DOI: 10.1016/j.jag.2013.11.009
Scopus记录号: 2-s2.0-84897470278
论文题名: Area-based and location-based validation of classified image objects
作者: Whiteside T ; G ; , Maier S ; W ; , Boggs G ; S
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 28, 期: 1 起始页码: 117
结束页码: 130
语种: 英语
英文关键词: Accuracy assessment
; Geographic object-based image analysis
; Validation
Scopus关键词: accuracy assessment
; classification
; geometry
; GIS
; image analysis
; model validation
; numerical model
; spatial analysis
英文摘要: Geographic object-based image analysis (GEOBIA) produces results that have both thematic and geometric properties. Classified objects not only belong to particular classes but also have spatial properties such as location and shape. Therefore, any accuracy assessment where quantification of area is required must (but often does not) take into account both thematic and geometric properties of the classified objects. By using location-based and area-based measures to compare classified objects to corresponding reference objects, accuracy information for both thematic and geometric assessment is available. Our methods provide location-based and area-based measures with application to both a single-class feature detection and a multi-class object-based land cover analysis. In each case the classification was compared to a GIS layer of associated reference data using randomly selected sample areas. Error is able to be pin-pointed spatially on per-object, per class and per-sample area bases although there is no indication whether the errors exist in the classification product or the reference data. This work showcases the utility of the methods for assessing the accuracy of GEOBIA derived classifications provided the reference data is accurate and of comparable scale. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79650
Appears in Collections: 气候变化事实与影响
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作者单位: Environmental Research Institute of the Supervising Scientist, Darwin, NT 0820, Australia; Research Institute of the Environment and Livelihoods, Charles Darwin University, Darwin, NT 0909, Australia; Wheatbelt NRM Inc, P.O. Box 311, Northam, WA 6401, Australia
Recommended Citation:
Whiteside T,G,, Maier S,et al. Area-based and location-based validation of classified image objects[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,28(1)