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首先介绍北斗卫星导航系统、全球定位系统及其组合系统伪距单点定位的数学模型和定位处理方法,分别进行了单系统及组合系统伪距单点定位的数据处理实验。实验结果表明,目前的北斗系统伪距单点定位的精度稍逊于全球定位系统,北斗系统及全球定位系统构成组合系统伪距单点定位的精度高于北斗系统的精度,低于全球定位系统。北斗系统伪距单点定位在X、Y、Z方向的精度分别1.60m、4.15m、6.45m,全球定位系统伪距单点定位在X、Y、Z方向的精度分别为1.28m、2.50m和3.6 5m,北斗系统/全球定位系统组合系统伪距单点定位在X、Y、Z方向的精度分别为1.45m、3.15m和4.90m。 相似文献
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对北斗区域卫星导航系统（BDS）正式运行后在南极中山站地区的基本导航定位性能进行了评估,包括卫星可用性、位置精度因子（PDOP）、伪距观测值质量、电离层模型精度及单频伪距导航定位性能等方面。对南极中山站地区实测数据分析的结果表明,首先,北斗卫星导航系统的可用性与伪距观测值质量在总体上与GPS处于同一水平,并已初步具备了全天导航定位的能力,但存在卫星分布不够均匀、GEO卫星高度角较低、电离层模型精度较差等问题。其次,北斗单频伪距单点定位北、东方向的精度分别优于22 m和9 m,高程方向优于25 m;超短基线的单频伪距差分定位在北、东、高程三个方向的精度分别为3.6 m、2.3 m和3.3 m;总体而言与GPS相比有一定差距。最后,北斗/GPS组合定位相对于单一的GPS定位不仅增加了系统的可靠性,还对定位的精度有明显改善,对于单频伪距单点定位、伪距差分定位的三维点位精度可分别提高10%、22%。 相似文献
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中国独立发展的北斗系统已经具备亚太地区的定位导航能力,为研究以北斗系统为主的车载导航技术的应用精度,采用伪距单点定位的方法分别对车载GPS,BD2,GPS\BD2 3种导航模式下的二维导航精度进行对比分析,结果显示定位精度分别为:3.66m,4.76 m,3.01 m,可以看出基于单点定位的北斗二维平面导航精度已达到5 m内,完全满足大众日常的出行要求。组合系统与GPS导航系统对比,组合系统具有更高的精度,是较好的导航模式。并基于visual studio平台编写定位软件,实现对车辆位置和速度信息的提取,监控车辆是否超速。 相似文献
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北斗卫星导航系统采用3种轨道类型卫星组成的混合星座,抗遮挡能力强,同时创新融合导航与通信能力,具备全球定位、导航、授时服务能力。利用小型无人机搭载低成本北斗/GPS芯片,设计并实现软硬件系统。通过实时回传的观测数据,采用GPS、北斗以及北斗/GPS组合三种定位模式,进行实时单点定位,并对各模式下的可见卫星数、空间几何精度衰减因子和定位精度进行分析与评估。实验表明：无人机载北斗/GPS组合定位,平均PDOP值为1.4,可见卫星数达32,实现了较优的观测几何构型,历元利用率高。北斗/GPS组合模式与RTK接收机获取的坐标比较,在E、N、U方向上定位偏差分别达到2.5 m、4.1 m和2.4 m。 相似文献
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为加快北斗导航系统在中国及亚太地区的推广应用,以JXCORS基准站点数据为基础,对接收的北斗导航卫星和GPS导航卫星数据进行处理,分析基准站点可见卫星的变化及DOP值变化,比较北斗与GPS伪距单点定位的精度与性能。结果表明,北斗伪距单点定位的精度与GPS伪距单点定位的精度和性能相当。 相似文献
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对GPS系统、北斗二号系统以及GPS/北斗组合系统伪距单点定位的关键技术进行研究,分析了3种导航系统的DOP值。单一系统随卫星高度角的增加,DOP值增大,定位精度下降。GPS伪距单点定位的精度达到2 m,北斗伪距单点定位的精度在5 m以内,GPS/北斗联合定位的精度和GPS相差不大。 相似文献
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Heavy metals contaminated soils and water will become a major environmental issue in the mining areas. This paper intends to use field hyper-spectra to estimate the heavy metals in the soil and water in Wan-sheng mining area in Chongqing. With analyzing the spectra of soil and water, the spectral features deriving from the spectral of the soils and water can be found to build the models between these features and the contents of Al, Cu and Cr in the soil and water by using the Stepwise Multiple Linear Regression (SMLR). The spectral features of Al are: 480 nm, 500 nm, 565 nm, 610 nm, 680 nm, 750 nm, 1000 nm, 1430 nm, 1755 nm, 1887 nm, 1920 nm, 1950 nm, 2210 nm, 2260 nm; The spectral features of Cu are: 480 nm, 500 nm, 610 nm, 750 nm, 860 nm, 1300 nm, 1430 nm, 1920 nm, 2150 nm, 2260 nm; And the spectral features of Cr are: 480 nm, 500 nm, 610 nm, 715 nm, 750 nm, 860 nm, 1300 nm, 1430 nm, 1755 nm, 1920 nm, 1950 nm. With these features, the best models to estimate the heavy metals in the study area were built according to the maximal R2. The R2 of the models of estimating Al, Cu and Cr in the soil and water are 0.813, 0.638, 0.604 and 0.742, 0.584, 0.513 respectively. And the gradient maps of these three types of heavy metals’ concentrations can be created by using the Inverse distance weighted (IDW).The gradient maps indicate that the heavy metals in the soil have similar patterns, but in the North-west of the streams in the study area, the contents are of great differences. These results show that it is feasible to predict contaminated heavy metals in the soils and streams due to mining activities by using the rapid and cost-effective field spectroscopy. 相似文献
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Soil erodibility, which is difficult to estimate and upscaling, was determined in this study using multiple spectral models of soil properties (soil organic matter (SOM), water-stable aggregates (WSA) > 0.25 mm, the geometric mean radius (Dg)). Herein, the soil erodibility indicators were calculated, and soil properties were quantitatively analyzed based on laboratory simulation experiments involving two selected contrasting soils. In addition, continuous wavelet transformation was applied to the reflectance spectra (350–2500 nm) of 65 soil samples from the study area. To build the relationship, the soil properties that control erodibility were identified prior to the spectral analysis. In this study, the SOM, Dg and WSA >0.25 mm were selected to represent the most significant soil properties controlling erodibility and describe the erodibility indicator based on a logarithmic regression model as a function of SOM or WSA > 0.25 mm. Five, six