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Drones count wildlife more accurately and precisely than humans
Author(s) -
Hodgson Jarrod C.,
Mott Rowan,
Baylis Shane M.,
Pham Trung T.,
Wotherspoon Simon,
Kilpatrick Adam D.,
Raja Segaran Ramesh,
Reid Ian,
Terauds Aleks,
Koh Lian Pin
Publication year - 2018
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12974
Subject(s) - wildlife , drone , replica , population , computer science , aerial survey , citizen science , seabird , scale (ratio) , data collection , remote sensing , environmental science , environmental resource management , geography , cartography , ecology , statistics , biology , mathematics , genetics , demography , botany , archaeology , sociology , predation
Knowing how many individuals are in a wildlife population allows informed management decisions to be made. Ecologists are increasingly using technologies, such as remotely piloted aircraft (RPA; commonly known as “drones,” unmanned aerial systems or unmanned aerial vehicles), for wildlife monitoring applications. Although RPA are widely touted as a cost‐effective way to collect high‐quality wildlife population data, the validity of these claims is unclear. Using life‐sized, replica seabird colonies containing a known number of fake birds, we assessed the accuracy of RPA‐facilitated wildlife population monitoring compared to the traditional ground‐based counting method. The task for both approaches was to count the number of fake birds in each of 10 replica seabird colonies. We show that RPA‐derived data are, on average, between 43% and 96% more accurate than the traditional ground‐based data collection method. We also demonstrate that counts from this remotely sensed imagery can be semi‐automated with a high degree of accuracy. The increased accuracy and increased precision of RPA‐derived wildlife monitoring data provides greater statistical power to detect fine‐scale population fluctuations allowing for more informed and proactive ecological management.