Centre de documentation
scientifique

A new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index / Huanhuan Yuan in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 390 - 399 Titre : A new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index Type de document : Article/Communication Auteurs : Huanhuan Yuan, Auteur ; Chaoyang Wu, Auteur ; Linlin Lu, Auteur ; Xiaoyue Wang, Auteur Année de publication : 2018 Article en page(s) : pp 390 - 399 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Canada [Termes IGN] croissance des arbres [Termes IGN] Enhanced vegetation index [Termes IGN] forêt [Termes IGN] modèle de simulation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] nuit [Termes IGN] Pinophyta [Termes IGN] production primaire brute [Termes IGN] simulation numérique [Termes IGN] température au sol Résumé : (Auteur) Accurate estimation of vegetation phenology (the start/end of growing season, SOS/EOS) is important to understand the feedbacks of vegetation to meteorological circumstances. Because the evergreen forests have limited change in greenness, there are relatively less study to predict evergreen conifer forests phenology, especially for EOS in autumn. Using 11-year (2000–2010) records of MODIS normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), together with gross primary production (GPP) and temperature data at five evergreen conifer forests flux sites in Canada, we comprehensively evaluated the performances of several variables in modeling flux-derived EOS. Results showed that neither NDVI nor EVI can be used to predict EOS as they had no significant correlation with ground observations. In comparison, temperature had a better predictive strength for EOS, and R2 between EOS and mean temperature (Tmean), the maximum temperature (Tmax, daytime temperature) and the minimum temperature (Tmin, nighttime temperature) were 0.45 (RMSE = 5.1 days), 0.32 (RMSE = 5.7 days) and 0.58 (RMSE = 4.6 days), respectively. These results suggest an unreported role of nighttime temperature in regulating EOS of evergreen forests, in comparison with previous study showing leaf-out in spring by daytime temperature. Furthermore, we demonstrated that it may be because nighttime temperature has a higher relationship with soil temperature (Ts) (R2 = 0.67, p  Numéro de notice : A2018-403 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.08.013 Date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90855 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018101	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018103	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018102	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Detecting winter wheat phenology with SPOT-VEGETATION data in the North China Plain / Linlin Lu in Geocarto international, vol 29 n° 3 - 4 (June - July 2014)  

Public [article]  inGeocarto international > vol 29 n° 3 - 4 (June - July 2014) . - pp. 244 - 255 Titre : Detecting winter wheat phenology with SPOT-VEGETATION data in the North China Plain Type de document : Article/Communication Auteurs : Linlin Lu, Auteur ; Cuizhen Wang, Auteur ; Huadong Guo, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp. 244 - 255 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] agriculture [Termes IGN] blé (céréale) [Termes IGN] Chine [Termes IGN] image SPOT-Végétation [Termes IGN] phénologie [Termes IGN] série temporelle Résumé : (Auteur)Monitoring phenological change in agricultural land improves our understanding of the adaptation of crops to a warmer climate. Winter wheat–maize and winter wheat–cotton double-cropping are practised in most agricultural areas in the North China Plain. A curve-fitting method is presented to derive winter wheat phenology from SPOT-VEGETATION S10 normalized difference vegetation index (NDVI) data products. The method uses a double-Gaussian model to extract two phenological metrics, the start of season (SOS) and the time of maximum NDVI (MAXT). The results are compared with phenological records at local agrometeorological stations. The SOS and MAXT have close agreement with in situ observations of the jointing date and milk-in-kernel date respectively. The phenological metrics detected show spatial variations that are consistent with known phenological characteristics. This study indicates that time-series analysis with satellite data could be an effective tool for monitoring the phenology of crops and its spatial distribution in a large agricultural region. Numéro de notice : A2014-338 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.760004 En ligne : https://doi.org/10.1080/10106049.2012.760004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73706 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2014021	RAB	Revue	Centre de documentation	En réserve L003	Disponible