Aumento della risoluzione spaziale per il sondaggio di temperatura e umidità da satellite geostazionario mediante radiometria ad onde millimetriche e submillimetriche

The purpose of this study is to develop and evaluate techniques that improve the spatial resolution of the channels already selected in the preliminary studies for Geostationary Observatory for Microwave Atmospheric Soundings (GOMAS). Reference high resolution multifrequency brightness temperatures scenarios have been derived by applying radiative transfer calculation to the spatially and microphysically detailed output of meteorological events simulated by the University of Wisconsin - Non-hydrostatic Model System (UW-NMS). Three approaches, Wiener filter, Super-Resolution and Image Fusion have been applied to some representative GOMAS frequency channels to enhance the resolution of antenna temperatures. The Wiener filter improved resolution of the largely oversampled images by a factor 1.5- 2.0 without introducing any penalty in the radiometric accuracy. Super-resolution, suitable for not largely oversampled images, improved resolution by a factor ~1.5 but introducing an increased radiometric noise by a factor 1.4-2.5. The image fusion allows finally to further increase the spatial frequency of the images obtained by the Wiener filter increasing the total resolution up to a factor 5.0 with an increased radiometric noise closely linked to the radiometric frequency and to the examined case study.

Multitemporal analysis of satellite imagery: implementation of a land evolution model in ALCS (ATSR LAND CLASSIFICATION SYSTEM)

In this report it was designed an innovative satellite-based monitoring approach applied on the Iraqi Marshlands to survey the extent and distribution of marshland re-flooding and assess the development of wetland vegetation cover. The study, conducted in collaboration with MEEO Srl , makes use of images collected from the sensor (A)ATSR onboard ESA ENVISAT Satellite to collect data at multi-temporal scales and an analysis was adopted to observe the evolution of marshland re-flooding. The methodology uses a multi-temporal pixel-based approach based on classification maps produced by the classification tool SOIL MAPPER ®. The catalogue of the classification maps is available as web service through the Service Support Environment Portal (SSE, supported by ESA). The inundation of the Iraqi marshlands, which has been continuous since April 2003, is characterized by a high degree of variability, ad-hoc interventions and uncertainty. Given the security constraints and vastness of the Iraqi marshlands, as well as cost-effectiveness considerations, satellite remote sensing was the only viable tool to observe the changes taking place on a continuous basis. The proposed system (ALCS – AATSR LAND CLASSIFICATION SYSTEM) avoids the direct use of the (A)ATSR images and foresees the application of LULCC evolution models directly to „stock‟ of classified maps. This approach is made possible by the availability of a 13 year classified image database, conceived and implemented in the CARD project (http://earth.esa.int/rtd/Projects/#CARD).The approach here presented evolves toward an innovative, efficient and fast method to exploit the potentiality of multi-temporal LULCC analysis of (A)ATSR images. The two main objectives of this work are both linked to a sort of assessment: the first is to assessing the ability of modeling with the web-application ALCS using image-based AATSR classified with SOIL MAPPER ® and the second is to evaluate the magnitude, the character and the extension of wetland rehabilitation.

Development of oil spill detection techniques for satellite optical sensors and their application to monitor oil spill discharge in Mediterranean sea

Satellite remote sensing has proved to be an effective support in timely detection and monitoring of marine oil pollution, mainly due to illegal ship discharges. In this context, we have developed a new methodology and technique for optical oil spill detection, which make use of MODIS L2 and MERIS L1B satellite top of atmosphere (TOA) reflectance imagery, for the first time in a highly automated way. The main idea was combining wide swaths and short revisit times of optical sensors with SAR observations, generally used in oil spill monitoring. This arises from the necessity to overcome the SAR reduced coverage and long revisit time of the monitoring area. This can be done now, given the MODIS and MERIS higher spatial resolution with respect to older sensors (250-300 m vs. 1 km), which consents the identification of smaller spills deriving from illicit discharge at sea. The procedure to obtain identifiable spills in optical reflectance images involves removal of oceanic and atmospheric natural variability, in order to enhance oil-water contrast; image clustering, which purpose is to segment the oil spill eventually presents in the image; finally, the application of a set of criteria for the elimination of those features which look like spills (look-alikes). The final result is a classification of oil spill candidate regions by means of a score based on the above criteria.

