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A simple method for detecting phenological change from time series of vegetation index / Jin Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)
[article]
Titre : A simple method for detecting phenological change from time series of vegetation index Type de document : Article/Communication Auteurs : Jin Chen, Auteur ; Yuhan Rao, Auteur ; Miaogen Shen, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 3436 - 3449 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] Chine
[Termes IGN] Enhanced vegetation index
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] phénologie
[Termes IGN] série temporelleRésumé : (Auteur) Remote sensing is a valuable way to retrieve spatially continuous information on vegetation phenological changes, which are widely used as an indicator of climate change. We propose a simple method called weighted cross-correlogram spectral matching-phenology (CCSM-P), which combines CCSM and a weighted correlation system, for detecting vegetation phenological changes by using multiyear vegetation index (VI) time series. In experiments with simulated enhanced VI (EVI) for various scenarios, CCSM-P exhibited high accuracy and robustness to noise and the potential to capture long-term phenological change trends. For a temperate grassland in northern China, CCSM-P retrieved more reasonable vegetation spring phenology from Moderate Resolution Imaging Spectroradiometer (MODIS) EVI images than the MODIS phenology product (MCD12Q2). When validated against field phenological observations in five of the AmeriFlux Network sites in the U.S. (four deciduous broadleaf forest sites and a closed shrublands site), and a cropland site in China, CCSM-P exhibited mean absolute differences (MADs) ranging from 2 to 10 days (median: 4.2 days), whereas MAD of non-CCSM methods showed larger variations, ranging from 5 to 58 days (median: 21.3 days). This is because CCSM-P integrates field phenological observations. Compared with non-CCSM methods, which are widely used to identify phenological events, CCSM-P is more accurate and less dependent on prior knowledge (thresholds or predefined functions), which indicates its effectiveness and applicability for detecting year-to-year variations and long-term change trends in phenology, and should facilitate more reliable assessments of phenological changes in climate change studies. Numéro de notice : A2016-854 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2518167 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2518167 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82992
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 6 (June 2016) . - pp 3436 - 3449[article]Satellite data as indicators of tree biomass growth and forest dieback in a Mediterranean holm oak forest / Romà Ogaya in Annals of Forest Science, vol 72 n° 1 (January 2015)
[article]
Titre : Satellite data as indicators of tree biomass growth and forest dieback in a Mediterranean holm oak forest Type de document : Article/Communication Auteurs : Romà Ogaya, Auteur ; Adrià Barbeta, Auteur ; Corina Başnou, Auteur ; Josep Peñuelas, Auteur Année de publication : 2015 Article en page(s) : pp 135 - 144 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse forestière
[Termes IGN] climat méditerranéen
[Termes IGN] croissance des arbres
[Termes IGN] données météorologiques
[Termes IGN] Enhanced vegetation index
[Termes IGN] évapotranspiration
[Termes IGN] forêt méditerranéenne
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] précipitation
[Termes IGN] Quercus ilexRésumé : (auteur) Context : In the framework of climate change, decreased tree growth and enhanced mortality induced by hot and dry conditions are increasing in many forests around the world, and particularly in Mediterranean forests.
Aims : Our aim was to estimate tree growth and mortality in a Mediterranean holm oak forest, using remote sensing data from MODIS.
Methods : We monitored annual increases of aboveground biomass by measuring tree basal area, and we determined tree mortality by counting dead stems. We analyzed the relationships between forest growth and mortality with mean annual values of some MODIS products and meteorological data.
Results : Mortality and increases of aboveground biomass correlated well with precipitation, September standardized precipitation/evapotranspiration indices (SPEI), and some MODIS products such as NDVI and enhanced vegetation index EVI. Other MODIS products such as gross primary production (GPP) and net photosynthesis, however, showed no clear relationship with tree mortality or measured increases of biomass.
Conclusion : The MODIS products as proxies of ecosystemic productivity (gross primary productivity, net photosynthesis) were weakly correlated with biomass increase, and did not reflect the mortality following the drought of autumn 2011. Nevertheless, NDVI and EVI were efficient indicators of forest productivity and diebackNuméro de notice : A2015-383 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s13595-014-0408-y Date de publication en ligne : 18/09/2014 En ligne : https://doi.org/10.1007/s13595-014-0408-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76875
in Annals of Forest Science > vol 72 n° 1 (January 2015) . - pp 135 - 144[article]The potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation / Chaoyang Wu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)
[article]
Titre : The potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation Type de document : Article/Communication Auteurs : Chaoyang Wu, Auteur ; Alemu Gonsamo, Auteur ; Fangmin Zhang, Auteur ; Jing M. Chen, Auteur Année de publication : 2014 Article en page(s) : pp 69 - 79 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] arbre sempervirent
[Termes IGN] bilan du carbone
[Termes IGN] croissance des arbres
[Termes IGN] écosystème forestier
[Termes IGN] Enhanced vegetation index
[Termes IGN] forêt de feuillus
[Termes IGN] indice de végétation
[Termes IGN] production primaire brute
