DOI: 10.1016/j.jag.2014.09.018
Scopus记录号: 2-s2.0-84930410402
论文题名: Using ontological inference and hierarchical matchmaking toovercome semantic heterogeneity in remote sensing-basedbiodiversity monitoring
作者: Nieland S ; , Kleinschmit B ; , Förster M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 37 起始页码: 133
结束页码: 141
语种: 英语
英文关键词: Earth observation
; Interoperability
; Natura 2000
; Nature conservation
; Semantic reasoning
Scopus关键词: biodiversity
; biomonitoring
; EOS
; heterogeneity
; hierarchical system
; nature conservation
; remote sensing
; spatial data
; Belgium
; Germany
英文摘要: Ontology-based applications hold promise in improving spatial data interoperability. In this work we useremote sensing-based biodiversity information and apply semantic formalisation and ontological infer-ence to show improvements in data interoperability/comparability. The proposed methodology includesan observation-based, "bottom-up" engineering approach for remote sensing applications and gives apractical example of semantic mediation of geospatial products. We apply the methodology to threedifferent nomenclatures used for remote sensing-based classification of two heathland nature conserva-tion areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semanticformalisation and their bio-geographical differences. The results indicate that a hierarchical and trans-parent nomenclature is far more important for transferability than the sensor or study area. The inclusionof additional information, not necessarily belonging to a vegetation class description, is a key factor forthe future success of using semantics for interoperability in remote sensing. © 2014 Elsevier B.V.. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79598
Appears in Collections: 气候变化事实与影响
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作者单位: Geoinformation in Environmental Planning Lab, Technische Universität Berlin, Straße des 17. Juni 145, Berlin, Germany
Recommended Citation:
Nieland S,, Kleinschmit B,, Förster M. Using ontological inference and hierarchical matchmaking toovercome semantic heterogeneity in remote sensing-basedbiodiversity monitoring[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,37