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Mapping the Abundance and Distribution of Ade´Lie Penguins Using Landsat-7

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Mapping the Abundance and Distribution of Ade´Lie Penguins Using Landsat-7 Mapping the Abundance and Distribution of Ade´lie Penguins Using Landsat-7: First Steps towards an Integrated Multi-Sensor Pipeline for Tracking Populations at the Continental Scale Heather J. Lynch1*, Mathew R. Schwaller2 1 Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York, United States of America, 2 Mesoscale Atmospheric Processes Laboratory, NASA/ Goddard Space Science Center, Greenbelt, Maryland, United States of America Abstract The last several years have seen an increased interest in the use of remote sensing to identify the location of penguin colonies in Antarctica, and the estimation of the abundance of breeding pairs contained therein. High-resolution (sub- meter) commercial satellite imagery (e.g., Worldview-1, Quickbird) is capable of colony detection and abundance estimation for both large and small colonies, and has already been used in a continental-scale survey of Ade´lie penguins. Medium- resolution Landsat imagery has been used successfully to detect the presence of breeding penguins, but has not been used previously for abundance estimation nor evaluated in terms of its minimum colony size detection threshold. We report on the first comprehensive analysis of the performance of these two methods for both detection and abundance estimation, identify the sensor-specific failure modes that can lead to both false positives and false negatives, and compare the abundance estimates of each method over multiple spatial scales. We find that errors of omission using Landsat imagery are low for colonies larger than ,10,000 breeding pairs. Both high-resolution and Landsat imagery can be used to obtain unbiased estimates of abundance, and while Landsat-derived abundance estimates have high variance for individual breeding colonies relative to estimates derived from high-resolution imagery, this difference declines as the spatial domain of interest is increased. At the continental scale, abundance estimates using the two methods are roughly equivalent. Our comparison of these two methods represents a bridge between the more developed high-resolution imagery, which can be expensive to obtain, and the medium-resolution Landsat-7 record, which is freely available; this comparison of methodologies represents an essential step towards integration of these disparate sources of data for regional assessments of Ade´lie population abundance and distribution. Citation: Lynch HJ, Schwaller MR (2014) Mapping the Abundance and Distribution of Ade´lie Penguins Using Landsat-7: First Steps towards an Integrated Multi- Sensor Pipeline for Tracking Populations at the Continental Scale. PLoS ONE 9(11): e113301. doi:10.1371/journal.pone.0113301 Editor: Guy J-P. Schumann, University California Los Angeles, United States of America Received April 21, 2014; Accepted October 23, 2014; Published November 20, 2014 This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files. We also provide a kmz file of the Landsat-7 retrievals (not necessary to reproduce the results reported in the paper, but possibly of use to readers) at the following URL: ftp://trmm-fc.gsfc.nasa.gov/wolff/MattS/landsat_adelie_colonies_full_continent.kmz. Funding: HJL was supported by National Science Foundation/Office of Polar Programs - Award No. 1255058; http://www.nsf.gov. HJL and MRS were supported by the National Air and Space Administration - Award No. NNX14AC32G; http://www.nasa.gov. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * Email: [email protected] Introduction automated algorithms that exploit the spectral signature of penguin guano can be used to detect the presence of penguin Though the idea of using satellite imagery to map penguin colonies in medium-resolution Landsat data [2,6]. Taken together, colonies is over thirty-years old [1], the use of these approaches for these new analytic methods—and the Terabytes of data to which ecological research and long-term monitoring has been in active they can be applied—afford the possibility of routine, continent- development only in the last few years (e.g., [2–4]). Recent data wide surveys of Ade´lie penguin presence and abundance, although policy changes, such as the free availability of archival Landsat to date no attempt has been made to use Landsat for regional imagery, have opened access to vast amounts of medium abundance estimation or to compare the detection and abundance resolution satellite imagery over Antarctica, and while access to information derived from these two types of satellite images. Our very high-resolution (VHR) imagery is hampered by licensing and analysis represents a bridge between abundance estimates based cost, increased tasking of satellites for imagery in the Antarctic on very high-resolution imagery and the medium-resolution data have rapidly increased the quantity of imagery available. Recent record available from Landsats-4, -5 and -7. Forging this studies demonstrate that penguin colony presence and abundance connection will facilitate integrated abundance estimates in the can be detected on a continental scale by manual interpretation of era when both of these satellite data types overlap, and will very high resolution (VHR) satellite imagery [5] and that PLOS ONE | www.plosone.org 1 November 2014 | Volume 9 | Issue 11 | e113301 Cross Validation of Ade´lie Penguin Detection and Abundance advance the development of a continuous time series of abundance streams is a necessary step in the full integration of these data into that leverages a Landsat data record dating back to the 1980s. a single remote sensing retrieval and analysis pipeline for This paper presents the results of an automated retrieval of monitoring Ade´lie penguin populations. This approach represents Ade´lie penguin colonies along the entire continent of Antarctica a significant improvement over direct field counts alone, which from medium-resolution Landsat-7 imagery (30 m pixel size), and lack the scalability of remote sensing surveys, and are subject to its comparison with data on presence and abundance based on underestimation bias in regional or global estimates due to the manual interpretation of VHR satellite imagery (,0.60 m pixel remoteness and inaccessibility of sections of the Antarctic coastline size). Landsat-7 launched on April 15, 1999 and has collected [7]. Population estimates that scale in space and time are expected imagery over Antarctica continuously since that time. Unfortu- to more seamlessly interoperate with trophic and climate models, nately, the ETM+ Scan Line Corrector failure in 2003 occurred so that changes in Ade´lie penguin populations can be clearly tied just as some of the first very-high resolution images became to harvesting in the Southern Ocean fisheries and climate change. available for the Antarctic, precluding direct contemporaneous comparison of abundance estimates from these two types of Methods sensors. We leverage the recently published global Ade´lie survey [5] to assess whether Landsat-7 can be used to estimate abundance Automated Landsat retrievals as well as occupancy, and to estimate the lower detection threshold Retrieval of Ade´lie penguin colony location and spatial extent for Landsat-7. Since the uncorrupted Landsat-7 imagery dates over the Antarctic Peninsula was conducted using Landsat-7 from 1999–2003 and the global Ade´lie survey [5] estimates Enhanced Thematic Mapper-Plus ETM+ data. The Landsat data predominately stem from 2010–2013, the correlation between the used in this study were obtained as a Climate Data Record (CDR), abundance estimates will be highly conservative, since the which was generated using the methods developed by [8], and correlation is degraded by changes in true abundance in the distributed by the U.S. Geological Survey Earth Resources intervening decade. Nevertheless, the relatively slow dynamics of Observation and Science Center (https://espa.cr.usgs.gov). This penguin colonies means that abundances between these two CDR applies a uniform processing to the entire dataset, and periods should be fairly consistent within the margin of error of the includes a host of products including top of atmosphere (TOA) abundance estimation itself, allowing us to investigate whether the reflectance, surface reflectance, brightness temperature, as well as number of pixels retrieved in the earlier period scales with the masks for clouds, cloud shadows, adjacent clouds, land and water. abundance reported by [5] for the latter period. This cross- The Landsat CDR TOA product was used for the automated validation approach is the best currently available to quantify the retrieval of Ade´lie penguin colonies following the methods accuracy and identify sources of error in using medium-resolution described in [2]. One difference between our Landsat survey Landsat imagery for occupancy (presence vs. absence) and and that described in [2] is that additional exposed soil and rock abundance. Controlling or correcting these errors is a key surfaces were sampled
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