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Improving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency / Jiaqi Tian in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 29 - 44 Titre : Improving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency Type de document : Article/Communication Auteurs : Jiaqi Tian, Auteur ; Xiaolin Zhu, Auteur ; Jin Chen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 29 - 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Enhanced vegetation index [Termes IGN] filtrage du bruit [Termes IGN] image Terra-MODIS [Termes IGN] indice de végétation [Termes IGN] lissage de données [Termes IGN] nébulosité [Termes IGN] phénologie [Termes IGN] série temporelle Résumé : (auteur) Vegetation phenology can be extracted from vegetation index (VI) time series of satellite data. The maximum value composite (MVC) procedure and smoothing filters have been conventionally used as standard methods to exclude noises in the VI time series before extracting the vegetation phenology [e.g., National Aeronautics and Space Administration (NASA) VNP22Q2 and United States Geological Survey (USGS) MCD12Q2 phenology products]. However, it is unclear how to optimize the MVC and smoothing filters to produce the most accurate phenology metrics given that cloud frequency varies spatially. This study designed two simulation experiments, namely (1) using only the MVC and (2) using the MVC and smoothing filters together to smooth the enhanced vegetation index (EVI) time series for detecting spring phenology, i.e., start of season (SOS), over the northern hemisphere (north of 30°N) on a 5° × 5° grid cell basis by the inflection point and relative threshold algorithms. The results revealed that (1) the inappropriate selection of MVC periods (e.g., too short or too long) affected the accuracy of the SOS extracted by both phenology detection algorithms; (2) a filtering process with optimal parameters can reduce the effects of the MVC period on SOS extraction to a considerable extent, i.e., 65% and 61% for iterative Savitzky–Golay (SG) and penalized cubic splines (SP) filters, respectively; (3) optimal parameters for both the MVC and smoothing filters showed significant spatial heterogeneity; and (4) validation with ground PhenoCam data indicated that optimal parameters of the MVC and smoothing filters can produce more accurate results than official vegetation phenology products that use uniform parameters. Specifically, the R2 values of the NASA product and the USGS product were 0.58 and 0.67, which were increased to 0.70 and 0.81, respectively, by the optimal smoothing process. Optimal parameters of the MVC and smoothing filters provided by this study in each 5° × 5° sub-region may help future studies to improve the accuracy of phenology detection from satellite VI time series. Numéro de notice : A2021-653 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.08.003 Date de publication en ligne : 14/08/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.08.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98383 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2021101	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2021103	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2021102	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series / Xiaolin Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 222 - 231 Titre : Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series Type de document : Article/Communication Auteurs : Xiaolin Zhu, Auteur ; Desheng Liu, Auteur Année de publication : 2015 Article en page(s) : pp 222 - 231 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] biomasse forestière [Termes IGN] image Landsat [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] puits de carbone [Termes IGN] série temporelle [Termes IGN] variation saisonnière Résumé : (auteur) Spatially explicit knowledge of aboveground biomass (AGB) in large areas is important for accurate carbon accounting. Landsat data have been widely used to provide efficient and timely estimates of forest AGB because of their long archive and relatively high spatial resolution. Previous studies have explored different empirical modeling approaches to estimate AGB, but most of them only used a single Landsat image in the peak season, which may cause a saturation problem and low accuracy. To improve the accuracy of AGB estimation using Landsat images, this study explored the use of NDVI seasonal time-series derived from Landsat images across different seasons to estimate AGB in southeast Ohio by six empirical modeling approaches. Results clearly show that NDVI in the fall season has a stronger correlation to AGB than in the peak season, and using seasonal NDVI time-series can result in a more accurate AGB estimation and less saturation than using a single NDVI. In comparing these different empirical approaches, it is difficult to decide which one is superior to the other because they have different strengths and their accuracy is generally similar, indicating that modeling methods may not be the key issue for improving the accuracy of AGB estimation from Landsat data. This study suggests that future research should pay more attention to seasonal time-series data, and especially the data from the fall season. Numéro de notice : A2015-695 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.014 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78329 [article]