and three wavelet features were observed to calibrate the estimated soil properties model, and the best performance was obtained with a combination feature regression model for SOM (R2 = 0.86, p < 0.01), Dg (R2 = 0.79, p < 0.01) and WSA >0.25 mm (R2 = 0.61, p < 0.01), respectively. One part of the wavelet features captured amplitude variations in the broad shape of the reflectance spectra, and another part captured variations in the shape and depth of the soil dry substances. The wavelet features for the validated dataset used to predict the SOM, WSA >0.25 mm and Dg were not significantly different compared with the calibrated dataset. The synthesized spectral models of soil properties, and the formation of a new equation for soil erodibility transformed from the spectral models of soil properties are presented in this study. These results show that a spectral analytical approach can be applied to complex datasets and provide new insights into emerging dynamic variation with erodibility estimation. 相似文献
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This paper presents a technique developed for the retrieval of the orientation of crop rows, over anthropic lands dedicated to agriculture in order to further improve estimate of crop production and soil erosion management. Five crop types are considered: wheat, barley, rapeseed, sunflower, corn and hemp. The study is part of the multi-sensor crop-monitoring experiment, conducted in 2010 throughout the agricultural season (MCM’10) over an area located in southwestern France, near Toulouse. The proposed methodology is based on the use of satellite images acquired by Formosat-2, at high spatial resolution in panchromatic and multispectral modes (with spatial resolution of 2 and 8 m, respectively). Orientations are derived and evaluated for each image and for each plot, using directional spatial filters (45° and 135°) and mathematical morphology algorithms. “Single-date” and “multi-temporal” approaches are considered. The single-date analyses confirm the good performances of the proposed method, but emphasize the limitation of the approach for estimating the crop row orientation over the whole landscape with only one date. The multi-date analyses allow (1) determining the most suitable agricultural period for the detection of the row orientations, and (2) extending the estimation to the entire footprint of the study area. For the winter crops (wheat, barley and rapeseed), best results are obtained with images acquired just after harvest, when surfaces are covered by stubbles or during the period of deep tillage (0.27 > R2 > 0.99 and 7.15° > RMSE > 43.02°). For the summer crops (sunflower, corn and hemp), results are strongly crop and date dependents (0 > R2 > 0.96, 10.22° > RMSE > 80°), with a well-marked impact of flowering, irrigation equipment and/or maximum crop development. Last, the extent of the method to the whole studied zone allows mapping 90% of the crop row orientations (more than 45,000 ha) with an error inferior to 40°, associated to a confidence index ranging from 1 to 5 for each agricultural plot. 相似文献
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Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic CH bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf (r2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf (r2 = 0.79, RMSE = 2.1%, n = 56), and canopy (r2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the spectral influences of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin). 相似文献
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Locally computed statistics of image texture and a case-based reasoning (CBR) system were evaluated for mapping of forest attributes. Cluster analysis was preferred to regression models, as a pre-selection method of features. The best stand-based accuracy using satellite sensor images was 74.64 m−3 ha−1 (36%) RMSE for stand volume, 1.98 m−3 ha−1 a−1 (49%) for annual increase in stand volume, where κ = 0.23 for stand growth classes and κ = 0.41 for dominant tree species in stands. The top pixel-based accuracy using orthophotos was 76.54 m−3 ha−1 (41%) RMSE for stand volume, 1.87 m−3 ha−1 a−1 (44%) for annual increase in stand volume, where κ = 0.24 for stand growth classes and κ = 0.38 for dominant tree species in stands. Mean saturation in 30 m radius was the most useful feature when orthophotos were used, and standard deviation of Landsat ETM 6.2 values in 80 m radius was the best when satellite sensor images were used. The most valuable feature components (radii, channels and local statistics) for orthophotos were: 30 m kernel radius, lightness and the mean of pixel values; for satellite sensor images: 80 m kernel radius, near-infrared channel (ETM 4) and the mean of pixel values. Locally computed statistics. 相似文献
