Species’ habitat use inferred from environmental variables at multiple scales: How much we gain from high-resolution vegetation data?
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- 作者：Aitor Gastó ; na ; Carlos Ciudada ; carlos.ciudad@upm.es" class="auth_mail" title="E-mail the corresponding author ; Marí ; a C. Mateo-Sá ; ncheza ; Juan I. Garcí ; a-Viñ ; asa ; Cé ; sar Ló ; pez-Leivaa ; Alfredo Ferná ; ndez-Landab ; Miguel Marchamaloc ; Jorge Cuevasa ; Begoñ ; a de la Fuentea ; d ; Marie-José ; e Fortine ; Santiago Sauraa
- 关键词：Habitat selection ; Multi-scale habitat modelling ; High-resolution data ; LiDAR ; Remote sensing ; Brown bear
- 刊名：International Journal of Applied Earth Observation and Geoinformation
- 出版年：2017
- 出版时间：March 2017
- 年：2017
- 卷：55
- 期：Complete
- 页码：1-8
- 全文大小：1310 K
文摘
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Habitat models for bears were developed using different spatial resolution data.
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We compared vegetation data from CORINE, forest map at 1:50,000 scale and LiDAR.
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Resolution affects spatial scale at which bear is estimated to perceive landscape.
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Reliability of coarse-resolution models depends on indirect non-vegetation factors.
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Model performance and credibility increases with resolution and is best with LiDAR.