1,427 research outputs found
Metric remote sensing experiments in preparation for Spacelab flights
Aerial and ground photographs of Wallis mountains and of Dolomiti di Cortina d'Ampezzo in Italy were made using spectrozonal emulsions and optical multichannel filters. A metric camera was used in the perspective of the first Spacelab flight aboard the space shuttle. Elementary forms of alpine geomorphology and ice or snow phenomena are detectable on these metric scenes
Digital image correlation (DIC) analysis of the 3 December 2013 Montescaglioso landslide (Basilicata, Southern Italy). Results from a multi-dataset investigation
Image correlation remote sensing monitoring techniques are becoming key tools for
providing effective qualitative and quantitative information suitable for natural hazard assessments,
specifically for landslide investigation and monitoring. In recent years, these techniques have
been successfully integrated and shown to be complementary and competitive with more standard
remote sensing techniques, such as satellite or terrestrial Synthetic Aperture Radar interferometry.
The objective of this article is to apply the proposed in-depth calibration and validation analysis,
referred to as the Digital Image Correlation technique, to measure landslide displacement.
The availability of a multi-dataset for the 3 December 2013 Montescaglioso landslide, characterized
by different types of imagery, such as LANDSAT 8 OLI (Operational Land Imager) and TIRS
(Thermal Infrared Sensor), high-resolution airborne optical orthophotos, Digital Terrain Models
and COSMO-SkyMed Synthetic Aperture Radar, allows for the retrieval of the actual landslide
displacement field at values ranging from a few meters (2–3 m in the north-eastern sector of the
landslide) to 20–21 m (local peaks on the central body of the landslide). Furthermore, comprehensive
sensitivity analyses and statistics-based processing approaches are used to identify the role of the
background noise that affects the whole dataset. This noise has a directly proportional relationship to
the different geometric and temporal resolutions of the processed imagery. Moreover, the accuracy
of the environmental-instrumental background noise evaluation allowed the actual displacement
measurements to be correctly calibrated and validated, thereby leading to a better definition of
the threshold values of the maximum Digital Image Correlation sub-pixel accuracy and reliability
(ranging from 1/10 to 8/10 pixel) for each processed dataset
Exploration of Large Digital Sky Surveys
We review some of the scientific opportunities and technical challenges posed
by the exploration of the large digital sky surveys, in the context of a
Virtual Observatory (VO). The VO paradigm will profoundly change the way
observational astronomy is done. Clustering analysis techniques can be used to
discover samples of rare, unusual, or even previously unknown types of
astronomical objects and phenomena. Exploration of the previously poorly probed
portions of the observable parameter space are especially promising. We
illustrate some of the possible types of studies with examples drawn from
DPOSS; much more complex and interesting applications are forthcoming.
Development of the new tools needed for an efficient exploration of these vast
data sets requires a synergy between astronomy and information sciences, with
great potential returns for both fields.Comment: To appear in: Mining the Sky, eds. A. Banday et al., ESO Astrophysics
Symposia, Berlin: Springer Verlag, in press (2001). Latex file, 18 pages, 6
encapsulated postscript figures, style files include
The Panchromatic High-Resolution Spectroscopic Survey of Local Group Star Clusters - I. General Data Reduction Procedures for the VLT/X-shooter UVB and VIS arm
Our dataset contains spectroscopic observations of 29 globular clusters in
the Magellanic Clouds and the Milky Way performed with VLT/X-shooter. Here we
present detailed data reduction procedures for the VLT/X-shooter UVB and VIS
arm. These are not restricted to our particular dataset, but are generally
applicable to different kinds of X-shooter data without major limitation on the
astronomical object of interest. ESO's X-shooter pipeline (v1.5.0) performs
well and reliably for the wavelength calibration and the associated
rectification procedure, yet we find several weaknesses in the reduction
cascade that are addressed with additional calibration steps, such as bad pixel
interpolation, flat fielding, and slit illumination corrections. Furthermore,
the instrumental PSF is analytically modeled and used to reconstruct flux
losses at slit transit and for optimally extracting point sources. Regular
observations of spectrophotometric standard stars allow us to detect
instrumental variability, which needs to be understood if a reliable absolute
flux calibration is desired. A cascade of additional custom calibration steps
is presented that allows for an absolute flux calibration uncertainty of less
than ten percent under virtually every observational setup provided that the
signal-to-noise ratio is sufficiently high. The optimal extraction increases
the signal-to-noise ratio typically by a factor of 1.5, while simultaneously
correcting for resulting flux losses. The wavelength calibration is found to be
accurate to an uncertainty level of approximately 0.02 Angstrom. We find that
most of the X-shooter systematics can be reliably modeled and corrected for.
This offers the possibility of comparing observations on different nights and
with different telescope pointings and instrumental setups, thereby
facilitating a robust statistical analysis of large datasets.Comment: 22 pages, 18 figures, Accepted for publication in Astronomy &
Astrophysics; V2 contains a minor change in the abstract. We note that we did
not test X-shooter pipeline versions 2.0 or later. V3 contains an updated
referenc
Satellite Image Fusion in Various Domains
In order to find out the fusion algorithm which is best suited for the panchromatic and multispectral images, fusion algorithms, such as PCA and wavelet algorithms have been employed and analyzed. In this paper, performance evaluation criteria are also used for quantitative assessment of the fusion performance. The spectral quality of fused images is evaluated by the ERGAS and Q4. The analysis indicates that the DWT fusion scheme has the best definition as well as spectral fidelity, and has better performance with regard to the high textural information absorption. Therefore, as the study area is concerned, it is most suited for the panchromatic and multispectral image fusion. an image fusion algorithm based on wavelet transform is proposed for Multispectral and panchromatic satellite image by using fusion in spatial and transform domains. In the proposed scheme, the images to be processed are decomposed into sub-images with the same resolution at same levels and different resolution at different levels and then the information fusion is performed using high-frequency sub-images under the Multi-resolution image fusion scheme based on wavelets produces better fused image than that by the MS or WA schemes
COMPARISON OF DIFFERENT FUSION ALGORITHMS IN URBAN AND AGRICULTURAL AREAS USING SAR (PALSAR AND RADARSAT) AND OPTICAL (SPOT) IMAGES
Image fusion techniques of remote sensing data are formal frameworks for merging and using images originating from different sources. This research investigates the quality assessment of Synthetic Aperture Radar (SAR) data fusion with optical imagery. Two different SAR data from different sensors namely RADARSAT-1 and PALSAR were fused with SPOT-2 data. Both SAR data have the same resolutionsand polarisations; however images were gathered in different frequencies as C band and L band respectively. This paper contributes to the comparative evaluation of fused data for understanding the performance of implemented image fusionalgorithms such as Ehlers, IHS (Intensity-Hue-Saturation), HPF (High Pass Frequency), two dimensional DWT (Discrete Wavelet Transformation), and PCA (Principal Component Analysis) techniques. Quality assessments of fused imageswere performed both qualitatively and quantitatively. For the statistical analysis; bias, correlation coefficient (CC), difference in variance (DIV), standard deviation difference (SDD), universal image quality index (UIQI) methods were applied on the fused images. The evaluations were performed by categorizing the test area into two as “urban” and “agricultural”. It has been observed that some of the methodshave enhanced either the spatial quality or preserved spectral quality of the original SPOT XS image to various degrees while some approaches have introduced distortions. In general we noted that Ehlers’ spectral quality is far better than those of the other methods. HPF performs almost best in agricultural areas for both SAR images
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