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Topic

Analysis of the Pacific Herring Population Spawning Areas Using Satellite Remote sensing

Department of Geography

Date & location

• Monday, September 15, 2025

• 10:00 A.M.

• Virtual Defence

Reviewers

Supervisory Committee

• Dr. Maycira Costa, Department of Geography, University of Victoria (Supervisor)

• Dr. David Atkinson, Department of Geography, UVic (Member) 

External Examiner

• Dr. Anders Jensen Knudby, Department of Geography, Environment and Geomatics, University of Ottawa 

Chair of Oral Examination

• Dr. Pauline van den Driessche, Department of Mathematics and Statistics, UVic

   

Abstract

Pacific Herring (Clupea pallasii) plays a critical ecological role as a forage species in the coastal waters of British Columbia (BC), supporting marine biodiversity and sustaining cultural and economic practices, particularly among Indigenous communities. However, longstanding concerns about spawning population variability, survey limitations, and changing environmental conditions have highlighted the need for improved methods to monitor herring spawning events. Traditional aerial and dive surveys conducted by the Department of Fisheries and Oceans (DFO), while valuable, may fail to capture the full spatial and temporal extent of these events, particularly in less-monitored regions and outside peak spawning windows. Remote sensing technologies have significant potential for visualizing herring spawning in BC; however, there is currently no automated method for detecting this type of coastal event over a time series using a medium-resolution (10–30 m) multisensor approach. This research aims to develop a remote sensing approach to detect herring spawning events, improving the knowledge of the timing of these events in southern BC waters. To address this, a methodology was developed using medium resolution satellites to accurately detect herring spawning events along the coast of North-East Vancouver Island (NEVI), followed by an analysis of the spatiotemporal distribution and change of herring spawning events in the NEVI based on historical satellite imagery (1985 to 2024).

The specific objectives of Chapter 2 were to implement two classification methods: a threshold-based approach (ThBA) using a developed spectral-based Spectral Herring Spawning Index (SHSI) and a Random Forest model (RF) using the SHSI and spectral bands. Both were evaluated using historical satellite imagery from multiple sensors (Landsat 5–9 and Sentinel-2) over February, March, and April between 1985 and 2024, and validated against a reference dataset of known spawning events. Both methods achieved satisfactory detection accuracy, mean values off 78.3% and 68.7% respectively for the ThBA and RF, with the ThBA demonstrating more consistent performance across different sensors. The RF classifier is characterised by a sensitivity to different types of confusion and was more affected by optically complex environmental conditions (e.g. the Fraser plume, cloud artifacts). Combined, these approaches allowed for alternatives of either a high-confidence or a very inclusive inventory of spawning events.

The spatiotemporal analysis conducted in Chapter 3 aimed at the comparison of the satellite-based detection compared to the reference dataset. The ThBA applied over the whole time series revealed previously undocumented spawning events, especially north of Vancouver Island, while also improving the spatial and temporal definition of events detected by traditional surveys. These findings underscore the potential of satellite-based monitoring as a scalable, cost-effective, and complementary tool to traditional survey methods. This method has the potential to inform ecosystem-based management, support policy development, and enhance the capacity of Indigenous stakeholders to monitor and protect critical herring spawning habitats by providing open-access and easily replicable methods.