GEODESIA SPAZIALE PDF

La geodesia satellitare si occupa della misurazione della forma e delle dimensioni della Terra , della determinazione della posizione di oggetti sulla sua superficie e della ricostruzione del campo gravitazionale della Terra per mezzo di sistemi di geodesia basati sull'utilizzo satelliti artificiali. I dati ricavati dalla geodesia satellitare possono essere applicati a diverse discipline, come la navigazione , l' idrografia e la geofisica. La geodesia satellitare si basa in particolare sulla meccanica orbitale. La geodesia satellitare ebbe inizio subito dopo il lancio dello Sputnik nel Le osservazioni effettuate dal satellite Vanguard 1 nel permisero una accurata misurazione dello schiacciamento dei poli [2]. Nel furono lanciati il satellite Transit-1B , per la determinazione della posizione mediante effetto Doppler , che permise la misura delle componenti armoniche del campo gravitazionale terrestre.

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The Multiband product ERS. This product is distributed in HTML format that includes the raster data for each band, a quick look of the images, the registration parameters and the most useful annotations.

SLC products. The final data consists of a set of annotated complex images. The ERS. It containins the complex and filtered interferogram, the coherence map and the interferogram flattened on the earth ellipsoid. Also the interferometric products are released in HTML format.

These products have a large user community, either in the field of image processing or in applications and environmental monitoring. Moreover the complexity of the processing and the analysis of the data make the SAR remote sensing a tool for expert users only.

In the last year, new ERS non standard products have been defined in order to improve an extensive use of ERS data and to provide a support to non expert users interested in the exploration and developments of SAR remote sensing applications. These new products are the multiband and the interferometric products. For many of the ERS applications, such as land use classification or change detection, a single image often doesn't provide exauustive information.

Therefore is necessary to register more than one image acquired in different times on the same geographic area. In order to perform the registration a reference image master is selected and the other ones slaves must be registered so that for each pixel the values of all the bands can be available.

This is performed by mean of a warp function that describes the correspondence between the master and the slaves pixels. This function is obtained on the basis of some Ground Control Points GCPs selected on the master and for which the corresponding coordinates on the slaves are well known. This function is often a polynomial function of various degree, depending on the type of distortion present on the images Richards , AA.

VV , Pratt W. Usually the GCPs are manually selected by operators, but this operation is often very imprecise and time consuming. The multiband product, also called multitemporal product, is a new service of the Italian PAF for the users interested in the comparison of many images acquired on the same geographical area.

This product consists of a set of two or more ERS images e. The registration process is performed by an Automatic Registration System that only requires as input the image to be considered as master, the number of GCPs to collect, the warp degree and the interpolation type.

This tool automatically selects the Ground Control Points to be used in the warp function definition, evaluating the images cross-correlation due to similarity in their morphology. The GCP prediction is performed on the basis of the correspondence between the master and the slaves.

It is obtained starting from the geographical coordinates of the four corners and on the basis of a projection model of the image on the earth ellipsoid Graf et al. Then, an equally spaced grid of GCP is generated on the master image and, for each point, the geographic coordinates and the corresponding slave images coordinates are computed.

A further GCP position refinement is performed estimating the peak of the bidimensional cross correlation between the master and the slave, extracted in a cell around the point. The algorithm is optimized by mean of an interpolation step, based on FFT and zero pad Oppenheim et al.

Both the cell size and the interpolation factor are selectable. The goodness of the GCPs can be tested correlating again them and verifying that the shift is zero. The GCPs that do not met this condition e. The remaing ones are used to derive a warp function.

The points having a residual respect to the warp function greater than a threshold value are excluded too. Finally the slave image is resampled on the basis of the warp function. The interpolation algorithms available are: nearest neighbours, bilinear interpolation and cubic convolution.

The multiband product Figure1 is distributed in a new HTML format that includes all the most important CEOS annotation, both the quick look of the multiband product and of each single band, the registration parameters and the raster data for each band. Each annotation is has a hyperlinked description of the parameters. Multiband products on Naples. This product is obtained by registering three ERS PRI acquired in different times.

The first product Single look complex Registered Image contains a couple of registered complex images with some new annotations like the baseline value for every image line. The second product Wavenumber shift Filtered Image , derived by the SRI, contains the following layers: complex and filtered interferogram, coherence map and interferogram flattened on the earth ellipsoid.

