DOI: 10.1016/j.jag.2013.11.015
Scopus记录号: 2-s2.0-84897400486
论文题名: Using multiple Landsat scenes in an ensemble classifier reduces classification error in a stable nearshore environment
作者: Knudby A ; , Nordlund L ; M ; , Palmqvist G ; , Wikström K ; , Koliji A ; , Lindborg R ; , Gullström M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 28, 期: 1 起始页码: 90
结束页码: 101
语种: 英语
英文关键词: Classification
; Ensemble classifier
; Landsat
; Nearshore
; Random forest
; Remote sensing
Scopus关键词: classification
; ensemble forecasting
; land cover
; Landsat
; nearshore environment
; remote sensing
; Tanzania
; Zanzibar Island
英文摘要: Medium-scale land cover maps are traditionally created on the basis of a single cloud-free satellite scene, leaving information present in other scenes unused. Using 1309 field observations and 20 cloud- and error-affected Landsat scenes covering Zanzibar Island, this study demonstrates that the use of multiple scenes can both allow complete coverage of the study area in the absence of cloud-free scenes and obtain substantially improved classification accuracy. Automated processing of individual scenes includes derivation of spectral features for use in classification, identification of clouds, shadows and the land/water boundary, and random forest-based land cover classification. An ensemble classifier is then created from the single-scene classifications by voting. The accuracy achieved by the ensemble classifier is 70.4%, compared to an average of 62.9% for the individual scenes, and the ensemble classifier achieves complete coverage of the study area while the maximum coverage for a single scene is 1209 of the 1309 field sites. Given the free availability of Landsat data, these results should encourage increased use of multiple scenes in land cover classification and reduced reliance on the traditional single-scene methodology. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79654
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geography, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A1S6, Canada; Western Indian Ocean - Community, Awareness, Research and Environment (WIO CARE), P.O. Box 4199, Zanzibar, Tanzania; Department of Ecology, Environment and Plant Sciences, Stockholm University, S-106 91 Stockholm, Sweden; Department of Physical Geography and Quaternary Geology, Stockholm University, SE-106 91 Stockholm, Sweden
Recommended Citation:
Knudby A,, Nordlund L,M,et al. Using multiple Landsat scenes in an ensemble classifier reduces classification error in a stable nearshore environment[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,28(1)