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Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
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Titre : Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China Type de document : Article/Communication Auteurs : Mingyue Wang, Auteur ; Jun’e Fu, Auteur ; Zhitao Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] coefficient de corrélation
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] écosystème
[Termes IGN] Fleuve jaune (Chine)
[Termes IGN] image Aqua-MODIS
[Termes IGN] image SPOT
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] précipitation
[Termes IGN] série temporelle
[Termes IGN] température
[Termes IGN] variation saisonnièreRésumé : (auteur) Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area. Numéro de notice : A2020-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040282 Date de publication en ligne : 24/04/2020 En ligne : https://doi.org/10.3390/ijgi9040282 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95022
in ISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 17 p.[article]An original method for tree species classification using multitemporal multispectral and hyperspectral satellite data / Olga Grigorieva in Silva fennica, vol 54 n° 2 (March 2020)
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Titre : An original method for tree species classification using multitemporal multispectral and hyperspectral satellite data Type de document : Article/Communication Auteurs : Olga Grigorieva, Auteur ; Olga Brovkina, Auteur ; Alisher Saidov, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Betula (genre)
[Termes IGN] carte forestière
[Termes IGN] classification
[Termes IGN] erreur de classification
[Termes IGN] image hyperspectrale
[Termes IGN] image Landsat-OLI
[Termes IGN] image multibande
[Termes IGN] phénologie
[Termes IGN] Pinus (genre)
[Termes IGN] réflectance spectrale
[Termes IGN] République Tchèque
[Termes IGN] Russie
[Termes IGN] signature spectrale
[Termes IGN] variation saisonnièreRésumé : (auteur) his study proposes an original method for tree species classification by satellite remote sensing. The method uses multitemporal multispectral (Landsat OLI) and hyperspectral (Resurs-P) data acquired from determined vegetation periods. The method is based on an original database of spectral features taking into account seasonal variations of tree species spectra. Changes in the spectral signatures of forest classes are analyzed and new spectral–temporal features are created for the classification. Study sites are located in the Czech Republic and northwest (NW) Russia. The differences in spectral reflectance between tree species are shown as statistically significant in the sub-seasons of spring, first half of summer, and main autumn for both study sites. Most of the errors are related to the classification of deciduous species and misclassification of birch as pine (NW Russia site), pine as mixture of pine and spruce, and pine as mixture of spruce and beech (Czech site). Forest species are mapped with accuracy as high as 80% (NW Russia site) and 81% (Czech site). The classification using multitemporal multispectral data has a kappa coefficient 1.7 times higher than does that of classification using a single multispectral image and 1.3 times greater than that of the classification using single hyperspectral images. Potentially, classification accuracy can be improved by the method when applying multitemporal satellite hyperspectral data, such as in using new, near-future products EnMap and/or HyspIRI with high revisit time. Numéro de notice : A2020-324 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.10143 Date de publication en ligne : 02/03/2020 En ligne : https://doi.org/10.14214/sf.10143 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95198
in Silva fennica > vol 54 n° 2 (March 2020)[article]Recent sea level change in the black sea from satellite altimetry and tide gauge observations / Nevin Betül Avsar in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
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Titre : Recent sea level change in the black sea from satellite altimetry and tide gauge observations Type de document : Article/Communication Auteurs : Nevin Betül Avsar, Auteur ; H.S. Kutoglu, Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] altimétrie
[Termes IGN] déformation verticale de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] données marégraphiques
[Termes IGN] données satellitaires
[Termes IGN] données topographiques
[Termes IGN] érosion côtière
[Termes IGN] marégraphe
[Termes IGN] montée du niveau de la mer
[Termes IGN] Noire, mer
[Termes IGN] série temporelle
[Termes IGN] surcharge hydrologique
[Termes IGN] variation saisonnière