[Termes IGN] température au solRésumé : (Auteur) Remote sensing of vegetation gross primary production (GPP) is an important step to analyze terrestrial carbon (C) cycles in response to changing climate. The availability of global networks of C flux measurements provides a valuable opportunity to develop remote sensing based GPP algorithms and test their performances across diverse regions and plant functional types (PFTs). Using 70 global C flux measurements including 24 non-forest (NF), 17 deciduous forest (DF) and 29 evergreen forest (EF), we present the evaluation of an upscaled remote sensing based greenness and radiation (GR) model for GPP estimation. This model is developed using enhanced vegetation index (EVI) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and global course resolution radiation data from the National Center for Environmental Prediction (NCEP). Model calibration was achieved using statistical parameters of both EVI and LST fitted for different PFTs. Our results indicate that compared to the standard MODIS GPP product, the calibrated GR model improved the GPP accuracy by reducing the root mean square errors (RMSE) by 16%, 30% and 11% for the NF, DF and EF sites, respectively. The standard MODIS and GR model intercomparisons at individual sites for GPP estimation also showed that GR model performs better in terms of model accuracy and stability. This evaluation demonstrates the potential use of the GR model in capturing short-term GPP variations in areas lacking ground measurements for most of vegetated ecosystems globally. Numéro de notice : A2014-085 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32990
in ISPRS Journal of photogrammetry and remote sensing > vol 88 (February 2014) . - pp 69 - 79[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014021 RAB Revue Centre de documentation En réserve L003 Disponible Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley / L. Zhong in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
[article]
Titre : Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley Type de document : Article/Communication Auteurs : L. Zhong, Auteur ; P. Gong, Auteur ; Gregory S. Biging, Auteur Année de publication : 2012 Article en page(s) : pp 799 - 813 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte agricole
[Termes IGN] classification par arbre de décision
[Termes IGN] cultures
[Termes IGN] Enhanced vegetation index
[Termes IGN] évapotranspiration
[Termes IGN] fusion d'images
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] image Terra-MODIS
[Termes IGN] phénologie
[Termes IGN] segmentation d'imageRésumé : (Auteur) The overarching goal of this study was to map specific crop types in the Central Valley, California and estimate the effect of classification uncertainty on the calculation of crop evapotranspiration (ETc). A phenology-based classification (PBC) approach was developed to identify crop types based on phenological and spectral metrics derived from the time series of Landsat TM/ETM_ imagery. Phenological metrics, calculated by fitting asymmetric double sigmoid functions to temporal profiles of enhanced vegetation index (EVI), were capable of separating crop types with distinct crop calendars. An innovative method was used to compute spectral metrics to represent crops' spectral characteristics at certain phenological stages instead of any specific imaging date. Crop mapping using these metrics showed a stable performance without influences of low-quality data and inter-annual differences in imaging dates. The requirement for ground reference data by the PBC approach was low because classification algorithms were mostly built according to the knowledge on crop calendars and agricultural practices. Techniques including image segmentation, data fusion with MODIS imagery, and decision tree were incorporated to make the approach effective and efficient. Though moderate accuracy (~65.0 percent) was achieved, ETc calculated by the Food and Agriculture Organization (FAO) 56 method showed that the estimate of water use was not likely to be significantly affected by the classification error in PBC. All these advantages imply the strength of the PBC approach in the regular crop mapping of the Central Valley. Numéro de notice : A2012-428 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.799 En ligne : https://doi.org/10.14358/PERS.78.8.799 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31874
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 799 - 813[article]Carbon Stock of European Beech Forest : A Case at M. Pizzalto, Italy / Aida Taghavi Bayat in APCBEE Procedia, vol 1 (2-20)
[article]
Titre : Carbon Stock of European Beech Forest : A Case at M. Pizzalto, Italy Type de document : Article/Communication Auteurs : Aida Taghavi Bayat, Auteur ; Hein van Gils, Auteur ; Michael Weir, Auteur Année de publication : 2012 Article en page(s) : pp 159 - 168 Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] biomasse aérienne
[Termes IGN] Enhanced vegetation index
[Termes IGN] Fagus (genre)
[Termes IGN] image Terra-MODIS
[Termes IGN] Italie
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] puits de carbone
[Termes IGN] régression linéaire
[Termes IGN] saison
[Termes IGN] teneur en carbone
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) In order to estimate carbon stock in above ground biomass (CS-AGB) of M. Pizzalto forest in the Central-Apennines in Italy, the moderate resolution imaging spectroradiometer (MODIS) vegetation index data (NDVI and EVI) were used in combination with field data. Biotic and abiotic parameters (slope angle, slope gradient, elevation, seasonal incoming solar radiation, length of growing season (LGS), soil type and forest management type) has been used in the modelling. NDVI and EVI values of field samples were extracted and used to estimate the LGS of beech forest for the six year period (2005-2010). Two management types, old-growth forest and young forest, showed average AGB and CS-AGB were 247 and 123 tons.ha-1 respectively in 2010 comparable to values for beech forests in the Apennines and Europe. LGS and management are the significant variables in a linear regression model for CS - AGB. Therefore, the forest authority can manage the young forest as sinks of carbon in agreement with the Kyoto protocol of the United Nations Framework Convention on Climate Change (UNFCCC). Numéro de notice : A2012-693 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.apcbee.2012.03.026 En ligne : https://doi.org/10.1016/j.apcbee.2012.03.026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74830
in APCBEE Procedia > vol 1 (2-20) . - pp 159 - 168[article]MODIS enhanced vegetation index predicts tree species richness across forested ecoregions in the contiguous USA / R.H. Waring in Remote sensing of environment, vol 103 n° 2 (30/07/2006)PermalinkA simple and effective radiometric correction method to improve landscape change detection across sensors and across time / X. Chen in Remote sensing of environment, vol 98 n° 1 (30/09/2005)PermalinkLand cover characterization of temperate east Asia using multi-temporal vegetation sensor data / S.H. Boles in Remote sensing of environment, vol 90 n° 4 (30/04/2004)Permalink