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Assessing forest phenology: A multi-scale comparison of near-surface (UAV, spectral reflectance sensor, PhenoCam) and satellite (MODIS, Sentinel-2) remote sensing / Shangharsha Thapa in Remote sensing, vol 13 n° 8 (15 April 2021)  

Public [article]  inRemote sensing > vol 13 n° 8 (15 April 2021) . - n° 1597 Titre : Assessing forest phenology: A multi-scale comparison of near-surface (UAV, spectral reflectance sensor, PhenoCam) and satellite (MODIS, Sentinel-2) remote sensing Type de document : Article/Communication Auteurs : Shangharsha Thapa, Auteur ; Virginia Garcia Millan, Auteur ; Lars Eklundh, Auteur Année de publication : 2021 Article en page(s) : n° 1597 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse multiéchelle [Termes descripteurs IGN] capteur multibande [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] phénologie [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] Suède [Termes descripteurs IGN] surveillance forestière [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) The monitoring of forest phenology based on observations from near-surface sensors such as Unmanned Aerial Vehicles (UAVs), PhenoCams, and Spectral Reflectance Sensors (SRS) over satellite sensors has recently gained significant attention in the field of remote sensing and vegetation phenology. However, exploring different aspects of forest phenology based on observations from these sensors and drawing comparatives from the time series of vegetation indices (VIs) still remains a challenge. Accordingly, this research explores the potential of near-surface sensors to track the temporal dynamics of phenology, cross-compare their results against satellite observations (MODIS, Sentinel-2), and validate satellite-derived phenology. A time series of Normalized Difference Vegetation Index (NDVI), Green Chromatic Coordinate (GCC), and Normalized Difference of Green & Red (VIgreen) indices were extracted from both near-surface and satellite sensor platforms. The regression analysis between time series of NDVI data from different sensors shows the high Pearson’s correlation coefficients (r > 0.75). Despite the good correlations, there was a remarkable offset and significant differences in slope during green-up and senescence periods. SRS showed the most distinctive NDVI profile and was different to other sensors. PhenoCamGCC tracked green-up of the canopy better than the other indices, with a well-defined start, end, and peak of the season, and was most closely correlated (r > 0.93) with the satellites, while SRS-based VIgreen accounted for the least correlation (r = 0.58) against Sentinel-2. Phenophase transition dates were estimated and validated against visual inspection of the PhenoCam data. The Start of Spring (SOS) and End of Spring (EOS) could be predicted with an accuracy of Numéro de notice : A2021-382 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13081597 date de publication en ligne : 20/04/2021 En ligne : https://doi.org/10.3390/rs13081597 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97633 [article]

Assessment of degree-2 order-1 gravitational changes from GRACE and GRACE Follow-on, Earth rotation, satellite laser ranging, and models / Jianli Chen in Journal of geodesy, vol 95 n° 4 (April 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 4 (April 2021) . - n° 38 Titre : Assessment of degree-2 order-1 gravitational changes from GRACE and GRACE Follow-on, Earth rotation, satellite laser ranging, and models Type de document : Article/Communication Auteurs : Jianli Chen, Auteur ; John Ries, Auteur ; Byron D. Tapley, Auteur Année de publication : 2021 Article en page(s) : n° 38 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] données géophysiques [Termes descripteurs IGN] données GRACE [Termes descripteurs IGN] données TLS (télémétrie) [Termes descripteurs IGN] marée terrestre [Termes descripteurs IGN] mouvement du pôle [Termes descripteurs IGN] paramètres d'orientation de la Terre [Termes descripteurs IGN] rotation de la Terre [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) We carry out a comprehensive analysis and assessment of degree-2 gravitational changes ΔC21, and ΔS21, estimated using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO), satellite laser ranging (SLR), Earth Orientation Parameters (EOP), and geophysical models over the period April 2002–February 2020. The four independent estimates of ΔC21 and ΔS21 variations agree well over a broad band of frequencies. The GRACE/GFO Release 6 (RL06) solutions show major improvements over the previous RL05 solutions at both seasonal and intra-seasonal time scales, when compared with EOP and SLR estimates. Among the four independent estimates, highest correlation coefficients and smallest RMS residuals are found between GRACE/GFO and EOP estimates of ΔC21 and ΔS21 variations. GRACE/GFO and EOP ΔC21 and ΔS21 estimates exhibit slightly different trends, which are related to the implementation and interpretation of the pole tide correction in GRACE/GFO data processing. This study provides an important early validation of GFO ΔC21 and ΔS21 solutions, especially the new pole tide correction applied in GRACE/GFO RL06 solutions using independent estimates. Numéro de notice : A2021-254 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01492-x date de publication en ligne : 06/03/2021 En ligne : https://doi.org/10.1007/s00190-021-01492-x Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97279 [article]

