Reference : UAS imagery reveals new survey opportunities for counting hippos
Scientific journals : Article
Life sciences : Zoology
UAS imagery reveals new survey opportunities for counting hippos
[fr] L'imagerie drone révèle de nouvelles opportunités d'inventaire pour les populations d'hippopotames
Linchant, Julie mailto [Université de Liège - ULiège > > > Form. doct. sc. agro. & ingé. biol.]
Lhoest, Simon mailto [Université de Liège - ULiège > Ingénierie des biosystèmes (Biose) > Gestion des ressources forestières et des milieux naturels >]
Quevauvillers, Samuel mailto [Université de Liège - ULiège > Ingénierie des biosystèmes (Biose) > Gestion des ressources forestières et des milieux naturels >]
Lejeune, Philippe mailto [Université de Liège - ULiège > Ingénierie des biosystèmes (Biose) > Gestion des ressources forestières et des milieux naturels >]
Vermeulen, Cédric mailto [Université de Liège - ULiège > Ingénierie des biosystèmes (Biose) > Laboratoire de Foresterie des régions trop. et subtropicales >]
Semeki Ngabinzeke, Jean [> >]
Luse Belanganayi, Basile [> >]
Delvingt, Willy [> >]
Bouché, Philippe [> >]
Public Library of Science
Yes (verified by ORBi)
[en] UAS ; hippo ; inventory
[en] Introduction
The common hippopotamus Hippopotamus amphibius L. is a vulnerable species that
requires efficient methods to monitor its populations for conservation purposes. Rapid evolution
of civil drones provides new opportunities but survey protocols still need development.
This study aims to determine the optimal flight parameters for accurate population estimates.
A second objective is to evaluate the effects of three environmental factors: wind
speed, sun reflection and cloud cover.
We estimated the population of two main hippo schools (Dungu and Wilibadi II) located in
Garamba National Park in Democratic republic of Congo. Eight observers reviewed 252
photos taken over the Dungu school, representing a total of 2016 experimental units. A
detection rate and a level of certainty were associated with each experimental unit, and five
parameters were related to each count: flight height, three environmental parameters (sun
reflection on water surface, cloud cover, and wind speed), and observers’ experience.
Flight height reduced the observers’ confidence in their detection ability, rather than the
detection itself. For accurate counts of large groups an average height of 150 m was shown
to be a good compromise between animal detection without zooming in and the area covered
in one frame. Wind speed had little influence on the counts, but it affected the performance
of the UAS. Sun reflection reduced the detection rate of hippos and increased level
of certainty, while cloud cover reduced detection rates slightly. Therefore, we recommend flying when the sun is still low on the horizon and when there is little cloud, or when cloud
cover is light and even. This last point reinforces our recommendation for flights early in the
day. The counts also showed large differences between groups of inexperienced and experienced
observers. Experienced observers achieved better detection rates and were generally
more confident in their detection. Experienced observers detected 86.5% of the hippos
on average (confidence interval = ±0.76%). When applied to data from the second site, the
detection was 84.3% (confidence interval = ±1.84%). Two correction factors were then calculated,
as the inverse of the detection rate, based on the estimated number of hippos present
during one flight (Factor 1) or in the general population respectively (Factor 2). Factor 2
especially was consistent with previous studies using traditional aerial counts (1.22 vs 1.25).
Factor 2 was found to be appropriate for use by experienced observers. These results confirm
the use of correction factor 2 for hippo surveys, regardless of the study site, as it
accounts for hippo behavior. Optimum counting and cost efficiency were achieved with two
trained observers counting 7 pictures.
This study is a promising approach for routine surveys of the hippopotamus which is a species
usually ignored in wildlife counts. Drone technology is expected to improve rapidly;
therefore UAS could become a very useful and affordable survey tool for other species
requiring specific monitoring.
European Union under Grant Number DCI-ENV/2012/309- 143
Forests and Climate Change in the Congo Research Project, funded under the Letter of Agreement between the Center for International Forestry Research (CIFOR) and Gembloux Agro- Bio-Tech in University of Liège (ULg / GxABT)
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