共查询到20条相似文献，搜索用时 32 毫秒
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Peter Gege Jochen Fries Peter Haschberger Paul Schtz Horst Schwarzer Peter Strobl Birgit Suhr Gerd Ulbrich Willem Jan Vreeling 《ISPRS Journal of Photogrammetry and Remote Sensing》2009,64(4):387-397
A new facility designed to perform calibration measurements of airborne imaging spectrometers was established at the German Aerospace Center (DLR) in Oberpfaffenhofen. This Calibration Home Base (CHB) is optimized to characterize radiometrically, spectrally, and geometrically the APEX (Airborne Prism Experiment) imaging spectrometer, which is currently being developed under the authority of the European Space Agency (ESA). It however can be used for other optical sensors as well. Computer control of major laboratory equipment allows automation of time consuming measurements. In APEX configuration (wavelength range: 380 to 2500 nm, instantaneous field of view: 0.48 mrad, field of view: ±14) spectral measurements can be performed to a wavelength uncertainty of ±0.15 nm, geometric measurements at increments of 0.0017 mrad across track and 0.0076 mrad along track, and radiometric measurements to an uncertainty of ±3% relative to national standard. The CHB can be adapted to similar sensors (including those with thermal infrared detectors) by exchanging the monochromator’s lamp, the gratings and the filters, and by adjusting the distance between the sensor and folding mirror. 相似文献
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星载高光谱成像光谱仪的特性与应用 总被引：6，自引：2，他引：6
介绍了星载高光谱成像光谱仪的种类、技术参数和数据特点,指出了成像光谱数据处理软件包应具有的功能,概括了成像光谱仪数据的应用前景。 相似文献
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改进APEX算法在图像增强中的应用 总被引：2，自引：0，他引：2
APEX是一种基于快速傅立叶变换的直接盲解卷积算法,能够快速复原复杂纹理图像.该算法适用于平移不变且以2维放射对称Le'vy Stable概率密度函数(G类点扩散函数)作为卷积核的图像.论述了APEX算法的原理,并针对APEX在适应性和稳定性方面的不足提出了改进方法.实验表明,改进的APEX算法能够有效应用在多种真实模糊图像上,增强图像对比度和锐化图像细节,使图像的视觉效果得到明显改善. 相似文献
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高光谱遥感技术在地质领域中的应用 总被引：1，自引：0，他引：1
近年来,高光谱应用技术在地质领域得到了深入的应用与发展,不仅深化了地质学的基础研究,也推动着遥感地质填图从岩性填图向矿物填图的飞跃,推进了高光谱遥感技术在成矿预测、地质成生环境成因信息探测、植被地化信息与理化信息提取以及矿山环境调查等应用的不断深入。本文围绕高光谱技术的特点,并结合作者近年来的工作实践,论述了高光谱技术在上述领域的实际应用情况与应用效果。 相似文献
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高光谱影像具有\"谱像合一\"的特征,因而可以从谱和像两个角度对高光谱影像进行分形分析。本文把计算表面分形维的双层地毯法用于计算Hyperion高光谱曲线的分形维,根据每一像元的高光谱曲线计算出每一尺度的上分形信号和下分形信号,并对分形信号值及分形特征尺度进行分析。结果表明对于不同地物其分形信号在某些特定尺度（分形特征尺度）有较大的差异,而且对于Hyperion高光谱影像,下分形信号可更有效地突出地物特征。文章最后简要讨论了上分形和下分形、起始计算尺度以及原始采样点数目对分形特征尺度的影响。 相似文献
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In this study, a high spectral resolution GER-2600 spectroradiometer was used to obtain the spectral data of soil samples that were polluted with four different types of petroleum–hydrocarbons products: Diesel, Gasoline, Crude Oil and Fuel Oil. The polluted soil samples were prepared in the laboratory at five concentrations levels: unpolluted soil, 2500, 100,000, 250,000 ppm and pure pollutant. Spectral data were pre-processed and then analysed with various approaches: Principal Components Transformation and ANOVA, Spectral Angle Mapper (SAM), Hydrocarbon Index (HI) and Spectral Mixture Analysis (SMA). The results showed that it was possible to determine the different spectral response between clean soil and some of the polluted soils: crude oil at concentrations higher than 100,000 ppm were the easiest to recognize; while samples polluted with gasoline at concentrations below 250,000 ppm were the most difficult to distinguish from non-polluted samples. 相似文献
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Mbongowo J. Mbuh 《国际地球制图》2013,28(12):1326-1349
AbstractPhosphorus and nitrogen have a strong influence on water resource and remote sensing technology has demonstrated that water quality monitoring over a greater range of temporal and spatial scales can be used to overcome these constraints. This research was designed to demonstrate the feasibility of combining remotely-sensed water quality observation and chemometric techniques to estimate water quality in the Shenandoah River. We used Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) imagery, combined with a partial least squares analysis to characterize the spatial distribution of nutrients in the Sheanadoah river. ARCHER retrievals for phosphorous with cross-validation show high sensitivity in estimating water quality in the Shenandoah River with the Bentonville in the South Fork, with an R2 of 0.93 sensitivity. Using the significance level of 0.05, data from the summer of 2014 showed that the p-value was 0.00 for both nitrogen and phosphorous. Results show retrieval method is transferable. 相似文献
