## 1 Introduction  
Climate change, fisheries, cetacean recovery, and human disturbance are all hypothesized as drivers of ecological change in Antarctica [1; 2; 3; 4]. Climate change is of particular concern on the western Antarctic Peninsula, because mean annual temperatures have risen 2 \({}^{\circ}\)C while mean winter temperatures have risen more than 5 \({}^{\circ}\)C [5; 6; 7; 8; 9]. The consequences of climate change may be seen across the marine food web from phytoplankton to top predators [3; 10; 11; 12; 13], though study of these processes has been traditionally limited by the challenges of doing field research across most of the Antarctic continent. The brushtailed penguins (_Pygoscelis_ spp.) are represented throughout Antarctica, and are composed of the Adelie penguin (_P. adeliae_), the chinstrap penguin (_P. antarctica_), and the gentoo penguin (_P. papua_). Adelie penguins are found around the entire continent, while chinstrap penguins and gentoo penguins are restricted to the Antarctic Peninsula and sub-Antarctic islands further north [14]. Owing to their narrow diets and the relative tractability of monitoring their populations at the breeding colony, penguins can serve as indicators of environmental and ecological change in the Southern Ocean [15; 16; 17]. Changes in the abundance and distribution of Antarctic penguin populations have been widely reported [13; 18], though it is only just recently, with the development of remote sensing (RS) as a tool for direct estimation of penguin populations, that we have been able to survey the Antarctic coastline comprehensively rather than at a few selected, easily-accessed breeding sites (e.g., [19; 20; 21]). These rapid and spatially-heterogeneous changes in penguin populations, and the appeal of penguins as an indicator of comprehensive shifts in the ecological functioning of the Southern Ocean, motivate the development of robust, automated (or semi-automated) workflows for the interpretation of satellite imagery for routine (annual) tracking of penguin populations at the continental scale. The Antarctic is quickly becoming a model system for the use of Earth Observation (EO) for the physical and biological sciences because the costs of field access are high, the landscape is simple (e.g., rock, snow, ice, water) and free of woody vegetation, and polar orbiting satellites provide extensive regular coverage of the region. Logistical challenges, difficulty in comprehensively searching out animals (individuals or groups) that are scattered across a vast continent, and limited scalability and repeatability of traditional survey approaches have further catalyzed the addition of EO-based methods to more traditional ground-based census methods [22]. Increased access to sub-meter commercial satellite images of very high spatial resolution (VHSR) EO sensors like IKONOS, QuickBird, GeoEye, Pleiades, Worldview-2, and Worldview-3, which rival aerial imagery in terms of spatial resolution, has added new methods for direct survey of individual animals or animal groups to the existing suite of tools available for land cover types. Since the early studies conducted by [23; 24], which uncovered the potential of penguin guano detection from medium-resolution EO sensors, a number of efforts to detect the distribution and abundance of penguin populations have been conducted using aerial sensors [25; 26], medium-resolution satellite sensors like Landsat and SPOT [19; 21; 27; 28; 29; 30; 31], and VHSR satellite sensors, such as IKONOS, Quickbird, and WorldView [13; 20; 22; 32]. While the use of VHSR imagery for Antarctic surveys has been demonstrated as feasible, there remain several challenges before VHSR imagery can be operationalized for regular ecological surveys or conservation assessments. Classification currently hinges on the experience of trained interpreters with direct on-the-ground experience with penguins, and manual interpretation is so labor intensive that large-scale surveys can be completed only infrequently.