral images, the performance of the proposed methodology is comparable with that of the SVM. For the library spectra, the proposed methodology shows a consistently higher (increase of about 30% when compared to SVM) classification accuracy. The proposed methodology has the potential to serve as a general library search method for materials identification using hyperspectral data. 相似文献
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Spectral feature fitting (SFF) is a commonly used strategy for hyperspectral imagery analysis to discriminate ground targets. Compared to other image analysis techniques, SFF does not secure higher accuracy in extracting image information in all circumstances. Multi range spectral feature fitting (MRSFF) from ENVI software allows user to focus on those interesting spectral features to yield better performance. Thus spectral wavelength ranges and their corresponding weights must be determined. The purpose of this article is to demonstrate the performance of MRSFF in oilseed rape planting area extraction. A practical method for defining the weighted values, the variance coefficient weight method, was proposed to set up criterion. Oilseed rape field canopy spectra from the whole growth stage were collected prior to investigating its phenological varieties; oilseed rape endmember spectra were extracted from the Hyperion image as identifying samples to be used in analyzing the oilseed rape field. Wavelength range divisions were determined by the difference between field-measured spectra and image spectra, and image spectral variance coefficient weights for each wavelength range were calculated corresponding to field-measured spectra from the closest date. By using MRSFF, wavelength ranges were classified to characterize the target's spectral features without compromising spectral profile's entirety. The analysis was substantially successful in extracting oilseed rape planting areas (RMSE ≤ 0.06), and the RMSE histogram indicated a superior result compared to a conventional SFF. Accuracy assessment was based on the mapping result compared with spectral angle mapping (SAM) and the normalized difference vegetation index (NDVI). The MRSFF yielded a robust, convincible result and, therefore, may further the use of hyperspectral imagery in precision agriculture. 相似文献
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Understanding the Unique Spectral Signature of Winter Rape 总被引：1，自引：0，他引：1
Driven by significant technological developments in the hyperspectral imaging, material mapping using reference spectra has received renewed interest of the remote sensing community. The applicability of reference spectral signatures in image classification depends mainly on the material type and its spectral signature behaviour. Identification and spectral characterization of materials which exhibit unique spectral behaviour is the first step in this approach. Consequently there have been active researches for the identification of surface materials which exhibit unique spectral signatures. The uniqueness of reflectance signature of winter rape relative to its co-occurring crop species was reported in this study. Reflectance spectral libraries constructed from field spectral reflectance measurements collected over five agricultural crops (alfalfa, winter barley, winter rape, winter rye, and winter wheat) during four subsequent growing seasons were classified by the linear discriminant analysis (LDA). Further, the reference field spectral database was used for the spectral feature fitting and classification of a historical HyMAP airborne hyperspectral imagery acquired at a separate site, by spectral library search. Results indicate the existence of a meaningful spectral matching between image and field spectra for winter rape and demonstrate the potential for transferring spectral library for hyperspectral image classification. The observed consistency in the discrimination of winter rape demonstrates experimentally the fundamental principle of remote sensing which suggests the theoretical existence of unique spectral signatures for materials which can be incorporated as reference spectral signatures for hyperspectral image classification. 相似文献
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Mingchang Wang Xuefeng Niu Qian Yang Shengbo Chen Guodong Yang Fengyan Wang 《Journal of the Indian Society of Remote Sensing》2018,46(1):1-8
Hyper spectral remote sensing is widely used to identify ground objects as a result of the advantages of ground radiation intensity characteristics and spectral position characteristics, in which inversion of vegetation components is the difficult point and hotspot. In this study, Huma county of Heilongjiang Province was selected as the study area, the canopy spectra of four types of typical vegetation were measured in situ firstly, including mongolian oak, cotton grass, lespedeza and white birch. Then, on the basis of analyzing the canopy spectral characteristics and their parameterization, the spectral differences of different vegetations were located, and the parameterization method of characteristics identification was determined. Finally, Hyperion data were used to calculate the canopy albedos based on the bidirectional reflectance model of vegetation canopies, and to map the vegetation components in the study area by use of linear spectral mixture model. The results showed that inversion of vegetation components in high vegetation-covered area was accurate using the canopy albedos and liner spectral mixture model, and was identical with the field sampling, which validated the feasibility of canopy albedos and liner spectral mixture model for the inversion of vegetation components. 相似文献
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面向地质应用的天宫一号成像光谱数据评价 总被引：1，自引：1，他引：0
天宫一号高光谱数据是继美国Hyperion之后,另一种可应用于地质领域的成像光谱数据.面向地质应用特点与需求,针对反射率产品开展全面、定量的数据质量评价对于深化应用研究具有重要意义.但是,由于航天成像光谱数据与地面实测波谱空间尺度差异甚大,在荒漠戈壁区选取自然地物进行波谱测试,并对其开展评价,特别是定量评价,非常困难.本文以航空HyMap数据为传递,完成了天宫一号成像光谱数据质量的定量评价.结果表明,在矿物识别采用的主要短波红外谱段,天宫一号高光谱数据的信噪比明显优于Hyperion数据.采用2190—2230 nm、2310—2355 nm两个谱段的吸收深度初步对天宫一号高光谱短波红外数据真实性进行了评价,经过校正后,天宫一号数据Al-OH、Mg-OH/CO32-矿物大类或组合的漏提率从71%、67%减小至29%、28%,可有效提高弱信息的检出率. 相似文献
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针对当前遥感数据缺乏统一文件格式标准,多源遥感产品的生产使用涉及多种文件格式的现状,在研究多种遥感数据格式及对应库GDAL、HDF4、HDF5的基础上,参考国家气象局的NOAA AVHRR 1B格式标准,利用工厂模式,设计和实现了一个具有统一操作接口的多源遥感数据格式抽象库DFAL,在更高的抽象层次解决了GDAL和HDF4、HDF5库不能一致使用的问题。使用DFAL库进行不同文件格式的读写,专家无需了解这些文件格式的差别,以便从繁杂的遥感数据格式中解放出来,将更多精力投入到遥感科学研究的层面上。在DFAL库的基础上实现了两类常用遥感数据格式Geo TIFF和HDF5之间的转换工具,方便工程应用。DFAL库及转换工具在国家高技术研究发展计划《星机地综合定量遥感系统与应用示范》的多尺度按需定量遥感产品生产系统中进行了应用测试,取得了很好的实际效果,证明了DFAL库稳定性和可用性,并大大减少了多源数据协同使用时多种文件格式读写的工作量。 相似文献