Lava discharge rate estimates from thermal infrared satellite data at Pacaya Volcano, Guatemala

Time-averaged discharge rates (TADR) were calculated for five lava flows at Pacaya Volcano (Guatemala), using an adapted version of a previously developed satellite-based model. Imagery acquired during periods of effusive activity between the years 2000 and 2010 were obtained from two sensors of differing temporal and spatial resolutions; the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Geostationary Operational Environmental Satellites (GOES) Imager. A total of 2873 MODIS and 2642 GOES images were searched manually for volcanic “hot spots”. It was found that MODIS imagery, with superior spatial resolution, produced better results than GOES imagery, so only MODIS data were used for quantitative analyses. Spectral radiances were transformed into TADR via two methods; first, by best-fitting some of the parameters (i.e. density, vesicularity, crystal content, temperature change) of the TADR estimation model to match flow volumes previously estimated from ground surveys and aerial photographs, and second by measuring those parameters from lava samples to make independent estimates. A relatively stable relationship was defined using the second method, which suggests the possibility of estimating lava discharge rates in near-real-time during future volcanic crises at Pacaya.

A New Velocity Map for Byrd Glacier, East Antarctica, from Sequential Aster Satellite Imagery

New ice-velocity measurements are obtained for the main trunk of Byrd Glacier, East Antarctica, using recently acquired Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. The velocities are derived from the application of a cross-correlation technique to sequential images acquired in 2000 and 2001. Images were co-registered and ortho-rectified with the aid of a digital elevation model (DEM) generated from ASTER stereo imagery. This paper outlines the process of DEM generation, image co-registration and correction, and the application of the cross-correlation technique to obtain ice velocities. Comparison of the new velocity map with earlier measurements of velocity from 1978 indicates that the glacier has undergone a substantial deceleration between observations. Portions of the glacier flowing at speeds of similar to 850 m a(-1) in 1978/79 were flowing at similar to 650 m a(-1) in 2000/01. The cause of this change in ice dynamics is not known, but the observation shows that East Antarctic outlet glaciers can undergo substantial changes on relatively short timescales.

Streak detection algorithm for space debris detection on optical images.

Any image processing object detection algorithm somehow tries to integrate the object light (Recognition Step) and applies statistical criteria to distinguish objects of interest from other objects or from pure background (Decision Step). There are various possibilities how these two basic steps can be realized, as can be seen in the different proposed detection methods in the literature. An ideal detection algorithm should provide high recognition sensitiv ity with high decision accuracy and require a reasonable computation effort . In reality, a gain in sensitivity is usually only possible with a loss in decision accuracy and with a higher computational effort. So, automatic detection of faint streaks is still a challenge. This paper presents a detection algorithm using spatial filters simulating the geometrical form of possible streaks on a CCD image. This is realized by image convolution. The goal of this method is to generate a more or less perfect match between a streak and a filter by varying the length and orientation of the filters. The convolution answers are accepted or rejected according to an overall threshold given by the ackground statistics. This approach yields as a first result a huge amount of accepted answers due to filters partially covering streaks or remaining stars. To avoid this, a set of additional acceptance criteria has been included in the detection method. All criteria parameters are justified by background and streak statistics and they affect the detection sensitivity only marginally. Tests on images containing simulated streaks and on real images containing satellite streaks show a very promising sensitivity, reliability and running speed for this detection method. Since all method parameters are based on statistics, the true alarm, as well as the false alarm probability, are well controllable. Moreover, the proposed method does not pose any extraordinary demands on the computer hardware and on the image acquisition process.

Search for satellites near comet 67P/Churyumov-Gerasimenko using Rosetta/OSIRIS images

Context. The European Space Agency Rosetta mission reached and started escorting its main target, the Jupiter-family comet 67P/Churyumov-Gerasimenko, at the beginning of August 2014. Within the context of solar system small bodies, satellite searches from approaching spacecraft were extensively used in the past to study the nature of the visited bodies and their collisional environment. Aims. During the approaching phase to the comet in July 2014, the OSIRIS instrument onboard Rosetta performed a campaign aimed at detecting objects in the vicinity of the comet nucleus and at measuring these objects' possible bound orbits. In addition to the scientific purpose, the search also focused on spacecraft security to avoid hazardous material in the comet's environment. Methods. Images in the red spectral domain were acquired with the OSIRIS Narrow Angle Camera, when the spacecraft was at a distance between 5785 km and 5463 km to the comet, following an observational strategy tailored to maximize the scientific outcome. From the acquired images, sources were extracted and displayed to search for plausible displacements of all sources from image to image. After stars were identified, the remaining sources were thoroughly analyzed. To place constraints on the expected displacements of a potential satellite, we performed Monte Carlo simulations on the apparent motion of potential satellites within the Hill sphere. Results. We found no unambiguous detections of objects larger than similar to 6 m within similar to 20 km and larger than similar to 1 m between similar to 20 km and similar to 110 km from the nucleus, using images with an exposure time of 0.14 s and 1.36 s, respectively. Our conclusions are consistent with independent works on dust grains in the comet coma and on boulders counting on the nucleus surface. Moreover, our analysis shows that the comet outburst detected at the end of April 2014 was not strong enough to eject large objects and to place them into a stable orbit around the nucleus. Our findings underline that it is highly unlikely that large objects survive for a long time around cometary nuclei.