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Gladys Villegas Wenzhi Liao Ronald Criollo Wilfried Philips Daniel Ochoa 《地球空间信息科学学报》2017,20(4):325-332
AbstractClose-range hyperspectral images are a promising source of information in plant biology, in particular, for in vivo study of physiological changes. In this study, we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological information. The detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation, disease infections, and environmental conditions have in plants. We tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote sensing. Experimental results demonstrate the efficiency of our fusion approach, with significant improvements over some conventional methods. 相似文献
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Thaumastocoris peregrinus (T. peregrinus) is a sap sucking insect that feeds on Eucalyptus leaves. It poses a threat to the forest industry by reducing the photosynthetic ability of the tree, resulting in stunted growth and even death of severely infested trees. Remote sensing techniques offer the potential to detect and map T. peregrinus infestations in plantation forests using current operational hyperspectral scanners. This study resampled field spectral data measured from a field spectrometer to the band settings of the Hyperion sensor in order to assess its potential in predicting T. peregrinus damage. Normalized indices based on NDVI ratios were calculated using the resampled visible and near-infrared bands of the Hyperion sensor to assess its utility in predicting T. peregrinus damage using Partial Least Squares (PLS) regression. The top 20 normalized indices were based on specific biochemical absorption features that predicted T. peregrinus damage with a mean bootstrapped R2 value of 0.63 on an independent test dataset. The top 20 indices were located in the near-infrared region between 803.3 nm and 894.9 nm. Twenty three previously published hyperspectral indices which have been used to assess stress in vegetation were also used to predict T. peregrinus damage and resulted in a mean bootstrapped R2 value of 0.59 on an independent test dataset. The datasets were combined to assess its collective strength in predicting T. peregrinus damage and significant indices were chosen based on variable importance scores (VIP) and were then entered into a PLS model. The indices chosen by VIP predicted T. peregrinus damage with a mean bootstrapped R2 value of 0.71 on an independent test dataset. A greedy backward variable selection model was further tested on the VIP selected indices in order to find the best subset of indices with the best predictive accuracy. The greedy backward variable selection model identified 3 indices and performed the best by predicting damage with an R2 value of 0.74 with the lowest RMSE of 1.30% on an independent test dataset. The best three indices identified include the anthocyanin reflectance index, carotenoid reflectance index and the normalized index calculated at 864.4 and 884.7 nm. Individual relationships between these indices and T. peregrinus damage indicate that high correlations are obtained with the inclusion of a few severely infested trees in the sample size. When the severely infested trees were removed from the study, the normalized index (864.4 and 884.7 nm) and the anthocyanin reflectance index still yielded significant correlations at the 99% confidence interval. This study indicates the significance of normalized indices and spectral indices calculated from the visible and near-infrared bands in hyperspectral data for the prediction of T. peregrinus damage. 相似文献
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A fast endmember-extraction algorithm based on Gaussian Elimination Method (GEM) is proposed in this paper under the fact that a pixel is an endmember if it has the maximum value in any spectral band of a hyperspectral image when based on linear mixing model. Applying Gaussian elimination is much like performing a lower triangular matrix to transform the hyperspectral image. As more endmembers have been extracted, fewer bands are needed to be involved in the Gaussian elimination process, thus greatly reducing the computing time. The experimental results with both simulated and real hyperspectral images indicate that the method proposed here is much faster than the vertex component analysis (VCA) method, and can provide a similar performance with VCA. 相似文献
