UZH-Logo

Maintenance Infos

A preliminary assessment of using conservation drones for Sumatran orang-utan (Pongo abelii) distribution and density


Wich, Serge; Dellatore, David; Houghton, Max; Ardi, Rio; Koh, Lian Pin (2016). A preliminary assessment of using conservation drones for Sumatran orang-utan (Pongo abelii) distribution and density. Journal of Unmanned Vehicle Systems, 4(1):45-52.

Abstract

To conserve biodiversity, scientists monitor wildlife populations and their habitats. Current methods have constraints, such as the costs of ground or aerial surveys, limited resolution of freely available satellite images, and expensive high-resolution satellite images. Recently researchers started to use unmanned aerial vehicles (UAVs or drones) for wildlife and habitat monitoring. Here we tested whether we could detect nests of the critically endangered Sumatran orang-utan on imagery acquired from a camera-mounted drone to determine distribution and density. Our results show that the distribution of nests compares well between aerial and ground-based surveys and that relative density (nest/km) shows a significant correlation between these two survey types. The results also indicate that both methods can be used to detect significant differences in relative density between previously degraded reforested and enriched areas. We conclude that orang-utan nest surveys from drones are a promising survey method to determine distribution and (relative) density of Sumatran orang-utans and perhaps other ape species.

To conserve biodiversity, scientists monitor wildlife populations and their habitats. Current methods have constraints, such as the costs of ground or aerial surveys, limited resolution of freely available satellite images, and expensive high-resolution satellite images. Recently researchers started to use unmanned aerial vehicles (UAVs or drones) for wildlife and habitat monitoring. Here we tested whether we could detect nests of the critically endangered Sumatran orang-utan on imagery acquired from a camera-mounted drone to determine distribution and density. Our results show that the distribution of nests compares well between aerial and ground-based surveys and that relative density (nest/km) shows a significant correlation between these two survey types. The results also indicate that both methods can be used to detect significant differences in relative density between previously degraded reforested and enriched areas. We conclude that orang-utan nest surveys from drones are a promising survey method to determine distribution and (relative) density of Sumatran orang-utans and perhaps other ape species.

Altmetrics

Downloads

33 downloads since deposited on 01 Feb 2016
33 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, not refereed, original work
Communities & Collections:07 Faculty of Science > Department of Anthropology
Dewey Decimal Classification:300 Social sciences, sociology & anthropology
Language:English
Date:2016
Deposited On:01 Feb 2016 16:56
Last Modified:05 Apr 2016 19:59
Publisher:N R C Research Press
ISSN:2291-3467
Publisher DOI:https://doi.org/10.1139/juvs-2015-0015
Permanent URL: https://doi.org/10.5167/uzh-120514

Download

[img]
Preview
Content: Accepted Version
Filetype: PDF
Size: 1MB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations