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Wildlife and Marine Mammal Spatial Observatory: Observation and automated detection of Southern Right Whales in multispectral satellite imagery

Ludwig Houegnigan, View ORCID ProfileEnrique Romero Merino, View ORCID ProfileEls Vermeulen, Jessica Block, Pooyan Safari, View ORCID ProfileFrancesc Moreno-Noguer, View ORCID ProfileCliment Nadeu
doi: https://doi.org/10.1101/2022.01.20.477141
Ludwig Houegnigan
1TALP Research Center and Signal Theory and Communications Department, Polytechnic University of Catalonia, Barcelona, Spain
6Intelligent Data Science and Artificial Intelligence Research Center (IDEAI), Polytechnic University of Catalonia, Barcelona, Spain
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  • For correspondence: ludwig.houegnigan@upc.edu
Enrique Romero Merino
4Soft Computing Research Group, Computer Science Department, Polytechnic University of Catalonia, Barcelona, Spain
6Intelligent Data Science and Artificial Intelligence Research Center (IDEAI), Polytechnic University of Catalonia, Barcelona, Spain
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Els Vermeulen
3University of Pretoria Mammal Research Institute (MRI), Whale Unit, Pretoria, South Africa
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  • ORCID record for Els Vermeulen
Jessica Block
2California Institute for Telecommunications and Information Technology, University of California, San Diego, USA
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Pooyan Safari
7Fraunhofer Institute HHI, Berlin, Germany
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Francesc Moreno-Noguer
5IRI, Polytechnic University of Catalonia and CSIC, Barcelona, Spain
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  • ORCID record for Francesc Moreno-Noguer
Climent Nadeu
1TALP Research Center and Signal Theory and Communications Department, Polytechnic University of Catalonia, Barcelona, Spain
6Intelligent Data Science and Artificial Intelligence Research Center (IDEAI), Polytechnic University of Catalonia, Barcelona, Spain
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Abstract

The Wildlife and Marine Mammal Spatial Observatory is a joint research effort for the census of wildlife and particularly of marine mammals in satellite imagery. In that context, this paper illustrates the development of a high accuracy algorithm for the detection of right whales in sub-meter resolution multispectral satellite imagery with the constraint of a relatively small sample support of 580 southern right whale images. A significant space is devoted to exploratory data analysis to describe the statistical structure of right whale pixels and ocean surface pixels across multispectral bands.

Observations of southern right whale in satellite imagery are divided into typical and atypical right whale forms and the first observations of right whale mother and calf pairs in satellite imagery are presented. Measurements of whales are furthermore automatically extracted from whale observations (major axis length, minor axis length, etc). A significant space is also devoted to statistical data exploration, a step frequently overlooked in machine learning solutions, that yet offers interesting insight into the structure of animal detection in satellite imagery. The extracted statistics can readily be used by researchers to develop detection solutions even with low sample support. The adopted solution for detection consists of feature extraction with a convolutional neural network followed by classification with a support vector machine. 20 different convolutional neural networks were tested for feature extraction. Biostatistics parameters (accuracy, sensitivity, specificity and precision) were measured for comparison. Most architectures generally achieved high performance with low false positive and false negative rates. 100% accuracy is achieved in the case of 2 convolutional neural networks, Nasnet Large and Inception V3, and only with a specific selection of multispectral bands.

NB: This is a preprint that does not include satellite imagery due recent reviews

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted January 22, 2022.
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Wildlife and Marine Mammal Spatial Observatory: Observation and automated detection of Southern Right Whales in multispectral satellite imagery
Ludwig Houegnigan, Enrique Romero Merino, Els Vermeulen, Jessica Block, Pooyan Safari, Francesc Moreno-Noguer, Climent Nadeu
bioRxiv 2022.01.20.477141; doi: https://doi.org/10.1101/2022.01.20.477141
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Wildlife and Marine Mammal Spatial Observatory: Observation and automated detection of Southern Right Whales in multispectral satellite imagery
Ludwig Houegnigan, Enrique Romero Merino, Els Vermeulen, Jessica Block, Pooyan Safari, Francesc Moreno-Noguer, Climent Nadeu
bioRxiv 2022.01.20.477141; doi: https://doi.org/10.1101/2022.01.20.477141

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