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C. C. Tscherning 《Journal of Geodesy》1999,73(6):332-336
A reproducing-kernel Hilbert space (RKHS) of functions harmonic in the set outside a sphere with radius R
0, having a reproducing kernel K
0(P,Q) is considered (P, Q, and later P
n
being points in the set of harmonicity). The degree variances of this kernel will be denoted σ0
n
.
The set of Riesz representers associated with the evaluation functionals (or gravity functionals) related to distinct points
P
n
,n = 1,…,N, on a two-dimensional surface surrounding the bounding sphere, will be linearly independent. These functions are used to
define a new N-dimensional RKHS with kernel (a
n
>0)
If the points all are located on a concentric sphere with radius R
1>R
0, and form an ε-net covering the sphere, and a
n
are suitable area elements (depending on N), then this kernel will converge towards an isotropic kernel with degree variances
Consequently, if K
N
(P,Q) is required to represent an isotropic covariance function of the Earth's gravity potential, COV(P,Q), σ0
n
can be selected so that σ
n
becomes equal to the empirical degree variances.
If the points are chosen at varying radial distances R
n
>R
0, then an anisotropic kernel, or equivalent covariance function representation, can be constructed. If the points are located
in a bounded region, the kernel may be used to modify the original kernel
Values of anisotropic covariance functions constructed based on these ideas are calculated, and some initial ideas are presented
on how to select the points P
n
.
Received: 24 September 1998 / Accepted: 10 March 1999 相似文献
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Barnaby Clark Juha Suomalainen Petri Pellikka 《International Journal of Applied Earth Observation and Geoinformation》2011
SPOT satellites have been imaging Earth's surface since SPOT 1 was launched in 1986. It is argued that absolute atmospheric correction is a prerequisite for quantitative remote sensing. Areas where land cover changes are occurring rapidly are also often areas most lacking in situ data which would allow full use of radiative transfer models for reflectance factor retrieval (RFR). Consequently, this study details the proposed historical empirical line method (HELM) for RFR from multi-temporal SPOT imagery. HELM is designed for use in landscape level studies in circumstances where no detailed overpass concurrent atmospheric or meteorological data are available, but where there is field access to the research site(s) and a goniometer or spectrometer is available. SPOT data are complicated by the ±27° off-nadir cross track viewing. Calibration to nadir only surface reflectance factor (ρs) is denoted as HELM-1, whilst calibration to ρs modelling imagery illumination and view geometries is termed HELM-2. Comparisons of field measured ρs with those derived from HELM corrected SPOT imagery, covering Helsinki, Finland, and Taita Hills, Kenya, indicated HELM-1 RFR absolute accuracy was ±0.02ρs in the visible and near infrared (VIS/NIR) bands and ±0.03ρs in the shortwave infrared (SWIR), whilst HELM-2 performance was ±0.03ρs in the VIS/NIR and ±0.04ρs in the SWIR. This represented band specific relative errors of 10–15%. HELM-1 and HELM-2 RFR were significantly better than at-satellite reflectance (ρSAT), indicating HELM was effective in reducing atmospheric effects. However, neither HELM approach reduced variability in mean ρs between multi-temporal images, compared to ρSAT. HELM-1 calibration error is dependent on surface characteristics and scene illumination and view geometry. Based on multiangular ρs measurements of vegetation-free ground targets, calibration error was negligible in the forward scattering direction, even at maximum off-nadir view. However, error exceeds 0.02ρs where off-nadir viewing was ≥20° in the backscattering direction within ±55° azimuth of the principal plane. Overall, HELM-1 results were commensurate with an identified VIS/NIR 0.02ρs accuracy benchmark. HELM thus increases applicability of SPOT data to quantitative remote sensing studies. 相似文献
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Computer algebra solution of the GPS N-points problem 总被引：1，自引：0，他引：1
A computer algebra solution is applied here to develop and evaluate algorithms for solving the basic GPS navigation problem: finding a point position using four or more pseudoranges at one
