Visualization of spatial patterns and temporal trends for aerial surveillance of illegal oil discharges in western Canadian marine waters

Analyzing the spatiotemporal habitat colonization dynamics of the common vole (Microtus arvalis Pallas) in Castilla y León, northwest Spain, using a hotspot-based approach†

BACKGROUND

The common vole is an agricultural pest and population outbreaks have caused significant crop damage in the agricultural areas of the west-central part of the Iberian Peninsula (Spain) during the last few decades. Thus, monitoring is imperative to gain a comprehensive insight on its spatiotemporal habitat colonization dynamics. This work was performed on a long-term database with the primary objective of establishing an operational framework for understanding the spatial and temporal distribution of the common vole, all of it based on the Getis-Ord statistics.

RESULTS

The temporal evolution of the vole abundance index (VAI) was consistent for the three studied habitats, that is, crops, reservoirs and paths. Furthermore, the majority of common vole abundance peaks coincide with summer periods, especially in annual herbaceous crops. The spatial distribution of vole abundance exhibited a non-random pattern, characterized by spatial clustering. Particularly, the areas with higher significance of this clustering were located at the so-called 'Tierra de Campos' county, covering northern Valladolid, southern Palencia and north-eastern Zamora provinces. Periods of major incidence and concentration were 2013-2014, 2016-2017 and 2019. Common vole temporal occupancy patterns demonstrate that colonization occurred simultaneously in alfalfa reservoirs and dispersion paths, both preceding settlement in annual herbaceous crop plots.

CONCLUSION

The geographic information system (GIS)-hotspots-based methodology proposed here can be valuable for stakeholders involved in integrated management of the common vole, serving as a detector of pest-prone areas in both space and time. These hotspots are useful for predicting future surveillance areas that accurately reflect pest colonization patterns. It was found that common vole abundance along dispersal paths acts as a source of dissemination, preceding the risk of colonization in annual herbaceous crop plots. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

OS-BREEZE: Oil Spills Boundary Red Emission Zone Estimation Using Unmanned Surface Vehicles

Maritime transport, responsible for delivering over eighty percent of the world's goods, is the backbone of the global delivery industry. However, it also presents considerable environmental risks, particularly regarding aquatic contamination. Nearly ninety percent of marine oil spills near shores are attributed to human activities, highlighting the urgent need for continuous and effective surveillance. To address this pressing issue, this paper introduces a novel technique named OS-BREEZE. This method employs an Unmanned Surface Vehicle (USV) for assessing the extent of oil pollution on the sea surface. The OS-BREEZE algorithm directs the USV along the spill edge, facilitating rapid and accurate assessment of the contaminated area. The key contribution of this paper is the development of this novel approach for monitoring and managing marine pollution, which significantly reduces the path length required for mapping and estimating the size of the contaminated area. Furthermore, this paper presents a scale model experiment executed at the Coastal and Marine Engineering Research Institute (CAMERI). This experiment demonstrated the method's enhanced speed and efficiency compared to traditional monitoring techniques. The experiment was methodically conducted across four distinct scenarios: the initial and advanced stages of an oil spill at the outer anchoring, as well as scenarios at the inner docking on both the stern and port sides.

Spatial and temporal assessment of oil spills in the Mediterranean Sea

Ship-generated oil pollution is a significant threat to the Mediterranean Sea. We present a geostatistical analysis of oil spills using three databases for the Mediterranean Sea: REMPEC (1977-2000) with 385 spills (17/year), ITOPF (1970-2018) with 167 spills (3.5/year) and EMSA (2015-2017) with 2066 detections (688/year). It was found that 88% of spills reported by REMPEC occurred near coastline areas, while 65% of the spills detected by EMSA occurred within a range of 22-100 km from the coastline. At the Exclusive Economic Zone (EEZ) level, EMSA oil spills densities were positively correlated with shipping and port activity. We conclude that there is a need to develop an open-access database of oil spills that will be based on both reports and remote sensing acquisition methods. Such a database will facilitate more efficient enforcement of international conventions in offshore areas and will increase the likelihood of effective response.

Spatial Analysis of Accidental Oil Spills Using Heterogeneous Data: A Case Study from the North-Eastern Ecuadorian Amazon

Accidental oil spills were assessed in the north-eastern Ecuadorian Amazon, a rich biodiversity and cultural heritage area. Institutional reports were used to estimate oil spill volumes over the period 2001–2011. However, we had to make with heterogeneous and incomplete data. After statistically discriminating well- and poorly-documented oil blocks, some spill factors were derived from the former to spatially allocate oil spills where fragmentary data were available. Spatial prediction accuracy was assessed using similarity metrics in a cross-validation approach. Results showed 464 spill events (42.2/year), accounting for 10,000.2 t of crude oil, equivalent to annual discharges of 909.1 (±SD = 1219.5) t. Total spill volumes increased by 54.8% when spill factors were used to perform allocation to poorly-documented blocks. Resulting maps displayed pollution ‘hotspots’ in Dayuma and Joya de Los Sachas, with the highest inputs averaging 13.8 t km−2 year−1. The accuracy of spatial prediction ranged from 32 to 97%, depending on the metric and the weight given to double-zeros. Simulated situations showed that estimation accuracy depends on variabilities in incident occurrences and in spill volumes per incident. Our method is suitable for mapping hazards and risks in sensitive ecosystems, particularly in areas where incomplete data hinder this process.

