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TitleTime series analysis of long-term terrestrial water storage over Canada from GRACE satellites using principal component analysis
AuthorLi, J; Wang, S; Zhou, F
SourceCanadian Journal of Remote Sensing vol. 42, issue 3, 2016 p. 161-170, https://doi.org/10.1080/07038992.2016.1166042
Year2016
Alt SeriesEarth Sciences Sector, Contribution Series 20150390
PublisherTaylor and Francis
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
ProvinceBritish Columbia; Alberta; Saskatchewan; Manitoba; Ontario; Quebec; New Brunswick; Nova Scotia; Prince Edward Island; Newfoundland and Labrador; Northwest Territories; Yukon; Nunavut
NTS1; 2; 3; 10; 11; 12; 13; 14; 15; 16; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 52; 53; 54; 55; 56; 57; 58; 59; 62; 63; 64; 65; 66; 67; 68; 69; 72; 73; 74; 75; 76; 77; 78; 79; 82; 83; 84; 85; 86; 87; 88; 89; 92; 93; 94; 95; 96; 97; 98; 99; 102; 103; 104; 105; 106; 107; 114O; 114P; 115; 116; 117; 120; 340; 560
Subjectshydrogeology; remote sensing; satellite geodesy; water exploration; underground waters; surface waters; GRACE satellites; principal component analysis (PCA); terrestrial water storage (TWS)
Illustrationssatellite images; formulae; tables; graphs
ProgramInformation Extraction Procedures for Landmass Monitoring, Remote Sensing Science
AbstractPrincipal component analysis (PCA) is a statistical technique widely used in remote sensing, yet few studies have addressed the physical meaning of component images. This study analysed the long-term (2003-2013) time series dataset of monthly terrestrial water storage (TWS) over Canada from the Gravity Recovery and Climate Experiment (GRACE) mission using PCA. The principal components were physically explained through establishing the mathematical relationship between the pixel values of a component image and the correlation coefficients between the original data and the loadings of the component image. It is found that the first component of the data represented the long-term TWS trend over the study period. The second component represented the monthly variation of TWS. The third and the forth components reflected the spatial and temporal anomalies of TWS. The first component contained 49.3% of the TWS variance. The first four components explained a total of 87.1% of the data variance. The TWS changes captured by the PCA were largely contributed by the changes in precipitation over Canada. This study provides an approach for physically interpreting the principal components and their loadings in PCA.
Summary(Plain Language Summary, not published)
The study characterize changes in terrestrial water storage (TWS) over Canada from the Gravity Recovery and Climate Experiment (GRACE) mission using principal component analysis (PCA). PCA essentially consists of choosing uncorrelated linear combinations of multiple image bands in such a way that each successively extracted linear combination, called a principal component, has a decreasing variance. It is found that the first component of the data represented the long-term TWS trend over the study period. The second component represented the monthly variation of TWS. The third and the forth components reflected the spatial and temporal anomalies of TWS. The TWS changes captured by the PCA were largely contributed by the changes in precipitation over Canada. This study provides an approach for physically interpreting the principal components and their loadings in PCA.
GEOSCAN ID297505