Title of article
Assessing and modeling moose (Alces alces) habitats with airborne laser scanning data
Author/Authors
Melin، نويسنده , , M. and Packalén، نويسنده , , P. and Matala، نويسنده , , J. and Mehtنtalo، نويسنده , , L. and Pusenius، نويسنده , , J.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2013
Pages
8
From page
389
To page
396
Abstract
In the analysis of forest resources, the use of ALS (airborne laser scanning) enables detailed three dimensional (3D) descriptions of forests and their vegetation. Simultaneously, ecologists have recognized that 3D information on vegetation is highly important in analyzing the habitat suitability of a given site. Recently, animals’ habitat preferences have been analyzed, for example, with GPS-collared animals. This has resulted in detailed knowledge about the animals’ movements both spatially and temporally. This study combines 3D information on vegetation obtained from ALS data with information about animal locations from GPS data. The aim was to map and analyze the habitat preferences of moose. The study area was located on the west coast of Finland. The data consisted of 18 GPS-collared moose (monitored from 2009 to 2010) and ALS data collected in 2010. We investigated how habitat structure changes as a function of distance to observed moose locations and how observed moose locations differ from randomly selected locations in terms of 3D structure. We also created a model-based habitat suitability map and tested it against moose occurrences. The results suggested that there are clear differences between the areas occupied and not occupied by moose and that these differences can be detected from ALS data. More importantly, ALS proved its potential in linking 3D descriptions of vegetation directly to observed moose locations without any proxy variables. These observations strongly support future studies.
Keywords
habitat analysis , Moose , GPS-tracking , ALS
Journal title
International Journal of Applied Earth Observation and Geoinformation
Serial Year
2013
Journal title
International Journal of Applied Earth Observation and Geoinformation
Record number
2379371
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