Precipitable water vapor fusion based on a generalized regression neural network / Bao Zhang in Journal of geodesy, vol 95 n° 4 (April 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 4 (April 2021) . - n° 36 Titre : Precipitable water vapor fusion based on a generalized regression neural network Type de document : Article/Communication Auteurs : Bao Zhang, Auteur ; Yibing Yao, Auteur Année de publication : 2021 Article en page(s) : n° 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] Amérique du nord [Termes descripteurs IGN] coefficient d'étalonnage [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] fusion de données [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] prévision météorologique [Termes descripteurs IGN] régression [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] vapeur d'eau [Termes descripteurs IGN] variation temporelle Résumé : (auteur) Water vapor plays an important role in Earth’s weather and climate processes and energy transfer. Plenty of techniques have developed to monitor precipitable water vapor (PWV), but joint use of different techniques has some problems, including systematic biases, different spatiotemporal coverages and resolutions among different datasets. To address the above problems and improve the data utilization, we propose to use a generalized regression neural network (GRNN) to fuse PWVs from Global Navigation Satellite System (GNSS), Moderate-Resolution Imaging Spectroradiometer (MODIS), and European Centre for Medium‐Range Weather Forecasts Reanalysis 5 (ERA5). The core idea of this method is to use the high-quality GNSS PWV to calibrate and optimize the relatively low-quality MODIS and ERA5 PWV through the constructed GRNNs. Using the proposed method, we generated more than 400 PWV maps that combine GNSS, MODIS, and ERA5 PWVs in North America in 2018. Results show that the overall bias, standard deviation (STD), and root-mean-square (RMS) error are 0.0 mm, 2.1 mm, and 2.2 mm for the improved MODIS PWV, and 0.0 mm, 1.6 mm, and 1.6 mm for the improved ERA5 PWV. Compared to the original MODIS and ERA5 PWV, the total improvements are 37.1% and 15.8% in terms of RMS. The RMS improvements are mainly contributed from the calibration of bias for the MODIS PWV and optimization for the ERA5 PWV. It also demonstrates that the original MODIS PWV tends to be greater than the GNSS PWV while the ERA5 PWV has very small biases. After calibration and optimization, the correlation coefficients between the modified PWV and the GNSS PWV are 0.96 for the MODIS PWV and 0.98 for the ERA5 PWV. The proposed method also diminishes the temporal and spatial variations in accuracy, generating homogeneous PWV products. Since the biases among the three datasets are well removed and data accuracies are improved to the same level, they are thus easily fused and jointly used. Numéro de notice : A2021-259 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01482-z date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.1007/s00190-021-01482-z Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97299 [article]

Urban heat island formation in greater Cairo: Spatio-temporal analysis of daytime and nighttime land surface temperatures along the urban–rural gradient / Darshana Athukorala in Remote sensing, vol 13 n° 7 (April 2021)  

Public [article]  inRemote sensing > vol 13 n° 7 (April 2021) . - n° 1396 Titre : Urban heat island formation in greater Cairo: Spatio-temporal analysis of daytime and nighttime land surface temperatures along the urban–rural gradient Type de document : Article/Communication Auteurs : Darshana Athukorala, Auteur ; Yuji Murayama, Auteur Année de publication : 2021 Article en page(s) : n° 1396 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] espace vert [Termes descripteurs IGN] Google Earth Engine [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] image Landsat-TIRS [Termes descripteurs IGN] image Landsat-TM [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] Le Caire [Termes descripteurs IGN] nuit [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] urbanisme [Termes descripteurs IGN] variation diurne [Termes descripteurs IGN] zone rurale [Termes descripteurs IGN] zone urbaine Résumé : (auteur) An urban heat island (UHI) is a significant anthropogenic modification of urban land surfaces, and its geospatial pattern can increase the intensity of the heatwave effects. The complex mechanisms and interactivity of the land surface temperature in urban areas are still being examined. The urban–rural gradient analysis serves as a unique natural opportunity to identify and mitigate ecological worsening. Using Landsat Thematic Mapper (TM), Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS), Land Surface Temperature (LST) data in 2000, 2010, and 2019, we examined the spatial difference in daytime and nighttime LST trends along the urban–rural gradient in Greater Cairo, Egypt. Google Earth Engine (GEE) and machine learning techniques were employed to conduct the spatio-temporal analysis. The analysis results revealed that impervious surfaces (ISs) increased significantly from 564.14 km2 in 2000 to 869.35 km2 in 2019 in Greater Cairo. The size, aggregation, and complexity of patches of ISs, green space (GS), and bare land (BL) showed a strong correlation with the mean LST. The average urban–rural difference in mean LST was −3.59 °C in the daytime and 2.33 °C in the nighttime. In the daytime, Greater Cairo displayed the cool island effect, but in the nighttime, it showed the urban heat island effect. We estimated that dynamic human activities based on the urban structure are causing the spatial difference in the LST distribution between the day and night. The urban–rural gradient analysis indicated that this phenomenon became stronger from 2000 to 2019. Considering the drastic changes in the spatial patterns and the density of IS, GS, and BL, urban planners are urged to take immediate steps to mitigate increasing surface UHI; otherwise, urban dwellers might suffer from the severe effects of heatwaves. Numéro de notice : A2021-352 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13071396 date de publication en ligne : 05/04/2021 En ligne : https://doi.org/10.3390/rs13071396 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97602 [article]