The input data for the Image Registration step is a couple of complex products e. The key point in the SLC registration is the derivation of the warp function that is obtained by using orbital and geographical information, image morphology and coherence maximization. As for the Multiband Product, a very coarse registration between the master and the slave is automatically performed on a regular GCP grid, starting from the image geographic location and orbit.

Then the system extracts a set of master-slave cells, calculates the cross correlation and interpolates to reach a 0. The warping function is then derived with the same steps implemented for the multiband product. A filter of the GCPs is made considering the coherence mean value and standard deviation, computed in a cell around the points.

The next operation consists in the slave interpolation. Due to the dimensions of the images e. The interpolator function has to be carefully selected because of the different characteristics in range and azimuth of an SLC. Infact, in the azimuth direction the warp function shows small variation but the spectra is not zero centered and so no "simple" low pass interpolator can be used.

In the range direction the spectra are zero centered but the variations of the warp function is high. For these reasons the interpolation is performed first along azimuth and next along range direction.

Along the azimuth, for each column of the input block the mean shift is computed and applied using a FFT method. Along the range, a cubic convolution interpolation is performed. As last step, a coarse baseline computation is done, based on the propagated orbits and on the warp function. Using the warp it is possible to synchronize the time of the two orbits and to evaluate the baseline as vector function of the master line, expressed in a three dimensional Conventional Terrestrial System CTS.

In the ERS. SRI product the coefficients of the 1st degree polynomial fitting each component of the baseline vector are annotated. The presence of a terrain slope seen in slight different way by the master and the slave image produces a shift in the range spectra of the interferometric couple Prati et al.

This effect, called Wavenumber shift has to be taken into account to avoid the interferogram decorrelation associated to the geometry. In order to correct this decorrelation effect, a filtering of both the images must be done, with a couple of "wavenumber" filters. These filters are generated starting from the knowledge of the local interferogram fringe frequency related to the local terrain slope. In the first step, a subdivision of the SRI data is done, with cells equally spatiated..

The sampling is done using sharp features because the frequency shift has a strict dependency from the slope change in the imaged terrain zone. For each cell, the relative frequency shift is estimated deriving a local range fringe frequency map. The two "wavenumber" filters, distinct for the master and slave image, are then generated as range and azimuth dependent functions and a standard method like Overlap and Save is used to filter the entire SRI data.

It is worth to say that, before the filtering, the images are interpolated in range by two, using a FFT and zero pad, to avoid the aliasing effect during the interferogram formation step. The resulting output product is called WFI - Wavenumber effect Filtered Images and consists of a wavenumber effect filtered master-slave couple.

This leads to a complex image which has as amplitude the product of the master and slave amplitude, and as phase the phase difference between the two images. The coherence map can be evaluated as usual provided that the topographic factor are corrected, as given from the local 2D fringe frequency, and using "non biased" coherence estimation algorithms Touzi et al. In such way the coherence map is derived and given as a further layer of the WFI data. In Figure 2 the histogram of coherence image on Etna is reported.

Given a certain geometry of a couple of side looking SAR sensors, only one half of the fringe frequencies has a physical meaning. The other half comes from the noise and the layover effect. The geometry determines which is the right half spectrum and so the sign of the layover filter.

Once this filter is evaluated, the complex interferogram can be filtered giving in output another layer of the WFI product, the filtered complex interferogram. Using the baseline, the orbital data and the earth ellipsoid shape, the phase contribution which depends by the presence of a "mean terrain" can be computed. The subtraction of this effect from the interferogram is called flat terrain correction. After this step, the interferogram fringes depends only on the elevation above the ellipsoid.

An example of this product is reported in Figure 3. The last step is the phase unwrapping of the interferogram, which recovers the true phase from its residual modulus 2 PI.

At present many algorithms exist, each with advantages and drawbacks Just et al. For this reason we are actually analyzing the various approaches, to find the best solution to the unwrapping problem for an operational context. The products are under validation and they will be soon available to the users as experimental products.

The SAR user community will take advantages from the availability of new general purpose products of certified and reliable quality. Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry.

Earth Home. Data Products. EO Data Access. How to Apply. How to Access. Advanced Search. Terlecchia, , Matera, Italy Ph.

Nuova Telespazio S. Copyright - European Space Agency. All rights reserved.

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