DOI: 10.1016/j.jag.2013.12.016
Scopus记录号: 2-s2.0-84897556679
论文题名: A bootstrap method for assessing classification accuracy and confidence for agricultural land use mapping in Canada
作者: Champagne C ; , McNairn H ; , Daneshfar B ; , Shang J
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 29, 期: 1 起始页码: 44
结束页码: 52
语种: 英语
Scopus关键词: accuracy assessment
; agricultural land
; bootstrapping
; image classification
; land use change
; mapping
; remote sensing
; Canada
英文摘要: Land cover and land use classifications from remote sensing are increasingly becoming institutionalized framework data sets for monitoring environmental change. As such, the need for robust statements of classification accuracy is critical. This paper describes a method to estimate confidence in classification model accuracy using a bootstrap approach. Using this method, it was found that classification accuracy and confidence, while closely related, can be used in complementary ways to provide additional information on map accuracy and define groups of classes and to inform the future reference sampling strategies. Overall classification accuracy increases with an increase in the number of fields surveyed, where the width of classification confidence bounds decreases. Individual class accuracies and confidence were non-linearly related to the number of fields surveyed. Results indicate that some classes can be estimated accurately and confidently with fewer numbers of samples, whereas others require larger reference data sets to achieve satisfactory results. This approach is an improvement over other approaches for estimating class accuracy and confidence as it uses repetitive sampling to produce a more realistic estimate of the range in classification accuracy and confidence that can be obtained with different reference data inputs. © 2014 Published by Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79618
Appears in Collections: 气候变化事实与影响
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作者单位: Science and Technology Branch, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON K1A-0C6, Canada
Recommended Citation:
Champagne C,, McNairn H,, Daneshfar B,et al. A bootstrap method for assessing classification accuracy and confidence for agricultural land use mapping in Canada[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,29(1)