Remote sensing of penguin populations : development and application of a satellite-based method

• Main Author: Brown, Jennifer Anne
• Format: Dissertation
• Language: English
• Published: University of Cambridge 2018
• Subjects: Antarctica; guano; hyperspectral; penguins; Pygoscelis; remote sensing; satellite; Signy
• DOI: 10.17863/CAM.25245

Five penguin species breed in Antarctica: emperors, Adélies, chinstraps, gentoos and macaronis. These are important Antarctic mid-trophic level predators and under predicted climate change are believed threatened. Accurate monitoring of populations is therefore of growing importance owing to the changing environment in which they live, particularly on the Western Antarctic Peninsula where rapid warming is occurring. The inaccessibility and size of many colonies makes ground based monitoring difficult with remote sensing providing an alternative, relatively low cost, monitoring method. Advancing current monitoring methods will help improve estimates of population trajectories at a regional scale. Recent and future progress in remote sensing, with new satellite sensors and platforms, offers increased potential for accurate, consistent large-scale data collection. The work in this thesis focuses on difficult to monitor brush-tailed penguins (Adélies, chinstraps and gentoos), aiming to develop new techniques and algorithms to improve their monitoring by satellite imagery. Penguin detection in satellite imagery is based on the red/brown guano stains that colonies create, with these stains evident from space. Fieldwork undertaken in Antarctica (Nov 2014-Jan 2015) using a field spectroradiometer obtained the first in situ hyperspectral reflectance spectra of Adélie and chinstrap guano. These spectra are used to identify the features responsible for varying guano types and suggest new indices for differentiating these in satellite imagery. Satellite imagery coincident with the fieldwork, obtained from WorldView-3 (~40 cm resolution) and Landsat 8 (~15 m resolution), are used to trial the index derived from the field spectra. Analysis of the field data and satellite images includes examination of guano colour for different species and comparison of methods of guano detection, aiming to enhance species detection from satellite imagery. In addition, Landsat 8 imagery from further locations is used to produce time series of this index for colonies, examining how guano colour changes over the breeding season are seen in satellite imagery. This dissertation concludes with recommendations for future developments of satellite-based methods based on the results of these analyses. Such improvements should help improve our current understanding of penguin population and continuing population changes in relation to climate change.