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361.
Kersten P.R. Jansen R.W. Luc K. Ainsworth T.L. 《Geoscience and Remote Sensing Letters, IEEE》2007,4(4):527-531
Synthetic aperture radar (SAR) image formation processing assumes that the scene is stationary, and to focus an object, one coherently sums a large number of independent returns. Any target motion introduces phases that distort and/or translate the target's image. Target motion produces a smear primarily in the azimuth direction of the SAR image. Time-frequency (TF) modeling is used to analyze and correct the residual phase distortions. An interactive focusing algorithm based on TF modeling demonstrates how to correct the phase and to rapidly focus the mover. This is demonstrated on two watercraft observed in a SAR image. Then, two time-frequency representations (TFRs) are applied to estimate the motion parameters of the movers or refocus them or both. The first is the short-time Fourier transform, from which a velocity profile is constructed based on the length of the smear. The second TFR is the time-frequency distribution series, which is a robust derivative of the Wigner-Ville distribution that works well in this SAR environment. The smear is a modulated chirp, from which a velocity profile is plotted and the phase corrections are integrated to focus the movers. The relationship between these two methods is discussed. Both methods show good agreement on the example. 相似文献
362.
363.
Temperature variations at very long baseline interferometry (VLBI) sites cause thermal deformations of the VLBI antennas and
corresponding displacements of the VLBI reference points. The thermal deformation effects typically contain seasonal and daily
signatures. The amplitudes of the annual vertical motion of the antenna reference point can reach several millimeters, depending
on the design of the antenna structure, on the material, and on the environmental effects such as global station position,
station height and climatology effects. Simple methods to correct this effect use the difference of the environmental temperature
with respect to a defined reference temperature, the antenna dimensions, the elevation of the antenna, the material of antenna
structure. Applying these simple models for thermal deformation in the VLBI data analysis improves the baseline length repeatability
by 3.5%. A comparison of these simple models with local thermal deformation measurements at the antennas in Onsala and Wettzell
show that the local measurements and the modeled corrections agree well when the temperature of the antenna structure is used,
but agree less good when the surrounding air temperatures are used. To overcome this problem we present a method to model
temperature penetration into the antenna structures, that allows to model thermal deformation effects that agree with the
observed vertical deformation of the Onsala and Wettzell radio telescopes with a root mean square deviation of 0.07 and 0.13 mm,
respectively. Possible implementations in the VLBI analysis are presented, and the definition of an adequate reference temperature
is discussed. 相似文献
364.
K. R. Koch 《Journal of Geodesy》2007,81(9):581-591
Among the Markov chain Monte Carlo methods, the Gibbs sampler has the advantage that it samples from the conditional distributions
for each unknown parameter, thus decomposing the sample space. In the case the conditional distributions are not tractable,
the Gibbs sampler by means of sampling-importance-resampling is presented here. It uses the prior density function of a Bayesian
analysis as the importance sampling distribution. This leads to a fast convergence of the Gibbs sampler as demonstrated by
the smoothing with preserving the edges of 3D images of emission tomography. 相似文献
365.
Sheshakumar K. Goroshi R. P. Singh S. Panigrahy J. S. Parihar 《Journal of the Indian Society of Remote Sensing》2011,39(3):315-321
This paper highlights the spatial and temporal variability of atmospheric columnar methane (CH4) concentration over India and its correlation with the terrestrial vegetation dynamics. SCanning IMaging Absorption spectrometer
for Atmospheric CHartographY (SCIAMACHY) on board ENVIronmental SATellite (ENVISAT) data product (0.5° × 0.5°) was used to
analyze the atmospheric CH4 concentration. Satellite Pour l'Observation de la Terre (SPOT)-VEGETATION sensor’s Normalized Difference Vegetation Index
(NDVI) product, aggregated at 0.5° × 0.5° grid level for the same period (2004 and 2005), was used to correlate the with CH4 concentration. Analysis showed mean monthly CH4 concentration during the Kharif season varied from 1,704 parts per billion volume (ppbv) to 1,780 ppbv with the lowest value in May and the highest value
in September. Correspondingly, mean NDVI varied from 0.28 (May) to 0.53 (September). Analysis of correlation between CH4 concentration and NDVI values over India showed positive correlation (r = 0.76; n = 6) in Kharif season. Further analysis using land cover information showed characteristic low correlation in natural vegetation region
and high correlation in agricultural area. Grids, particularly falling in the Indo-Gangetic Plains showed positive correlation.