epoch (the GPS N-points problem). Using Mathematica 5.2 software, the GPS N-points problem is solved numerically, symbolically, semi-symbolically, and with Gauss–Jacobi, on a work station. For the case of N > 4, two minimization approaches based on residuals and distance norms are evaluated for the direct numerical solution and their computational duration is compared. For N = 4, it is demonstrated that the symbolic computation is twice as fast as the iterative direct numerical method. For N = 6, the direct numerical solution is twice as fast as the semi-symbolic, with the residual minimization requiring less computation
time compared to the minimization of the distance norm. Gauss–Jacobi requires eight times more computation time than the direct
numerical solution. It does, however, have the advantage of diagnosing poor satellite geometry and outliers. Besides offering
a complete evaluation of these algorithms, we have developed Mathematica 5.2 code (a notebook file) for these algorithms (i.e., Sturmfel’s resultant, Dixon’s resultants, Groebner basis, reduced
Groebner basis and Gauss–Jacobi). These are accessible to any geodesist, geophysicist, or geoinformation scientist via the
GPS Toolbox () website or the Wolfram Information Center ().
相似文献
| Erik W. GrafarendEmail: |
19.
Xia Yao Yan ZhuYongChao Tian Wei FengWeiXing Cao 《International Journal of Applied Earth Observation and Geoinformation》2010
Hyperspectral sensing can provide an effective means for fast and non-destructive estimation of leaf nitrogen (N) status in crop plants. The objectives of this study were to design a new method to extract hyperspectral spectrum information, to explore sensitive spectral bands, suitable bandwidth and best vegetation indices based on precise analysis of ground-based hyperspectral information, and to develop regression models for estimating leaf N accumulation per unit soil area (LNA, g N m−2) in winter wheat (Triticum aestivum L.). Three field experiments were conducted with different N rates and cultivar types in three consecutive growing seasons, and time-course measurements were taken on canopy hyperspectral reflectance and LNA under the various treatments. Then, normalized difference spectral indices (NDSI) and ratio spectral indices (RSI) based on the original spectrum and the first derivative spectrum were constructed within the range of 350–2500 nm, and their relationships with LNA were quantified. The results showed that both LNA and canopy hyperspectral reflectance in wheat changed with varied N rates, with consistent patterns across different cultivars and seasons. The sensitive spectral bands for LNA existed mainly within visible and near infrared regions. The best spectral indices for estimating LNA in wheat were found to be NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516), and the regression models based on the above four spectral indices were formulated as Y = 26.34x1.887, Y = 5.095x − 6.040, Y = 0.609 e3.008x and Y = 0.388x1.260, respectively, with R2 greater than 0.81. Furthermore, expanding the bandwidth of NDSI (R860, R720) and RSI (R990, R720) from 1 nm to 100 nm at 1 nm interval produced the LNA monitoring models with similar performance within about 33 nm and 23 nm bandwidth, respectively, over which the statistical parameters of the models became less stable. From testing of the derived equations, the model for LNA estimation on NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516) gave R2 over 0.79 with more satisfactory performance than previously reported models and physical models in wheat. It can be concluded that the present hyperspectral parameters of NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516) can be reliably used for estimating LNA in winter wheat. 相似文献
20.
Gianfranco Piras Kieran P. Donaghy Giuseppe Arbia 《Journal of Geographical Systems》2007,9(4):311-344
This paper presents an innovative approach to the study of regional economic dynamics within a nonlinear continuous-time econometric
framework—a generalized specification of the Lotka–Volterra system of equations. This specification, which accounts for interdependent
behavior of three industrial sectors and spillover effects of activities in neighboring regions, is employed in an analysis
of five Italian regions between 1980 and 2003. For these regions, we report estimation results, characterize the varying systems
dynamics, analyze the models’ local and global stability properties, and determine via sensitivity analyses which structural
features appear to exert the greatest influence on these properties.
相似文献
| Kieran P. DonaghyEmail: |