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Cost-effective observation methodology to assess seal population sizes using unmanned aerial vehicle and automatic image analysis


The abundance estimation of ice breeding seals (harp and hooded) and coastal seals (grey and harbour) are based on aerial photographic surveys and manual inspection of aerial photographs. Photo surveys in remote areas (the West Ice) are expensive and the logistics have become increasingly difficult during the last years. The project aims to explore the use of unmanned aerial vehicle (UAV) operated from a survey vessel to photograph harp and hooded seal whelping areas. The photos will be analysed and model led using a mosaic method, which will give a total photographic coverage of the area and provides us with the opportunity to obtain a total number of seals in the covered area. Then we will explore how various sampling techniques, such as random sampling and traditional aerial strip transect methods with different transect widths and various spatial coverage along transects will affect the quality of the estimates of the seal abundance. Manual analysis of the images is extremely time consuming and costly, and involves subjective human interpretation by trained experts. This project aims at developing methodology for automating the process of counting seals from aerial images. This will be achieved through the development of new image analysis and pattern recognition techniques tailored to detect seals in digital colour images. The project will also investigate the potential of thermal infrared sensors that extract temperature characteristics of the imaged objects. The result of the research will be knowle dge about how to apply an UAV to estimate the seal population sizes, and a set of algorithms for automatic and semi-automatic detection of seals in aerial images, leading to cost-effective abundance estimation of seal populations. This will further lead t o better long-term management of seal populations. This project would make a valuable contribution by simplifying the logistics and reducing the cost of collecting field data.

Project leader: Kjell Tormod Nilssen

Started: 2014

Ends: 2017

Category: Primærnæringsinstitutter

Sector: Instituttsektor

Budget: 4620000


Address: Bergen