This could be attributed to the rice crop which is grown as a predominant crop during this period. The CH4 concentration pattern matched well with growth pattern of rice with the highest concentration coinciding with the peak growth
period of crop in the September. Characteristically low correlation was observed (r = 0.1; n = 6) in deserts of Rajasthan and forested Himalayan ecosystem. Thus, the paper emphasizes the synergistic use of different
satellite based data in understanding the variability of atmospheric CH4 concentration in relation to vegetation. 相似文献
366.
R. Heinkelmann J. B?hm S. Bolotin G. Engelhardt R. Haas R. Lanotte D. S. MacMillan M. Negusini E. Skurikhina O. Titov H. Schuh 《Journal of Geodesy》2011,85(7):377-393
Time-series of zenith wet and total troposphere delays as well as north and east gradients are compared, and zenith total delays (ZTD) are combined on the level of parameter estimates. Input data sets are provided by ten Analysis Centers (ACs) of the International VLBI Service for Geodesy and Astrometry (IVS) for the CONT08 campaign (12?C26 August 2008). The inconsistent usage of meteorological data and models, such as mapping functions, causes systematics among the ACs, and differing parameterizations and constraints add noise to the troposphere parameter estimates. The empirical standard deviation of ZTD among the ACs with regard to an unweighted mean is 4.6?mm. The ratio of the analysis noise to the observation noise assessed by the operator/software impact (OSI) model is about 2.5. These and other effects have to be accounted for to improve the intra-technique combination of VLBI-derived troposphere parameters. While the largest systematics caused by inconsistent usage of meteorological data can be avoided and the application of different mapping functions can be considered by applying empirical corrections, the noise has to be modeled in the stochastic model of intra-technique combination. The application of different stochastic models shows no significant effects on the combined parameters but results in different mean formal errors: the mean formal errors of the combined ZTD are 2.3?mm (unweighted), 4.4?mm (diagonal), 8.6?mm [variance component (VC) estimation], and 8.6?mm (operator/software impact, OSI). On the one hand, the OSI model, i.e. the inclusion of off-diagonal elements in the cofactor-matrix, considers the reapplication of observations yielding a factor of about two for mean formal errors as compared to the diagonal approach. On the other hand, the combination based on VC estimation shows large differences among the VCs and exhibits a comparable scaling of formal errors. Thus, for the combination of troposphere parameters a combination of the two extensions of the stochastic model is recommended. 相似文献
367.
GPS tomography in the polar cap: comparison with ionosondes and in situ spacecraft data 总被引:1,自引:1,他引:1
Dimitry Pokhotelov P. T. Jayachandran Cathryn N. Mitchell John W. MacDougall Michael H. Denton 《GPS Solutions》2011,15(1):79-87
Tomographic 4D reconstructions of ionospheric anomalies appearing in the high-latitude polar cap region are compared with
plasma density measurements by digital ionosonde located near the north magnetic pole at Eureka station and with in situ plasma
measurements on-board DMSP spacecraft. The moderate magnetic storm of 14–17 October 2002 is taken as an example of a geomagnetic
disturbance which generates large-scale ionospheric plasma anomalies at mid-latitudes and in the polar cap region. Comparison
of the GPS tomographic reconstructions over Eureka station with the ionosonde measurements of the F layer peak densities indicates
that the GPS tomography correctly predicts the time of arrival and passage of the ionospheric tongue of ionization over the
magnetic pole area, although the tomographic technique appears to under-estimate the value of F peak plasma density. Comparison
with the in situ plasma measurements by the DMSP SSIES instruments shows that the GPS tomography correctly reproduces the
large-scale spatial structure of ionospheric anomalies over a wide range of latitudes from mid-latitudes to the high-latitude
polar cap region, though the tomographic reconstructions tend to over-estimate the density of the topside ionosphere at 840 km
DMSP orbit. This study is essential for understanding the quality and limitations of the tomographic reconstruction techniques,
particularly in high-latitude regions where GPS TEC measurements and other ionospheric data sources are limited. 相似文献
368.
