DOI: 10.1016/j.jag.2014.02.010
Scopus记录号: 2-s2.0-84902996631
论文题名: IRSeL-an approach to enhance continuity and accuracy of remotelysensed land cover data
作者: Rathjens H ; , Dörnhöfer K ; , Oppelt N
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 31, 期: 1 起始页码: 1
结束页码: 12
语种: 英语
英文关键词: Crop rotations
; Land use change
; Landsata
; Remote sensing
; Space-time interpolation
Scopus关键词: accuracy assessment
; agricultural land
; crop rotation
; data assimilation
; data set
; interpolation
; land cover
; land use change
; Landsat
; remote sensing
; spatiotemporal analysis
; Germany
英文摘要: Land cover data gives the opportunity to study interactions between land cover status and environmentalissues such as hydrologic processes, soil properties, or biodiversity. Land cover data often are based onclassification of remote sensing data that seldom provides the requisite accuracy, spatial availability andtemporal observational frequency for environmental studies. Thus, there is a high demand for accurateand spatio-temporal complete time series of land cover. In the past considerable research was undertakento increase land cover classification accuracy, while less effort was spent on interpolation techniques.The purpose of this article is to present a space-time interpolation and revision approach for remotelysensed land cover data. The approach leverages special properties known for agricultural areas such ascrop rotations or temporally static land cover classes. The newly developed IRSeL-tool (Interpolationand improvement of Remotely Sensed Land cover) corrects classification errors and interpolates missingland cover pixels. The easy-to-use tool solely requires an initial land cover data set. The IRSeL specificinterpolation and revision technique, the data input requirements and data output structure are describedin detail. A case study in an area around the city of Neumünster in Northern Germany from 2006 to 2012was performed for IRSeL validation with initial land cover data sets (Landsat TM image classifications)for the years 2006, 2007, 2009, 2010 and 2011. The results of the case study showed that IRSeL performswell; including years with no classification data overall accuracy values for IRSeL interpolated pixels rangefrom 0.63 to 0.81. IRSeL application significantly increases the accuracy of the land cover data; overallaccuracy values rise 0.08 in average resulting in overall accuracy values of at least 0.86. Consideringestimated reliabilities, the IRSeL tool provides a temporally and spatially completed and revised landcover data set that allows drawing conclusions for land cover related studies. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79761
Appears in Collections: 气候变化事实与影响
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作者单位: Kiel University, Department of Geography, Ludewig-Meyn-Str. 14, 24098 Kiel, Germany
Recommended Citation:
Rathjens H,, Dörnhöfer K,, Oppelt N. IRSeL-an approach to enhance continuity and accuracy of remotelysensed land cover data[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,31(1)