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Mapping leaf chlorophyll content from Sentinel-2 and RapidEye data in spruce stands using the invertible forest reflectance model / Roshanak Darvishzadeh in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)
[article]
Titre : Mapping leaf chlorophyll content from Sentinel-2 and RapidEye data in spruce stands using the invertible forest reflectance model Type de document : Article/Communication Auteurs : Roshanak Darvishzadeh, Auteur ; Andrew K. Skidmore, Auteur ; Haidi Abdullah, Auteur ; Elias Cherenet, Auteur Année de publication : 2019 Article en page(s) : pp 58-70 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse multibande
[Termes IGN] bande rouge
[Termes IGN] bande spectrale
[Termes IGN] Bavière (Allemagne)
[Termes IGN] canopée
[Termes IGN] carte de la végétation
[Termes IGN] image RapidEye
[Termes IGN] image Sentinel-MSI
[Termes IGN] modèle d'inversion
[Termes IGN] Picea abies
[Termes IGN] réflectance végétale
[Termes IGN] spectrophotométrie
[Termes IGN] teneur en chlorophylle des feuillesRésumé : (auteur) Leaf chlorophyll plays an essential role in controlling photosynthesis, physiological activities and forest health. In this study, the performance of Sentinel-2 and RapidEye satellite data and the Invertible Forest Reflectance Model (INFORM) radiative transfer model (RTM) for retrieving and mapping of leaf chlorophyll content in the Norway spruce (Picea abies) stands of a temperate forest was evaluated. Biochemical properties of leaf samples as well as stand structural characteristics were collected in two subsequent field campaigns during July 2015 and 2016 in the Bavarian Forest National Park (BFNP), Germany, parallel with the timing of the RapidEye and Sentinel-2 images. Leaf chlorophyll was measured both destructively and nondestructively using wet chemical spectrophotometry analysis and a hand-held chlorophyll content meter. The INFORM was utilised in the forward mode to generate two lookup tables (LUTs) in the spectral band settings of RapidEye and Sentinel-2 data using information obtained from the field campaigns. Before generating the LUTs, the sensitivity of the model input parameters to the spectral data from RapidEye and Sentinel-2 were examined. The canopy reflectance of the studied plots were obtained from the satellite images and used as input for the inversion of LUTs. The coefficient of determination (R2), root mean square errors (RMSE), and the normalised root mean square errors (NRMSE), between the retrieved and measured leaf chlorophyll, were then used to examine the attained results from RapidEye and Sentinel-2 data, respectively. The use of multiple solutions and spectral subsets for the inversion process were further investigated to enhance the retrieval accuracy of foliar chlorophyll. The result of the sensitivity analysis demonstrated that the simulated canopy reflectance of Sentinel-2 is sensitive to the alternation of all INFORM input parameters, while the simulated canopy reflectance from RapidEye did not show sensitivity to leaf water content variations. In general, there was agreement between the simulated and measured reflectance spectra from RapidEye and Sentinel-2, particularly in the visible and red-edge regions. However, examining the average absolute error from the simulated and measured reflectance revealed a large discrepancy in spectral bands around the near-infrared shoulder. The relationship between retrieved and measured leaf chlorophyll content from the Sentinel-2 data had a higher coefficient of determination with a higher NRMSE (NRMSE = 0.36 μg/cm2, R2 = 0.45) compared to those obtained using the RapidEye data (NRMSE = 0.31 μg/cm2 and R2 = 0.39). Using the mean of the ten best solutions (retrieved chlorophyll) the retrieval error for both Sentinel-2 and RapidEye data decreased (NRMSE = 0.34, NRMSE = 0.26, respectively), as compared to only selecting the single best solution. When the Sentinel-2 red edge bands were used as the spectral subset, the retrieval error of leaf chlorophyll decreased indicating the importance of red edge, as well as properly located spectral bands, for leaf chlorophyll estimation. The chlorophyll maps produced by the inversion of the two LUTs effectively represented the variation of foliar chlorophyll in BFNP and confirmed our earlier findings on the observed stress pattern caused by insect infestation. Our findings emphasise the importance of multispectral satellites which benefits from red edge spectral bands such as Sentinel-2 as well as RapidEye for regional mapping of vegetation foliar properties, particularly, chlorophyll using RTMs such as INFORM. Numéro de notice : A2019-460 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2019.03.003 Date de publication en ligne : 08/03/2019 En ligne : https://doi.org/10.1016/j.jag.2019.03.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93577
