气候变化领域集成服务门户(CCPortal): Investigating spatial error structures in continuous raster data

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DOI	10.1016/j.jag.2018.09.020
	Investigating spatial error structures in continuous raster data
	Tsutsumida N.; Rodríguez-Veiga P.; Harris P.; Balzter H.; Comber A.
发表日期	2019
ISSN	15698432
起始页码	259
结束页码	268
卷号	74
英文摘要	The objective of this study is to investigate spatial structures of error in the assessment of continuous raster data. The use of conventional diagnostics of error often overlooks the possible spatial variation in error because such diagnostics report only average error or deviation between predicted and reference values. In this respect, this work uses a moving window (kernel) approach to generate geographically weighted (GW) versions of the mean signed deviation, the mean absolute error and the root mean squared error and to quantify their spatial variations. Such approach computes local error diagnostics from data weighted by its distance to the centre of a moving kernel and allows to map spatial surfaces of each type of error. In addition, a GW correlation analysis between predicted and reference values provides an alternative view of local error. These diagnostics are applied to two earth observation case studies. The results reveal important spatial structures of error and unusual clusters of error can be identified through Monte Carlo permutation tests. The first case study demonstrates the use of GW diagnostics to fractional impervious surface area datasets generated by four different models for the Jakarta metropolitan area, Indonesia. The GW diagnostics reveal where the models perform differently and similarly, and found areas of under-prediction in the urban core, with larger errors in peri-urban areas. The second case study uses the GW diagnostics to four remotely sensed aboveground biomass datasets for the Yucatan Peninsula, Mexico. The mapping of GW diagnostics provides a means to compare the accuracy of these four continuous raster datasets locally. The discussion considers the relative nature of diagnostics of error, determining moving window size and issues around the interpretation of different error diagnostic measures. Investigating spatial structures of error hidden in conventional diagnostics of error provides informative descriptions of error in continuous raster data. © 2018 The Authors
英文关键词	Error distribution; Local error diagnostics; Spatial accuracy; Spatial heterogeneity
语种	英语
scopus关键词	accuracy assessment; error analysis; heterogeneity; Monte Carlo analysis; periurban area; raster; remote sensing; spatial analysis; spatial variation; Indonesia; Jakarta; Mexico [North America]; Yucatan Peninsula
来源期刊	International Journal of Applied Earth Observation and Geoinformation
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156563
作者单位	Graduate School of Global Environmental Studies, Kyoto University, Kyoto, 606-8501, Japan; Centre for Landscape and Climate Research, University of Leicester, Leicester, LE1 7RH, United Kingdom; NERC National Centre for Earth Observation (NCEO), University of Leicester, Leicester, LE1 7RH, United Kingdom; Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton, EX20 2SB, United Kingdom; School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom
推荐引用方式 GB/T 7714	Tsutsumida N.,Rodríguez-Veiga P.,Harris P.,et al. Investigating spatial error structures in continuous raster data[J],2019,74.
APA	Tsutsumida N.,Rodríguez-Veiga P.,Harris P.,Balzter H.,&Comber A..(2019).Investigating spatial error structures in continuous raster data.International Journal of Applied Earth Observation and Geoinformation,74.
MLA	Tsutsumida N.,et al."Investigating spatial error structures in continuous raster data".International Journal of Applied Earth Observation and Geoinformation 74(2019).