FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2017657457> ?p ?o ?g. }

• W2017657457 endingPage "3353" @default.
• W2017657457 startingPage "3340" @default.
• W2017657457 abstract "With the advent of free Landsat data stretching back decades, there has been a surge of interest in utilizing remotely sensed data in multitemporal analysis for estimation of biophysical parameters. Such analysis is confounded by cloud cover and other image-specific problems, which result in missing data at various aperiodic times of the year. While there is a wealth of information contained in remotely sensed time series, the analysis of such time series is severely limited due to the missing data. This paper illustrates a technique which can greatly expand the possibilities of such analyses, a Fourier regression algorithm, here on time series of normalized difference vegetation indices (NDVIs) for Landsat pixels with 30-m resolution. It compares the results with those using the spatial and temporal adaptive reflectance fusion model (STAR-FM), a popular approach that depends on having MODIS pixels with resolutions of 250 m or coarser. STAR-FM uses changes in the MODIS pixels as a template for predicting changes in the Landsat pixels. Fourier regression had an <i xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>R</i> <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> of at least 90% over three quarters of all pixels, and it had the highest <i xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>R</i> <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>Predicted</sub> <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> values (compared to STAR-FM) on two thirds of the pixels. The typical root-mean-square error for Fourier regression fitting was about 0.05 for NDVI, ranging from 0 to 1. This indicates that Fourier regression may be used to interpolate missing data for multitemporal analysis at the Landsat scale, especially for annual or longer studies." @default.
• W2017657457 created "2016-06-24" @default.
• W2017657457 creator A5022909470 @default.
• W2017657457 creator A5033989395 @default.
• W2017657457 creator A5065260963 @default.
• W2017657457 creator A5087114682 @default.
• W2017657457 date "2012-09-01" @default.
• W2017657457 modified "2023-10-16" @default.
• W2017657457 title "Fitting the Multitemporal Curve: A Fourier Series Approach to the Missing Data Problem in Remote Sensing Analysis" @default.
• W2017657457 cites W1963768209 @default.
• W2017657457 cites W1997149866 @default.
• W2017657457 cites W2032938835 @default.
• W2017657457 cites W2056811372 @default.
• W2017657457 cites W2057641906 @default.
• W2017657457 cites W2063623478 @default.
• W2017657457 cites W2069276699 @default.
• W2017657457 cites W2082201041 @default.
• W2017657457 cites W2085282193 @default.
• W2017657457 cites W2088603520 @default.
• W2017657457 cites W2095897558 @default.
• W2017657457 cites W2099650730 @default.
• W2017657457 cites W2151456308 @default.
• W2017657457 cites W2156842872 @default.
• W2017657457 cites W2156903587 @default.
• W2017657457 cites W2158744420 @default.
• W2017657457 cites W2162416391 @default.
• W2017657457 cites W2164943663 @default.
• W2017657457 cites W2170282805 @default.
• W2017657457 cites W4232345992 @default.
• W2017657457 doi "https://doi.org/10.1109/tgrs.2012.2183137" @default.
• W2017657457 hasPublicationYear "2012" @default.
• W2017657457 type Work @default.
• W2017657457 sameAs 2017657457 @default.
• W2017657457 citedByCount "102" @default.
• W2017657457 countsByYear W20176574572013 @default.
• W2017657457 countsByYear W20176574572014 @default.
• W2017657457 countsByYear W20176574572015 @default.
• W2017657457 countsByYear W20176574572016 @default.
• W2017657457 countsByYear W20176574572017 @default.
• W2017657457 countsByYear W20176574572018 @default.
• W2017657457 countsByYear W20176574572019 @default.
• W2017657457 countsByYear W20176574572020 @default.
• W2017657457 countsByYear W20176574572021 @default.
• W2017657457 countsByYear W20176574572022 @default.
• W2017657457 countsByYear W20176574572023 @default.
• W2017657457 crossrefType "journal-article" @default.
• W2017657457 hasAuthorship W2017657457A5022909470 @default.
• W2017657457 hasAuthorship W2017657457A5033989395 @default.
• W2017657457 hasAuthorship W2017657457A5065260963 @default.
• W2017657457 hasAuthorship W2017657457A5087114682 @default.
• W2017657457 hasConcept C111368507 @default.
• W2017657457 hasConcept C11413529 @default.
• W2017657457 hasConcept C119857082 @default.
• W2017657457 hasConcept C127313418 @default.
• W2017657457 hasConcept C132651083 @default.
• W2017657457 hasConcept C143724316 @default.
• W2017657457 hasConcept C151406439 @default.
• W2017657457 hasConcept C151730666 @default.
• W2017657457 hasConcept C1549246 @default.
• W2017657457 hasConcept C154945302 @default.
• W2017657457 hasConcept C160633673 @default.
• W2017657457 hasConcept C205372480 @default.
• W2017657457 hasConcept C41008148 @default.
• W2017657457 hasConcept C62649853 @default.
• W2017657457 hasConceptScore W2017657457C111368507 @default.
• W2017657457 hasConceptScore W2017657457C11413529 @default.
• W2017657457 hasConceptScore W2017657457C119857082 @default.
• W2017657457 hasConceptScore W2017657457C127313418 @default.
• W2017657457 hasConceptScore W2017657457C132651083 @default.
• W2017657457 hasConceptScore W2017657457C143724316 @default.
• W2017657457 hasConceptScore W2017657457C151406439 @default.
• W2017657457 hasConceptScore W2017657457C151730666 @default.
• W2017657457 hasConceptScore W2017657457C1549246 @default.
• W2017657457 hasConceptScore W2017657457C154945302 @default.
• W2017657457 hasConceptScore W2017657457C160633673 @default.
• W2017657457 hasConceptScore W2017657457C205372480 @default.
• W2017657457 hasConceptScore W2017657457C41008148 @default.
• W2017657457 hasConceptScore W2017657457C62649853 @default.
• W2017657457 hasIssue "9" @default.
• W2017657457 hasLocation W20176574571 @default.
• W2017657457 hasOpenAccess W2017657457 @default.
• W2017657457 hasPrimaryLocation W20176574571 @default.
• W2017657457 hasRelatedWork W1550175370 @default.
• W2017657457 hasRelatedWork W1990205660 @default.
• W2017657457 hasRelatedWork W2044092692 @default.
• W2017657457 hasRelatedWork W2119012848 @default.
• W2017657457 hasRelatedWork W2547665164 @default.
• W2017657457 hasRelatedWork W2803445926 @default.
• W2017657457 hasRelatedWork W3103111272 @default.
• W2017657457 hasRelatedWork W4289655544 @default.
• W2017657457 hasRelatedWork W4387331850 @default.
• W2017657457 hasRelatedWork W2622688551 @default.
• W2017657457 hasVolume "50" @default.
• W2017657457 isParatext "false" @default.
• W2017657457 isRetracted "false" @default.
• W2017657457 magId "2017657457" @default.
• W2017657457 workType "article" @default.