Sandip R. Oza R. K. K. Singh N. K. Vyas B. S. Gohil Abhijit Sarkar 《Journal of the Indian Society of Remote Sensing》2011,39(2):147-152
The identification of sea-ice has frequently been cited as one of the most important tasks for deriving the sea-ice parameters
and to avoid erroneous retrieval of wind vector over sea-ice infested oceans using space-borne scatterometer data. Discrimination
between sea-ice and ocean is ambiguous under the high wind and/or thin/scattered ice conditions. The pre-launch technique
developed for Oceansat-2, utilizes the dual-polarized QuikSCAT scatterometer data by using the spatio-temporal coherence properties
of sea ice in addition to backscatter coefficient and the Active Polarization Ratio. Results were compared with the operational
sea-ice products from National Snow and Ice Data Center. The threshold API value of −0.025 was found optimum for sea-ice and
ocean discrimination. The overall sea-ice identification accuracy achieved was of the order of 95 per cent, ranging from 92.5%
(during December in Southern Hemisphere) to 98% (during March in Northern Hemisphere). The applicability of the algorithm
for both the Arctic as well as Antarctic makes it suitable for its operational use with the Oceansat-2 scatterometer data. 相似文献
369.
Sushma Panigrahy Shibendu Shankar Ray K. R. Manjunath P. S. Pandey S. K. Sharma Anil Sood Manoj Yadav P. C. Gupta N. Kundu Jai Singh Parihar 《Journal of the Indian Society of Remote Sensing》2011,39(3):355-364
Cropping system study is not only useful to understand the overall sustainability of agricultural system, but also it helps
in generating many important parameters which are useful in climate change impact assessment. Considering its importance,
Space Applications Centre, took up a project for mapping and characterizing major cropping systems of Indo-Gangetic Plains
of India. The study area included the five states of Indo-Gangetic Plains (IGP) of India, i.e. Punjab, Haryana, Uttar Pradesh,
Bihar and West Bengal. There were two aspects of the study. The first aspect included state and district level cropping system
mapping using multi-date remote sensing (IRS-AWiFS and Radarsat ScanSAR) data. The second part was to characterize the cropping
system using moderate spatial resolution multi-date remote sensing data (SPOT VGT NDVI) and ground survey. The remote sensing
data was used to compute three cropping system performance indices (Multiple Cropping Index, Area Diversity Index and Cultivated
Land Utilization Index). Ground survey was conducted using questionnaires filled up by 1,000 farmers selected from 103 villages
based on the cropping systems map. Apart from ground survey, soil and water sampling and quality analysis were carried out
to understand the effect of different cropping systems and their management practices. The results showed that, rice-wheat
was the major cropping system of the IGP, followed by Rice-Fallow-Fallow and Maize-Wheat. Other major cropping systems of
IGP included Sugarcane based, Pearl millet-Wheat, Rice-Fallow-Rice, Cotton-Wheat. The ground survey could identify 77 cropping
systems, out of which 38 are rice-based systems. Out of these 77 cropping systems, there were 5 single crop systems, occupying
6.5% coverage (of all cropping system area), 56 double crop systems with 72.7% coverage, and 16 triple crop systems with 20.8%
coverage. The cropping system performance analysis showed that the crop diversity was found to be highest in Haryana, while
the cropping intensity was highest in Punjab state. 相似文献
370.
Dhaval Vyas N.S.R. Krishnayya K.R. Manjunath S.S. Ray Sushma Panigrahy 《International Journal of Applied Earth Observation and Geoinformation》2011
There is an urgent necessity to monitor changes in the natural surface features of earth. Compared to broadband multispectral data, hyperspectral data provides a better option with high spectral resolution. Classification of vegetation with the use of hyperspectral remote sensing generates a classical problem of high dimensional inputs. Complexity gets compounded as we move from airborne hyperspectral to Spaceborne technology. It is unclear how different classification algorithms will perform on a complex scene of tropical forests collected by spaceborne hyperspectral sensor. The present study was carried out to evaluate the performance of three different classifiers (Artificial Neural Network, Spectral Angle Mapper, Support Vector Machine) over highly diverse tropical forest vegetation utilizing hyperspectral (EO-1) data. Appropriate band selection was done by Stepwise Discriminant Analysis. The Stepwise Discriminant Analysis resulted in identifying 22 best bands to discriminate the eight identified tropical vegetation classes. Maximum numbers of bands came from SWIR region. ANN classifier gave highest OAA values of 81% with the help of 22 selected bands from SDA. The image classified with the help SVM showed OAA of 71%, whereas the SAM showed the lowest OAA of 66%. All the three classifiers were also tested to check their efficiency in classifying spectra coming from 165 processed bands. SVM showed highest OAA of 80%. Classified subset images coming from ANN (from 22 bands) and SVM (from 165 bands) are quite similar in showing the distribution of eight vegetation classes. Both the images appeared close to the actual distribution of vegetation seen in the study area. OAA levels obtained in this study by ANN and SVM classifiers identify the suitability of these classifiers for tropical vegetation discrimination. 相似文献