Record Details

Spotting East African Mammals in Open Savannah from Space

MELSpace

View Archive Info
 
 
Field Value
 
Title Spotting East African Mammals in Open Savannah from Space
 
Creator Yang, Zheng
 
Contributor Wang, Tiejun
de Leeuw, Jan
Said, Mohammed
Freer, Jim
Skidmore, Andrew K.
 
Subject animal
informatics
baseline survey
 
Description Knowledge of population dynamics is essential for managing and conserving
wildlife. Traditional methods of counting wild animals such as aerial survey or
ground counts not only disturb animals, but also can be labour intensive and costly.
New, commercially available very high-resolution satellite images offer great
potential for accurate estimates of animal abundance over large open areas.
However, little research has been conducted in the area of satellite-aided wildlife
census, although computer processing speeds and image analysis algorithms have
vastly improved. This paper explores the possibility of detecting large animals in the
open savannah of Maasai Mara National Reserve, Kenya from very high-resolution
GeoEye-1 satellite images. A hybrid image classification method was employed for
this specific purpose by incorporating the advantages of both pixel-based and
object-based image classification approaches. This was performed in two steps:
firstly, a pixel-based image classification method, i.e., artificial neural network was
applied to classify potential targets with similar spectral reflectance at pixel level;
and then an object-based image classification method was used to further
differentiate animal targets from the surrounding landscapes through the
applications of expert knowledge. As a result, the large animals in two pilot study
areas were successfully detected with an average count error of 8.2%, omission
error of 6.6% and commission error of 13.7%. The results of the study show for the
first time that it is feasible to perform automated detection and counting of large wild
animals in open savannahs from space, and therefore provide a complementary
and alternative approach to the conventional wildlife survey techniques.
 
Date 2014-12-31
2017-01-10T18:20:09Z
2017-01-10T18:20:09Z
 
Type Journal Article
 
Identifier https://mel.cgiar.org/reporting/download/hash/1nCnCguN
Zheng Yang, Tiejun Wang, Jan de Leeuw, Mohammed Said, Jim Freer, Andrew K. Skidmore. (31/12/2014). Spotting East African Mammals in Open Savannah from Space. PloS one, 9 (12), pp. 1-16.
https://hdl.handle.net/20.500.11766/5474
Open access
 
Language en
 
Rights CC-BY-NC-4.0
 
Format PDF
 
Publisher Public Library of Science (PLOS ONE)
 
Source PloS one;9,(2014) Pagination 1,16