[Vedettes matières IGN] AltimétrieRésumé : (auteur) Global mean sea level has been rising at an increasing rate, especially since the early 19th century in response to ocean thermal expansion and ice sheet melting. The possible consequences of sea level rise pose a significant threat to coastal cities, inhabitants, infrastructure, wetlands, ecosystems, and beaches. Sea level changes are not geographically uniform. This study focuses on present-day sea level changes in the Black Sea using satellite altimetry and tide gauge data. The multi-mission gridded satellite altimetry data from January 1993 to May 2017 indicated a mean rate of sea level rise of 2.5 ± 0.5 mm/year over the entire Black Sea. However, when considering the dominant cycles of the Black Sea level time series, an apparent (significant) variation was seen until 2014, and the rise in the mean sea level has been estimated at about 3.2 ± 0.6 mm/year. Coastal sea level, which was assessed using the available data from 12 tide gauge stations, has generally risen (except for the Bourgas Station). For instance, from the western coast to the southern coast of the Black Sea, in Constantza, Sevastopol, Tuapse, Batumi, Trabzon, Amasra, Sile, and Igneada, the relative rise was 3.02, 1.56, 2.92, 3.52, 2.33, 3.43, 5.03, and 6.94 mm/year, respectively, for varying periods over 1922–2014. The highest and lowest rises in the mean level of the Black Sea were in Poti (7.01 mm/year) and in Varna (1.53 mm/year), respectively. Measurements from six Global Navigation Satellite System (GNSS) stations, which are very close to the tide gauges, also suggest that there were significant vertical land movements at some tide gauge locations. This study confirmed that according to the obtained average annual phase value of sea level observations, seasonal sea level variations in the Black Sea reach their maximum annual amplitude in May–June. Numéro de notice : A2020-254 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030185 Date de publication en ligne : 20/03/2020 En ligne : https://doi.org/10.3390/ijgi9030185 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95008
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 18 p.[article]Xylem anatomy of Robinia pseudoacacia L. and Quercus robur L. is differently affected by climate in a temperate alluvial forest / Paola Nola in Annals of Forest Science, Vol 77 n° 1 (March 2020)
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Titre : Xylem anatomy of Robinia pseudoacacia L. and Quercus robur L. is differently affected by climate in a temperate alluvial forest Type de document : Article/Communication Auteurs : Paola Nola, Auteur ; Francesco Bracco, Auteur ; Silvia Assini, Auteur ; Georg von Arx, Auteur ; Daniele Catagneri, Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cerne
[Termes IGN] dendrochronologie
[Termes IGN] espèce exotique envahissante
[Termes IGN] espèce pionnière
[Termes IGN] forêt ripicole
[Termes IGN] gestion forestière
[Termes IGN] orthoptère
[Termes IGN] Quercus pedunculata
[Termes IGN] Robinia pseudoacacia
[Termes IGN] sécheresse
[Termes IGN] variation saisonnière
[Termes IGN] xylème
[Termes IGN] zone tempérée
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Key message: Xylem hydraulic traits of native Quercus robur are more sensitive to previous-summer drought than those of alien Robinia pseudoacacia. The latter modulates vessel traits and ring porosity to cope with inter-annual climate variability, and is less affected by extreme events. This suggests that R. pseudoacacia might be more competitive under future drier conditions. Context: Forest management strategies require knowledge on how co-occurring native and alien species respond to unprecedented climate conditions, which can severely affect xylem conductivity and tree performance. Aims: We aimed at quantitatively comparing xylem anatomical traits of co-occurring native Quercus robur and alien Robinia pseudoacacia and assessing similarities and differences in their response to climate variability. Methods: We analyzed tree-ring anatomy and built chronologies of several parameters related to vessel number, size, and theoretical conductivity. Mean chronologies for each parameter were correlated to monthly temperature and precipitation data for the period 1954–2005 and within 30-year moving windows. We also assessed responses to extreme conditions in 2003. Results: Quercus robur showed typical ring-porous vessel distribution, while R. pseudoacacia modulated vessel size and number year by year, frequently showing semi-ring porous appearance. Previous rainy summers increased size of large vessels in Q. robur, and number of large vessels in R. pseudoacacia. In winter, R. pseudoacacia was sensitive to water excess. High temperature in March increased vessel size in Q. robur, but reduced it in R. pseudoacacia. The 2003 summer heatwave strongly reduced vessel size and number in the following year in Q. robur, but had much less effect on R. pseudoacacia. Conclusion: Quercus robur xylem traits are more influenced by both inter-annual climate variability and extreme events than those of R. pseudoacacia. Lower performance under dry conditions might reduce competitiveness of Q. robur in the future, slowing down the natural replacement of the invasive pioneer R. pseudoacacia by later-stage Q. robur. Numéro de notice : A2020-068 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0906-z Date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1007/s13595-019-0906-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94581