Terrestrial laser scanning intensity captures diurnal variation in leaf water potential / S. Junttila in Remote sensing of environment, Vol 255 (March 2021)  

Public [article]  inRemote sensing of environment > Vol 255 (March 2021) . - n° 112274 Titre : Terrestrial laser scanning intensity captures diurnal variation in leaf water potential Type de document : Article/Communication Auteurs : S. Junttila, Auteur ; T. Hölttä, Auteur ; Eetu Puttonen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112274 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] Betula (genre) [Termes descripteurs IGN] diagnostic foliaire [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] dynamique de la végétation [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] sécheresse [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] stress hydrique [Termes descripteurs IGN] teneur en eau de la végétation [Termes descripteurs IGN] variation diurne Résumé : (auteur) During the past decades, extreme events have become more prevalent and last longer, and as a result drought-induced plant mortality has increased globally. Timely information on plant water dynamics is essential for understanding and anticipating drought-induced plant mortality. Leaf water potential (ΨL), which is usually measured destructively, is the most common metric that has been used for decades for measuring water stress. Remote sensing methods have been developed to obtain information on water dynamics from trees and forested landscapes. However, the spatial and temporal resolutions of the existing methods have limited our understanding of the water dynamics and diurnal variation of ΨL within single trees. Thus, we investigated the capability of terrestrial laser scanning (TLS) intensity in observing diurnal variation in ΨL during a 50-h monitoring period. We aimed to improve the understanding on how large a part of the diurnal variation in ΨL can be captured using TLS intensity observations. We found that TLS intensity at the 905 nm wavelength measured from a static position was able to explain 77% of the variation in ΨL for three trees of two tree species with a root mean square error of 0.141 MPa. Based on our experiment with three trees, a time series of TLS intensity measurements can be used in detecting changes in ΨL, and thus it is worthwhile to expand the investigations to cover a wider range of tree species and forests and further increase our understanding of plant water dynamics at wider spatial and temporal scales. Numéro de notice : A2021-192 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2020.112274 date de publication en ligne : 14/01/2021 En ligne : https://doi.org/10.1016/j.rse.2020.112274 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97113 [article]

Is the seasonal variation in frost resistance and plant performance in four oak species affected by changing temperatures? / Maggie Preißer in Forests, vol 12 n° 3 (March 2021)  

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Radar measurements of snow depth over sea ice on an unmanned aerial vehicle / Adrian Eng-Choon Tan in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

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Saline-soil deformation extraction based on an improved time-series InSAR approach / Wei Xiang in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)  

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Assessment of mass-induced sea level variability in the Tropical Indian Ocean based on GRACE and altimeter observations / Shiva Shankar Manche in Journal of geodesy, vol 95 n° 2 (February 2021)  

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Comprehensive time-series analysis of bridge deformation using differential satellite radar interferometry based on Sentinel-1 / Matthias Schlögl in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)  

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Mapping seasonal agricultural land use types using deep learning on Sentinel-2 image time series / Misganu Debella-Gilo in Remote sensing, Vol 13 n° 2 (January 2021)  

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Characteristics of seasonal variations and noises of the daily double-difference and PPP solutions / Kamil Maciuk in Journal of applied geodesy, vol 15 n° 1 (January 2021)  

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Dynamic mechanism of blown sand hazard formation at the Jieqiong section of the Lhasa–Shigatse railway / Shengbo Xie in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)  

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A new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello in Journal of the Royal Statistical Society: Series C Applied Statistics, vol inconnu ([01/01/2021])  

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Soil biodiversity as affected by different thinning intensities in a pinus laricio stand of Calabrian Apennine, South Italy / Adele Muscolo in Forests, vol 12 n° 1 (January 2021)  

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