Matches in SemOpenAlex for { <https://semopenalex.org/work/W2155840753> ?p ?o ?g. }
- W2155840753 endingPage "218" @default.
- W2155840753 startingPage "203" @default.
- W2155840753 abstract "Abstract While data like HJ-1 CCD images have advantageous spatial characteristics for describing crop properties, the temporal resolution of the data is rather low, which can be easily made worse by cloud contamination. In contrast, although Moderate Resolution Imaging Spectroradiometer (MODIS) can only achieve a spatial resolution of 250 m in its normalised difference vegetation index (NDVI) product, it has a high temporal resolution, covering the Earth up to multiple times per day. To combine the high spatial resolution and high temporal resolution of different data sources, a new method (Spatial and Temporal Adaptive Vegetation index Fusion Model [STAVFM]) for blending NDVI of different spatial and temporal resolutions to produce high spatial–temporal resolution NDVI datasets was developed based on Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). STAVFM defines a time window according to the temporal variation of crops, takes crop phenophase into consideration and improves the temporal weighting algorithm. The result showed that the new method can combine the temporal information of MODIS NDVI and spatial difference information of HJ-1 CCD NDVI to generate an NDVI dataset with both high spatial and high temporal resolution. An application of the generated NDVI dataset in crop biomass estimation was provided. An average absolute error of 17.2% was achieved. The estimated winter wheat biomass correlated well with observed biomass (R 2 of 0.876). We conclude that the new dataset will improve the application of crop biomass estimation by describing the crop biomass accumulation in detail. There is potential to apply the approach in many other studies, including crop production estimation, crop growth monitoring and agricultural ecosystem carbon cycle research, which will contribute to the implementation of Digital Earth by describing land surface processes in detail." @default.
- W2155840753 created "2016-06-24" @default.
- W2155840753 creator A5009757097 @default.
- W2155840753 creator A5010666672 @default.
- W2155840753 creator A5040636728 @default.
- W2155840753 date "2013-05-01" @default.
- W2155840753 modified "2023-10-02" @default.
- W2155840753 title "Generation of high spatial and temporal resolution NDVI and its application in crop biomass estimation" @default.
- W2155840753 cites W1974047452 @default.
- W2155840753 cites W1974180061 @default.
- W2155840753 cites W2006563460 @default.
- W2155840753 cites W2027776168 @default.
- W2155840753 cites W2029058476 @default.
- W2155840753 cites W2049476189 @default.
- W2155840753 cites W2056447651 @default.
- W2155840753 cites W2056811372 @default.
- W2155840753 cites W2064875349 @default.
- W2155840753 cites W2072113769 @default.
- W2155840753 cites W2079594423 @default.
- W2155840753 cites W2081399384 @default.
- W2155840753 cites W2082199675 @default.
- W2155840753 cites W2082286381 @default.
- W2155840753 cites W2104588681 @default.
- W2155840753 cites W2105339868 @default.
- W2155840753 cites W2119513445 @default.
- W2155840753 cites W2125763679 @default.
- W2155840753 cites W2130564827 @default.
- W2155840753 cites W2154700052 @default.
- W2155840753 cites W2161245744 @default.
- W2155840753 cites W2161887011 @default.
- W2155840753 cites W2738243764 @default.
- W2155840753 doi "https://doi.org/10.1080/17538947.2011.623189" @default.
- W2155840753 hasPublicationYear "2013" @default.
- W2155840753 type Work @default.
- W2155840753 sameAs 2155840753 @default.
- W2155840753 citedByCount "84" @default.
- W2155840753 countsByYear W21558407532012 @default.
- W2155840753 countsByYear W21558407532013 @default.
- W2155840753 countsByYear W21558407532014 @default.
- W2155840753 countsByYear W21558407532015 @default.
- W2155840753 countsByYear W21558407532016 @default.
- W2155840753 countsByYear W21558407532017 @default.
- W2155840753 countsByYear W21558407532018 @default.
- W2155840753 countsByYear W21558407532019 @default.
- W2155840753 countsByYear W21558407532020 @default.
- W2155840753 countsByYear W21558407532021 @default.
- W2155840753 countsByYear W21558407532022 @default.
- W2155840753 countsByYear W21558407532023 @default.
- W2155840753 crossrefType "journal-article" @default.
- W2155840753 hasAuthorship W2155840753A5009757097 @default.
- W2155840753 hasAuthorship W2155840753A5010666672 @default.
- W2155840753 hasAuthorship W2155840753A5040636728 @default.
- W2155840753 hasConcept C105795698 @default.
- W2155840753 hasConcept C111368507 @default.
- W2155840753 hasConcept C115540264 @default.
- W2155840753 hasConcept C119666444 @default.
- W2155840753 hasConcept C121332964 @default.
- W2155840753 hasConcept C127313418 @default.
- W2155840753 hasConcept C127413603 @default.
- W2155840753 hasConcept C142724271 @default.
- W2155840753 hasConcept C146978453 @default.
- W2155840753 hasConcept C1549246 @default.
- W2155840753 hasConcept C154945302 @default.
- W2155840753 hasConcept C19269812 @default.
- W2155840753 hasConcept C205372480 @default.
- W2155840753 hasConcept C205649164 @default.
- W2155840753 hasConcept C25989453 @default.
- W2155840753 hasConcept C2776133958 @default.
- W2155840753 hasConcept C2777007095 @default.
- W2155840753 hasConcept C33923547 @default.
- W2155840753 hasConcept C33954974 @default.
- W2155840753 hasConcept C39432304 @default.
- W2155840753 hasConcept C41008148 @default.
- W2155840753 hasConcept C62520636 @default.
- W2155840753 hasConcept C62649853 @default.
- W2155840753 hasConcept C6557445 @default.
- W2155840753 hasConcept C71924100 @default.
- W2155840753 hasConcept C86803240 @default.
- W2155840753 hasConcept C94747663 @default.
- W2155840753 hasConceptScore W2155840753C105795698 @default.
- W2155840753 hasConceptScore W2155840753C111368507 @default.
- W2155840753 hasConceptScore W2155840753C115540264 @default.
- W2155840753 hasConceptScore W2155840753C119666444 @default.
- W2155840753 hasConceptScore W2155840753C121332964 @default.
- W2155840753 hasConceptScore W2155840753C127313418 @default.
- W2155840753 hasConceptScore W2155840753C127413603 @default.
- W2155840753 hasConceptScore W2155840753C142724271 @default.
- W2155840753 hasConceptScore W2155840753C146978453 @default.
- W2155840753 hasConceptScore W2155840753C1549246 @default.
- W2155840753 hasConceptScore W2155840753C154945302 @default.
- W2155840753 hasConceptScore W2155840753C19269812 @default.
- W2155840753 hasConceptScore W2155840753C205372480 @default.
- W2155840753 hasConceptScore W2155840753C205649164 @default.
- W2155840753 hasConceptScore W2155840753C25989453 @default.
- W2155840753 hasConceptScore W2155840753C2776133958 @default.
- W2155840753 hasConceptScore W2155840753C2777007095 @default.
- W2155840753 hasConceptScore W2155840753C33923547 @default.
- W2155840753 hasConceptScore W2155840753C33954974 @default.