Quantifying damage from wild pigs with small unmanned aerial systems
ABSTRACT Wild pig (Sus scrofa) population expansion and associated damage to crops, wildlife, and the environment is a growing concern in the United States. The destructive rooting behavior of wild pigs indicates where they have foraged and their general presence on the landscape. We used aerial ima...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-06-01
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| Series: | Wildlife Society Bulletin |
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| Online Access: | https://doi.org/10.1002/wsb.868 |
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| author | Sathishkumar Samiappan Joby M. Prince Czarnecki Hearne Foster Bronson K. Strickland Jessica L. Tegt Robert J. Moorhead |
| author_facet | Sathishkumar Samiappan Joby M. Prince Czarnecki Hearne Foster Bronson K. Strickland Jessica L. Tegt Robert J. Moorhead |
| author_sort | Sathishkumar Samiappan |
| collection | DOAJ |
| description | ABSTRACT Wild pig (Sus scrofa) population expansion and associated damage to crops, wildlife, and the environment is a growing concern in the United States. The destructive rooting behavior of wild pigs indicates where they have foraged and their general presence on the landscape. We used aerial imagery with a small unmanned aerial system to assess damage of corn (Zea mays) fields by wild pigs in the Mississippi Alluvial Valley of Mississippi, USA, during the 2016 growing season. Images were automatically classified using segmentation‐based fractal texture analysis and support vector machines. We assessed the accuracy of automated classification with 5,400 Global Positioning System ground reference points collected in the fields. Classification accuracies for identification of damaged and nondamaged areas were between 65% and 78%. In general, automated classification underestimated the area of damage present within fields. Kappa values ranged from 0.26 to 0.51, on a scale of 0.0–1.0. Small unmanned aerial systems overcome limitations of existing methods because they can survey an entire field rapidly and without significant field labor. © 2018 The Wildlife Society. |
| format | Article |
| id | doaj-art-e64be9b35ba245bf8617c23ee02749a1 |
| institution | DOAJ |
| issn | 2328-5540 |
| language | English |
| publishDate | 2018-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Wildlife Society Bulletin |
| spelling | doaj-art-e64be9b35ba245bf8617c23ee02749a12025-08-20T02:49:22ZengWileyWildlife Society Bulletin2328-55402018-06-0142230430910.1002/wsb.868Quantifying damage from wild pigs with small unmanned aerial systemsSathishkumar Samiappan0Joby M. Prince Czarnecki1Hearne Foster2Bronson K. Strickland3Jessica L. Tegt4Robert J. Moorhead5Geosystems Research InstituteMississippi State UniversityBox 9627Mississippi StateMS39762USAGeosystems Research InstituteMississippi State UniversityBox 9627Mississippi StateMS39762USADepartment of Wildlife, Fisheries, and AquacultureMississippi State UniversityBox 9609Mississippi StateMS39762USADepartment of Wildlife, Fisheries, and AquacultureMississippi State UniversityBox 9609Mississippi StateMS39762USADepartment of Wildlife, Fisheries, and AquacultureMississippi State UniversityBox 9609Mississippi StateMS39762USAGeosystems Research InstituteMississippi State UniversityBox 9627Mississippi StateMS39762USAABSTRACT Wild pig (Sus scrofa) population expansion and associated damage to crops, wildlife, and the environment is a growing concern in the United States. The destructive rooting behavior of wild pigs indicates where they have foraged and their general presence on the landscape. We used aerial imagery with a small unmanned aerial system to assess damage of corn (Zea mays) fields by wild pigs in the Mississippi Alluvial Valley of Mississippi, USA, during the 2016 growing season. Images were automatically classified using segmentation‐based fractal texture analysis and support vector machines. We assessed the accuracy of automated classification with 5,400 Global Positioning System ground reference points collected in the fields. Classification accuracies for identification of damaged and nondamaged areas were between 65% and 78%. In general, automated classification underestimated the area of damage present within fields. Kappa values ranged from 0.26 to 0.51, on a scale of 0.0–1.0. Small unmanned aerial systems overcome limitations of existing methods because they can survey an entire field rapidly and without significant field labor. © 2018 The Wildlife Society.https://doi.org/10.1002/wsb.868corndamage assessmenthuman–wildlife conflictMississippismall unmanned aerial systemsSus scrofa |
| spellingShingle | Sathishkumar Samiappan Joby M. Prince Czarnecki Hearne Foster Bronson K. Strickland Jessica L. Tegt Robert J. Moorhead Quantifying damage from wild pigs with small unmanned aerial systems Wildlife Society Bulletin corn damage assessment human–wildlife conflict Mississippi small unmanned aerial systems Sus scrofa |
| title | Quantifying damage from wild pigs with small unmanned aerial systems |
| title_full | Quantifying damage from wild pigs with small unmanned aerial systems |
| title_fullStr | Quantifying damage from wild pigs with small unmanned aerial systems |
| title_full_unstemmed | Quantifying damage from wild pigs with small unmanned aerial systems |
| title_short | Quantifying damage from wild pigs with small unmanned aerial systems |
| title_sort | quantifying damage from wild pigs with small unmanned aerial systems |
| topic | corn damage assessment human–wildlife conflict Mississippi small unmanned aerial systems Sus scrofa |
| url | https://doi.org/10.1002/wsb.868 |
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