Since the 1980s, satellite-borne synthetic aperture radar (SAR) has been investigated for early warning and monitoring of marine oil spills to permit effective satellite surveillance in the marine environment.Automated detection of oil spills from satellite SAR intensity imagery consists of three steps: 1) Detection of dark spots; 2) Extraction of features from the detected dark spots; and 3) Classification of the dark spots into oil spills and look-alikes. However, marine oil spill detection is a very difficult and challenging task. Open questions exist in each of the three stages.In this thesis, the focus is on the first stage-dark spot detection. An efficient and effective dark spot detection method is critical and fundamental for developing an automated oil spill detection system. A novel method for this task is presented. The key to the method is utilizing the spatial density feature to enhance the separability of dark spots and the background. After an adaptive intensity thresholding, a spatial density thresholding is further

High-rate GNSS positioning has been widely investigated and applied in science and engineering. We extend it to high-rate attitude determination under a multi-GNSS constellation. A series of experiments of high-rate GNSS attitude determination has been conducted on a platform with three 50 Hz geodetic receivers and two high-grade inertial measurement units (IMU). The high-rate attitude solutions are computed for each of the multi-GNSS systems and the combined constellation by either using short baselines with correct ambiguity resolution or precise point positioning (PPP) and compared with the IMU measurements. In the case of a single GNSS system, the experimental results have shown that GPS is of the best accuracy, followed by GLONASS. The results with Beidou are the noisiest. The combined multi-GNSS constellation can significantly improve the high-rate attitude solutions from any single GNSS system alone, which is, in particular, most suitable for applications to any platform in slow or quasi-static motion. However, the improvement rate could depend on proper weightings of measurements from different GNSS systems in the dynamical experiments. The accuracy of baseline-based high-rate GNSS attitude solutions remains stable over time, while that of PPP-based solutions substantially degrades with time, as theoretically expected. Within a short period of time, the PPP-based high-rate yaw solutions with the combined multi-GNSS constellation are comparable in accuracy with those computed from baselines with correct ambiguity resolution in the dynamical experiments. The attitude results from either static or dynamical experiments have shown that high-rate GNSS attitude determination is sufficiently precise to measure rotatory motions. GNSS rotational seismology is applied to the 2011 Tohoku Mw9.0 earthquake, illustrating the potential of multi-GNSS to precisely detect seismic rotatory motions.

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Rapid response to destructive tsunami and seismic events requires rapid determination of the earthquake magnitude. We propose a new method that employs peak ground velocities (PGVs) derived from Global Navigation Satellite System (GNSS) data to estimate earthquake magnitudes. With a total of 1434 records from 22 events as the constraints, we perform the regression and obtain a PGV scaling law for magnitude determination. The advantage of the new method is that the PGVs are extracted from the GNSS velocity waveforms, which can be easily computed using broadcast GNSS ephemeris. In contrast, the peak ground displacement (PGD) depends on a sophisticated high-precision GNSS-processing subject to external correction data, realization of which cannot be kept robust constantly, especially in real time. The results show that the PGV magnitudes agree with reported moment magnitudes with mean absolute deviation of 0.26 magnitude units for the 22 events and also agree well with the PGD magnitude. We further demonstrate that GNSS-derived PGV and the modified Mercalli intensity values can be consistent with their counterparts from the U.S. Geological Survey ShakeMap products and therefore the GNSS-derived PGVs have the potential to be included in the ShakeMap as a complementary constraint, especially in areas with sparse seismic station coverage for large earthquake.