in Annals of Forest Science > Vol 77 n° 1 (March 2020) . - 16 p.[article]Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods / Elisa Kamir in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
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Titre : Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods Type de document : Article/Communication Auteurs : Elisa Kamir, Auteur ; François Waldner, Auteur ; Zvi Hochman, Auteur Année de publication : 2020 Article en page(s) : pp 124 - 135 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] Australie
[Termes IGN] blé (céréale)
[Termes IGN] carte agricole
[Termes IGN] climat
[Termes IGN] estimation de précision
[Termes IGN] fonction de base radiale
[Termes IGN] image satellite
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle non linéaire
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression
[Termes IGN] rendement agricole
[Termes IGN] série temporelle
[Termes IGN] variation saisonnièreRésumé : (Auteur) Closing the yield gap between actual and potential wheat yields in Australia is important to meet the growing global demand for food. The identification of hotspots of the yield gap, where the potential for improvement is the greatest, is a necessary step towards this goal. While crop growth models are well suited to quantify potential yields, they lack the ability to provide accurate large-scale estimates of actual yields, owing to the sheer quantity of data they require for parameterisation. In this context, we sought to provide accurate estimates of actual wheat yields across the Australian wheat belt based on machine-learning regression methods, climate records and satellite image time series. Out of nine base learners and two ensembles, support vector regression with radial basis function emerged as the single best learner (root mean square error of 0.55 t ha−1 and R2 of 0.77 at the pixel level). At national scale, this model explained 73% of the yield variability observed across statistical units. Benchmark approaches based on peak Normalised Difference Vegetation Index (NDVI) and on a harvest index were largely outperformed by the machine-learning regression models (R2 Numéro de notice : A2020-046 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.11.008 Date de publication en ligne : 20/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.008 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94556
in ISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 124 - 135[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020021 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020023 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020022 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt A warning against over-interpretation of seasonal signals measured by the Global Navigation Satellite System / Kristel Chanard in Nature communications, vol 11 (2020)
PermalinkArctic sea ice thickness retrievals from CryoSat-2: seasonal and interannual comparisons of three different products / Mengmeng Li in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)
PermalinkInversion de données PolSAR en bande P pour l'estimation de la biomasse forestière / Colette Gelas (2020)
PermalinkA new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello (2020)
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PermalinkUsing remote sensing to assess the effect of time of day on the spatial and temporal variation of LST in urban areas / Akram Abdulla (2020)
PermalinkAccurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits / Tawanda W. Gara in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)
PermalinkVulnerability of forest ecosystems to fire in the French Alps / Sylvain Dupire in European Journal of Forest Research, Vol 138 n° 5 (octobre 2019)
PermalinkDecomposition of geodetic time series: A combined simulated annealing algorithm and Kalman filter approach / Feng Ming in Advances in space research, vol 64 n°5 (1 September 2019)
PermalinkConsistency and representativeness of integrated water vapour from ground-based GPS observations and ERA-Interim reanalysis / Olivier Bock in Atmospheric chemistry and physics, vol 19 n° 14 (July 2019)
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