DOI: 10.1016/j.jag.2014.10.012
Scopus记录号: 2-s2.0-84926369197
论文题名: Using information layers for mapping grassland habitat distribution at local to regional scales
作者: Buck O ; , Millán V ; E ; , Klink A ; , Pakzad K
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 37 起始页码: 83
结束页码: 89
语种: 英语
英文关键词: Article 17 reporting
; Biodiversity monitoring
; Grassland
; Habitat directive
; Information layer
; Natura 2000
Scopus关键词: biodiversity
; environmental monitoring
; grassland
; habitat structure
; image classification
; mapping
; RapidEye
; remote sensing
; support vector machine
; Germany
; Schleswig-Holstein
英文摘要: The Natura 2000 network of protected sites is one of the means to enable biodiversity conservation in Europe. EU member states have to undertake surveillance of habitats and species of community interest protected under the Habitat Directive. Remote sensing techniques have been applied successfully to monitor biodiversity aspects according to Natura 2000, but many challenges remain in assessing dynamics and habitat changes outside protected sites. Grasslands are among the most threatened habitats in Europe. In this paper we tested the integration of expert knowledge into different standard classification approaches to map grassland habitats in Schleswig Holstein, Germany. Knowledge about habitat features is represented as raster information layers, and used in subsequent grassland classifications. Overall classification accuracies were highest for the maximum likelihood and support vector machine approaches using RapidEye time series, but results improved for specific grassland classes when information layers were included in the classification process. © 2014 Elsevier B.V.. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79550
Appears in Collections: 气候变化事实与影响
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作者单位: EFTAS GmbH, Oststrasse2-18, Münster, Germany
Recommended Citation:
Buck O,, Millán V,E,et al. Using information layers for mapping grassland habitat distribution at local to regional scales[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,37