A preliminary spatial assessment of risk: Marine birds and chronic oil pollution on Canada's Pacific coast

Chronic oil pollution poses substantial risks to marine birds and other marine wildlife worldwide. On Canada's Pacific coast, the negative ecological consequences to marine birds and marine ecosystems in general remain poorly understood. Using information relating to oil spill probability of occurrence, areas of overall importance to marine birds, and the at-sea distribution and density of 12 marine bird species and seven bird groups, including multiple Species at Risk, we undertook a spatial assessment of risk. Our results identify two main areas important to marine birds potentially at higher risk of exposure to oil. For individual bird species or species groups, those predicted to have elevated bird densities near the mainland and the northeast coast of Vancouver Island were identified as being at higher potential risk of exposure. Our results, however, should be considered preliminary. As with other anthropogenic stressors, in order to better understand and subsequently mitigate the consequences of chronic oil pollution on marine birds, improved information relating to marine birds and the occurrence of oil spills on Canada's Pacific coast is needed.

Offshore oil spill response practices and emerging challenges

Offshore oil spills are of tremendous concern due to their potential impact on economic and ecological systems. A number of major oil spills triggered worldwide consciousness of oil spill preparedness and response. Challenges remain in diverse aspects such as oil spill monitoring, analysis, assessment, contingency planning, response, cleanup, and decision support. This article provides a comprehensive review of the current situations and impacts of offshore oil spills, as well as the policies and technologies in offshore oil spill response and countermeasures. Correspondingly, new strategies and a decision support framework are recommended for improving the capacities and effectiveness of oil spill response and countermeasures. In addition, the emerging challenges in cold and harsh environments are reviewed with recommendations due to increasing risk of oil spills in the northern regions from the expansion of the Arctic Passage.

Modeling the distribution of illicit oily discharges detected by aerial surveillance in western Canadian marine waters

Oily discharges from vessel operations have been documented in Canada's Pacific region by the National Aerial Surveillance Program (NASP) since the early 1990s. We explored a number of regression methods to explain the distribution and counts per grid cell of oily discharges detected from 1998 to 2007 using independent predictor variables, while trying to address the large number of zeros present in the data. Best-fit models indicate that discharges are generally concentrated close to shore typically in association with small harbours, and with major commercial and tourist centers. Oily discharges were also concentrated in Barkley Sound and at the entrance of Juan de Fuca Strait. The identification of important factors associated with discharge patterns, and predicting discharge rates in areas with surveillance effort can be used to inform future surveillance. Model output can also be used as inputs for risk models for existing conditions and as baseline for future scenarios.

Estimating discharge rates of oily wastes and deterrence based on aerial surveillance data collected in western Canadian marine waters

Illegal discharge of waste oil from ships is a major source of mortality for seabirds globally. Using linear and log-linear regression, we explored the relationship between detection rates of marine oily discharges and surveillance effort at different time scales, based on data collected in the Canadian Pacific Ocean by the National Aerial Surveillance Program (NASP) from 1997 to 2006. We introduce an approach for quantifying reductions in discharge rates with increased surveillance while controlling appropriately for surveillance effort, as standard linear correction for effort can introduce considerable bias. Despite low probabilities of detection (0.088-1.1%), we found evidence for reduced discharge rates with increasing surveillance effort for data summarized monthly and bimonthly in region A, which is closest to the NASP base airport. Using residuals derived from the best-fit log-linear models, we found detected discharge rates declined annually (-[0.070 spills/month]×year).

Hotspot analysis of spatial environmental pollutants using kernel density estimation and geostatistical techniques

Concentrations of four heavy metals (Cr, Cu, Ni, and Zn) were measured at 1,082 sampling sites in Changhua county of central Taiwan. A hazard zone is defined in the study as a place where the content of each heavy metal exceeds the corresponding control standard. This study examines the use of spatial analysis for identifying multiple soil pollution hotspots in the study area. In a preliminary investigation, kernel density estimation (KDE) was a technique used for hotspot analysis of soil pollution from a set of observed occurrences of hazards. In addition, the study estimates the hazardous probability of each heavy metal using geostatistical techniques such as the sequential indicator simulation (SIS) and indicator kriging (IK). Results show that there are multiple hotspots for these four heavy metals and they are strongly correlated to the locations of industrial plants and irrigation systems in the study area. Moreover, the pollution hotspots detected using the KDE are the almost same to those estimated using IK or SIS. Soil pollution hotspots and polluted sampling densities are clearly defined using the KDE approach based on contaminated point data. Furthermore, the risk of hazards is explored by these techniques such as KDE and geostatistical approaches and the hotspot areas are captured without requiring exhaustive sampling anywhere.

Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms

This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR) for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and coastal ecosystem. The amount of pollutant discharges and associated effects on the marine environment are important parameters in evaluating sea water quality. Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. SAR images have been widely used for oil spill detection. The present paper gives an overview of the methodologies used to detect oil spills on the radar images. In particular we concentrate on the use of the manual and automatic approaches to distinguish oil spills from other natural phenomena. We discuss the most common techniques to detect dark formations on the SAR images, the features which are extracted from the detected dark formations and the most used classifiers. Finally we conclude with discussion of suggestions for further research. The references throughout the review can serve as starting point for more intensive studies on the subject.