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The estimation of above ground biomass in forests is critical for carbon cycle modeling and climate change mitigation programs. Small footprint lidar provides accurate biomass estimates, but its application in tropical forests has been limited, particularly in Africa. Hyperspectral data record canopy spectral information that is potentially related to forest biomass. To assess lidar ability to retrieve biomass in an African forest and the usefulness of including hyperspectral information, we modeled biomass using small footprint lidar metrics as well as airborne hyperspectral bands and derived vegetation indexes. Partial Least Square Regression (PLSR) was adopted to cope with multiple inputs and multicollinearity issues; the Variable of Importance in the Projection was calculated to evaluate importance of individual predictors for biomass. Our findings showed that the integration of hyperspectral bands (R2 = 0.70) improved the model based on lidar alone (R2 = 0.64), this encouraging result call for additional research to clarify the possible role of hyperspectral data in tropical regions. Replacing the hyperspectral bands with vegetation indexes resulted in a smaller improvement (R2 = 0.67). Hyperspectral bands had limited predictive power (R2 = 0.36) when used alone. This analysis proves the efficiency of using PLSR with small-footprint lidar and high resolution hyperspectral data in tropical forests for biomass estimation. Results also suggest that high quality ground truth data is crucial for lidar-based AGB estimates in tropical African forests, especially if airborne lidar is used as an intermediate step of upscaling field-measured AGB to a larger area. 相似文献
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由于高光谱数据的海量高维特征,使得传统的信息系统难以有效地对这些数据进行高效地存储、处理、分析,表现等管理操作。因此如何采用新的技术来开发一个能有效管理高光谱遥感影像数据的影像管理系统,是当前高光谱快速发展和深入应用的一个瓶颈之一。本文在研究的过程中,对当前影像管理系统的发展作了大量的分析,利用成熟的关系数据库和程序设计语言,开发了一个方便实用的高光谱遥感影像管理系统以管理高光遥感影像和其他遥感信息,提高影像管理效率。系统已初步实现了多景高光谱遥感影像检索,可以任意加载、导入高光谱遥感影像,运行效果良好。 相似文献
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高光谱数据处理及在铀资源勘查中的应用——以广西苗儿山地区为例 总被引：4，自引：0，他引：4
以广西苗儿山地区机载成像细分红外高光谱数据为例,探讨了高光谱数据的特点及其处理方法。编制了一系列数据预处理软件,对图像进行了条带去除、波段间配准、航向压缩、镜向变换、辐射校正、正切校正、相对反射率转换等预处理,获得了高质量图像; 在 ENVI软件基础上建立了研究区野外实测光谱曲线库及分类子库,并对各子库进行了系统研究。同时,提出了正确的图像配准方案,对图像进行了精校正和镶嵌,取得了满意的效果; 在纯净像元提取、混合像元分解、匹配滤波、光谱特征拟合等方面进行了探索,提取了该区铀矿化的特征光谱信息; 最后,探讨了高光谱数据的地质应用潜力,尤其在硅化带识别方面的应用取得了成功,发现了一系列的新的含铀硅化断裂带,预测了三个成矿有利地段。经验证,其中两片地区的铀明显偏高并有矿化显示。 相似文献
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M. van der Meijde H.M.A. van der Werff P.F. Jansma F.D. van der Meer G.J. Groothuis 《International Journal of Applied Earth Observation and Geoinformation》2009
Leakage of hydrocarbon has a large economic and environmental impact. Traditional methods for investigating leakage and resulting pollution, such as drilling, are destructive, time consuming and expensive. Remote sensing is an alternative that is non-destructive and has been been tested extensively for exploration of onshore hydrocarbon reservoirs and detection of hydrocarbons at the Earth’s surface. In this research, a leaking pipeline is investigated through field reflectance spectrometry and the findings are validated with traditional drilling and geophysical measurements. The measurements show a significant increase of vegetation anomalies on the pipeline with respect to areas further away. The observed anomalies are positively related to hydrocarbon pollution through chemical analysis of drillings. Subsurface geophysical measurements show a large correlation with observed surface vegetation stress, enhancing the identification of hydrocarbon-related vegetation stress through spectroscopy. 相似文献
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Hyperspectral Unmixing (HU) has received increasing attention in the past decades due to its ability of unveiling information latent in hyperspectral data. Unfortunately, most existing methods fail to take advantage of the spatial information in data. To overcome this limitation, we propose a Structured Sparse regularized Nonnegative Matrix Factorization (SS-NMF) method based on the following two aspects. First, we incorporate a graph Laplacian to encode the manifold structures embedded in the hyperspectral data space. In this way, the highly similar neighboring pixels can be grouped together. Second, the lasso penalty is employed in SS-NMF for the fact that pixels in the same manifold structure are sparsely mixed by a common set of relevant bases. These two factors act as a new structured sparse constraint. With this constraint, our method can learn a compact space, where highly similar pixels are grouped to share correlated sparse representations. Experiments on real hyperspectral data sets with different noise levels demonstrate that our method outperforms the state-of-the-art methods significantly. 相似文献