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Optical remote sensing is emerging among non-conventional geophysical methods for oil & gas exploration and mineral prospecting. Complementary to all traditional technologies such as seismic, magnetic, gravity or electric methods, multispectral imaging is able to detect long-term biochemical and geochemical environmental alterations, known as microseepage effect, produced by invisible small fluxes...
This paper describes the use of a new multi-image co-registration method tuned for SAR multi-temporal data collected with different orbits, viewing angles and polarization. Tests were performed using COSMO-SkyMed (X-band) and Sentinel-1 data (C-band) time series imaged in stripmap and spotlight modes. Results shows an overview sub-pixel accuracy also for the challenging co-registration of dual orbit...
Every day, ships of different type, size and origin cross the world seas. Not only for commerce and transport, but also for illegal activities. In addition to conventional positioning and tracking systems, detection with Earth observation satellites is an effective means to monitor human movements across the sea. The European Copernicus Programme operates towards this goal, through the definition...
This paper presents the preliminary results obtained within a research project aimed to assess the feasibility of a system to monitor the immigration flows in the Southern Mediterranean Sea by solely relying on images coming from scientific and commercial satellites, which already operates on a regular basis. “Space Shepherd”, a project funded by Politecnico di Milano, Italy, has the ultimate goal...
Multispectral remote sensing is an emerging technology for the oil & gas industry. Since its first application, Earth Observation has seen an enormous breakthrough in a brand-new field such as geosciences for hydrocarbon exploration: both the awareness of the microseepage phenomenon and data processing methods for its detection have greatly improved in the last years. This paper describes a case...
This paper wants to explore the application of the theory of reliability, which has become largely popular in the analysis of geodetic and photogrammetric networks, to the multiple co-registration of satellite time-series of images through block adjustment. Indeed the current and future availability of long series of satellite imagery can be exploited for the purpose of change detection and soil monitoring...
Accidental release of crude oil into the sea due to human activity causes water pollution and heavy damages to natural ecosystems killing birds, fish, mammals and other organisms. A number of monitoring systems are used for tracking the spills and their effects on the marine environment, as well as for collecting data for feeding models. Among them, Earth observation technologies play a crucial role...
This paper investigates the use of Minimum Noise Fraction (MNF) components to improve the spectral separability of two specific thematic classes in airborne hyperspectral imagery using Spectral Angle Mapper (SAM). Particularly, we compared trends on data distribution before and after MNF transform. Two different data sets recorded with the Multispectral Infrared Visible Imaging Spectrometer (MIVIS)...
In modern remote sensing applications the use of automatic image processing codes is becoming increasingly common. When dealing with satellite time series or multi‐source data, image co‐registration is a time‐consuming, but necessary, pre‐processing step. This study shows how a medium resolution satellite multitemporal dataset can be effectively processed using automatic data processing. Results on real and transformed ASTER data showed that, without human interaction, the automatic ground control points extraction (AGE) technique, developed at Politecnico di Milano, is able to obtain accuracies generally sufficient for practical applications and similar to those reported in other studies....
This paper presents a photogrammetric procedure for human back shape reconstruction. The system is almost fully automated and provides an accurate 3D model by using a processing chain based on different image-matching algorithms. The method can be properly tuned to deal more effectively with different image datasets thanks to the optional choice between techniques and input parameters. This allows...
This study shows a comparison between pixel-based and object-based approaches in data fusion of high-resolution multispectral GeoEye-1 imagery and high-resolution COSMO-SkyMed SAR data for land-cover/land-use classification. The per-pixel method consisted of a maximum likelihood classification of fused data based on discrete wavelet transform and a classification from optical images alone. Optical...
This paper describes the use of airborne hyperspectral remote sensing for mapping asbestos roofs in an orographic complex area in Northern Italy, the Aosta Valley. Using training samples collected during field surveys, thematic classification was able to detect the majority of asbestos surfaces. Considering the total amount of asbestos areas validation showed a correct detection of about 80%, while...
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