Oil spills, whether in open water or near shorelines, cause serious environmental problems. Moreover, polarimetric synthetic-aperture radar provides abundant oil spill information with all-weather, day–night detection capability, but its use is limited by data usage and processing costs. Compact Polarimetric (CP) systems as a subsequent emerging system, which balance data volume and system design requirements, are promising in this regard. Herein, we utilize multisource oil spill scenarios and datasets from multiple polarimetric modes (VV-HH, π/4, DCP, and CTLR) to assess the oil spill detection capability of each mode under varying incidence angles conditions, spill causes, and oil types. Using qualitative and quantitative evaluation indicators, we compare the typical features of the multiple polarization modes as well as assess their consistency with Full Polarization (FP) information and their oil spill recognition performance across different incidence angles. In large-incidence-angle oil spill scenarios, the VV–HH mode exhibits the highest information consistency with the FP mode and the strongest oil spill recognition ability. At small incidence angles, the CP mode (i.e., CTLR mode) exhibits the best overall performance, benefiting from its effective self-calibration capability and low noise sensitivity. Furthermore, despite containing comprehensive information, the FP mode is not always superior to the dual-polarization and CP modes. Thus, in oil spill scenarios across different incidence angles, incorporating features from an appropriate polarization mode into oil spill information extraction and recognition can optimize the associated efficiency.

Detecting marine oil spills is vital for protecting the marine environment, ensuring maritime traffic safety, supporting marine development, and enabling effective emergency response. The dual-polarimetric (DP) synthetic aperture radar (SAR) system represents an evolution from single to full polarization (FP), which has become an essential tool for oil spill detection with the growing availability of open-source and shared datasets. Recent research has focused on enhancing DP information structures to better exploit this data. This study introduces improved DP models’ structure with modified the scattering vector coefficients to ensure consistency with the corresponding components of the FP system, enabling comprehensive comparison and analysis with traditional DP structure, includes theoretical and quantitative evaluations of simulated data from FP system, as well as validation using real DP scenarios. The results showed the following: (1) The polarimetric entropy H_L obtained through the improved DP scattering matrix C_L can achieve higher information consistency results closely aligns with FP system and better performance, compared to the typical two DP scattering structures. (2) For multiple polarimetric features from DP scattering matrix (both traditional feature and combination feature), the improved DP scattering matrix C_L can be used for oil spill extraction effectively with prominent results. (3) For oil spill extraction, the polarimetric features-based C_L tend to have relatively high contribution, especially the H_A feature combination, leading to substantial gains in improved classification performance. This approach not only enriches the structural information of the DP system under VV–VH mode but also improves oil spill identification by integrating multi-structured DP features. Furthermore, it offers a practical alternative when FP data are unavailable.

Marine oil spills severely threaten marine ecosystems, the coastal economy, and marine engineering structures. Because it enables all-weather and all-time acquisition of rich target information, fully polarimetric synthetic aperture radar (FP SAR) is widely used for monitoring marine oil spills. However, the differences in the scattering characteristics among oil types can cause variability in the information contained in the features extracted using FP SAR. Herein, RADARSAT-2 images obtained from a rare oil-on-water experiment conducted in the Norwegian North Sea were used to compare the distribution differences in polarimetric features based on the oil slick type and incident angle. Results showed that the incident angle exerted some influence on polarimetric features and the detection performance for oil spills with a low oil–water contrast, particularly at large incident angles. The polarimetric features related to scattering mechanisms exhibited good robustness and effectiveness across various incident angles. The polarimetric feature that combines the scattering entropy H and modified anisotropy A₁₂ exhibited strong overall performance and high suitability for extracting information on oil spills at different incident angles. This study demonstrates that incorporating appropriate polarimetric features according to the incident angle enables the identification of different oil slick types and facilitates oil spill detection and monitoring.

Background: Urban blue–green environments are vital components of the urban exposome, shaping daily opportunities for physical activity, stress mitigation, and broader public health. However, these benefits depend on daily accessibility. In compact coastal metropolises, extensive nature may coexist with highly unequal residential access. This study investigates whether socially vulnerable residential areas in Shenzhen experience reduced exposure to public green and coastal blue spaces. Methods: Using 4,071 residential patches, a residential-scale exposure framework was developed. Social vulnerability was estimated with housing price, property-management fee, dwelling age, and neighborhood commercial-service structure. Blue–green exposure was calculated through a supply–demand model integrating walking-network accessibility, 15-min living-circle coverage, and residential demand. Lorenz curves evaluated capacity-weighted inequality. Scatterplots and quadrant typology analysis identified nonlinear associations and areas where high vulnerability coincided with low exposure. Results: Exposure to potentially restorative coastal blue–green places was unevenly distributed across Shenzhen. Residential areas with high or relatively high green-space exposure accounted for 16.12% of total residential area, whereas 167.31 km ² , or 12.77%, was classified as low exposure. Coastal blue-space exposure was more concentrated: 95.71% of residential land fell within the lowest exposure category, while high and relatively high exposure accounted for only 0.49 and 0.70%, respectively. The lowest-exposure 80% of capacity-weighted residential locations accounted for 11.08% of total green-space exposure, and approximately 94.76% of capacity-weighted residential locations had almost no coastal blue-space exposure. High green-space exposure became rare at high social vulnerability levels, and no substantial blue-space exposure was observed among patches with SVI values above approximately 0.85. Conclusion: Socially vulnerable communities endure a compounded socio-environmental disadvantage, wherein systemic socioeconomic marginalization is exacerbated by severe spatial deprivation of everyday restorative blue–green exposures. This spatial mismatch underscores that the mere physical presence of urban nature does not equate to equitable health-promoting opportunities. To advance environmental health equity, urban governance must transcend macro-level ecological expansion to prioritize targeted, neighborhood-scale interventions. By integrating micro-spatial renewal, enhancing inclusive waterfront connectivity, and implementing robust anti-displacement safeguards, healthy-city planning can ensure that the salutogenic benefits of the urban exposome are equitably accessible to all residents.