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Article

An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

1
Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York, NY 11794, USA
2
Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT 06269, USA
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Author to whom correspondence should be addressed.
Academic Editors: Ioannis Gitas and Prasad S. Thenkabail
Remote Sens. 2016, 8(5), 375; https://doi.org/10.3390/rs8050375
Received: 10 February 2016 / Revised: 18 April 2016 / Accepted: 25 April 2016 / Published: 30 April 2016
The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA) methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR) satellite imagery and closely examined the transferability of knowledge-based GEOBIA rules across different study sites focusing on the same semantic class. We systematically gauged the segmentation quality, classification accuracy, and the reproducibility of fuzzy rules. A master ruleset was developed based on one study site and it was re-tasked “without adaptation” and “with adaptation” on candidate image scenes comprising guano stains. Our results suggest that object-based methods incorporating the spectral, textural, spatial, and contextual characteristics of guano are capable of successfully detecting guano stains. Reapplication of the master ruleset on candidate scenes without modifications produced inferior classification results, while adapted rules produced comparable or superior results compared to the reference image. This work provides a road map to an operational “image-to-assessment pipeline” that will enable Antarctic wildlife researchers to seamlessly integrate VHSR imagery into on-demand penguin population census. View Full-Text
Keywords: Antarctica; penguins; guano; GEOBIA; VHSR imagery; census Antarctica; penguins; guano; GEOBIA; VHSR imagery; census
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MDPI and ACS Style

Witharana, C.; Lynch, H.J. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images. Remote Sens. 2016, 8, 375. https://doi.org/10.3390/rs8050375

AMA Style

Witharana C, Lynch HJ. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images. Remote Sensing. 2016; 8(5):375. https://doi.org/10.3390/rs8050375

Chicago/Turabian Style

Witharana, Chandi, and Heather J. Lynch 2016. "An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images" Remote Sensing 8, no. 5: 375. https://doi.org/10.3390/rs8050375

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