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801.
不同插值方法对CORS高程时间序列的影响分析 总被引:2,自引:0,他引:2
在CORS站高程时间序列的研究中,当连续缺失较多数据时,插值显得尤为重要。为了较好地解决这个问题,本文尝试采用正交多项式拟合的方法,分别利用正交多项式拟合、拉格朗日和三次样条等插值方法对高程时间序列进行插值,并对不同方法的插值结果进行了分析比较,验证了正交多项式拟合的可行性及有效性。结果表明:在高程时间序列插值中,三次样条插值结果较差;连续缺失3个点及以下时,正交多项式拟合、拉格朗日插值结果均较好,插值效果相当;随着缺失点数量的增加,正交多项式拟合结果要优于另2种方法。 相似文献
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Abstract Visualization techniques have been developed to recreate natural landscapes, but little has been done to investigate their potential for illustrating land cover change using spatio‐temporal data. In this work, remote sensing, geographic information systems (GIS) and visualization techniques were applied to generate realistic computer visualizations depicting the dynamic nature of forested environments. High resolution digital imagery and aerial photography were classified using object‐oriented methods. The resulting classifications, along with preexisting land cover datasets, were used to drive the correct placement of vegetation in the visualized landscape, providing an accurate representation of reality at various points in time. 3D Nature's Visual Nature Studio was used to construct a variety of realistic images and animations depicting forest cover change in two distinct ecological settings. Visualizations from Yellowstone National Park focused on the dramatic impact of the 1988 fire upon the lodgepole pine forest. For a study area in Kansas, visualization techniques were used to explore the continuous human‐land interactions impacting the eastern deciduous forest and tallgrass prairie ecotone between 1941 and 2002. The resulting products demonstrate the flexibility and effectiveness of visualizations for representing spatio‐temporal patterns such as changing forest cover. These geographic visualizations allow users to communicate findings and explore new hypotheses in a clear, concise and effective manner. 相似文献
806.
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
807.
Demetris Koutsoyiannis 《水文科学杂志》2013,58(2):225-244
ABSTRACTThe old principle of parsimonious modelling of natural processes has regained its importance in the last few years. The inevitability of uncertainty and risk, and the value of stochastic modelling in dealing with them, are also again appreciated, after a period of growing hopes for radical reduction of uncertainty. Yet, in stochastic modelling of natural processes several families of models are used that are often non-parsimonious, unnatural or artificial, theoretically unjustified and, eventually, unnecessary. Here we develop a general methodology for more theoretically justified stochastic processes, which evolve in continuous time and stem from maximum entropy production considerations. The discrete-time properties thereof are theoretically derived from the continuous-time ones and a general simulation methodology in discrete time is built, which explicitly handles the effects of discretization and truncation. Some additional modelling issues are discussed with a focus on model identification and fitting, which are often made using inappropriate methods.
EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR S. Grimaldi 相似文献
808.
铬天青S光度法是硅中铝含量的测定方法之一,该方法的标准曲线大多采用不过零点的线性拟合,导致低铝含量测定误差大。为提高方法准确度并降低方法检出限,研究了铝标准曲线低浓度部分的拟合问题,探讨了不同拟合模型对检测结果准确度的影响。实验结果表明,不同浓度铝标准液的吸光度在0~0.3 μg/mL范围内并不满足一次函数线性关系,采用三次函数关系y=-17.45230x3+10.42883x2+1.04047x (y为扣空白的吸光度,x为铝的质量浓度)拟合能获得良好结果,其相关系数R2为0.99975。利用已知铝含量的硅试液检验该公式,其相对标准偏差(RSD)为2.55%。样品中铝的测定值与电感耦合等离子体发射光谱法测定值吻合。该法可以显著提高低浓度的铝测定的准确性,可用于测定高纯硅中含量在0.55 μg/g以上的铝杂质。 相似文献
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810.
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