in International journal of applied Earth observation and geoinformation > vol 79 (July 2019) . - pp 58-70[article]Sensitivity of GPS tropospheric estimates to mesoscale convective systems in West Africa / Samuel Nahmani in Atmospheric chemistry and physics, vol 19 n° 14 (July 2019)
[article]
Titre : Sensitivity of GPS tropospheric estimates to mesoscale convective systems in West Africa Type de document : Article/Communication Auteurs : Samuel Nahmani , Auteur ; Olivier Bock , Auteur ; Françoise Guichard, Auteur Année de publication : 2019 Projets : VEGAN / Bock, Olivier, TOSCA / Bock, Olivier Article en page(s) : pp 9541 - 9561 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] Afrique occidentale
[Termes IGN] analyse de sensibilité
[Termes IGN] bande C
[Termes IGN] convection
[Termes IGN] données GPS
[Termes IGN] GAMIT
[Termes IGN] GIPSY-OASIS
[Termes IGN] gradient de troposphère
[Termes IGN] meso échelle
[Termes IGN] modèle atmosphérique
[Termes IGN] Niger
[Termes IGN] propagation troposphérique
[Termes IGN] résidu
[Termes IGN] retard troposphérique zénithal
[Termes IGN] signal GPSRésumé : (Auteur) This study analyzes the characteristics of GPS tropospheric estimates (zenith wet delays – ZWDs, gradients, and post-fit phase residuals) during the passage of mesoscale convective systems (MCSs) and evaluates their sensitivity to the research-level GPS data processing strategy implemented. Here, we focus on MCS events observed during the monsoon season of West Africa. This region is particularly well suited for the study of these events due to the high frequency of MCS occurrences in the contrasting climatic environments between the Guinean coast and the Sahel. This contrast is well sampled with data generated by six African Monsoon Multidisciplinary Analysis (AMMA) GPS stations. Tropospheric estimates for a 3-year period (2006–2008), processed with both the GAMIT and GIPSY-OASIS software packages, were analyzed and intercompared. First, the case of a MCS that passed over Niamey, Niger, on 11 August 2006 demonstrates a strong impact of the MCS on GPS estimates and post-fit residuals when the GPS signals propagate through the convective cells as detected on reflectivity maps from the MIT C-band Doppler radar. The estimates are also capable of detecting changes in the structure and dynamics of the MCS. However, the sensitivity is different depending on the tropospheric modeling approach adopted in the software. With GIPSY-OASIS, the high temporal sampling (5 min) of ZWDs and gradients is well suited for detecting the small-scale, short-lived, convective cells, while the post-fit residuals remain quite small. With GAMIT, the lower temporal sampling of the estimated parameters (hourly for ZWDs and daily for gradients) is not sufficient to capture the rapid delay variations associated with the passage of the MCS, but the post-fit phase residuals clearly reflect the presence of a strong refractivity anomaly. The results are generalized with a composite analysis of 414 MCS events observed over the 3-year period at the six GPS stations with the GIPSY-OASIS estimates. A systematic peak is found in the ZWDs coincident with the cold pool crossing time associated with the MCSs. The tropospheric gradients reflect the path of the MCS propagation (generally from east to west). This study concludes that ZWDs, gradients, and post-fit phase residuals provide relevant and complementary information on MCSs passing over or in the vicinity of a GPS station. Numéro de notice : A2019-572 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/acp-19-9541-2019 Date de publication en ligne : 29/07/2019 En ligne : https://doi.org/10.5194/acp-19-9541-2019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94444
in Atmospheric chemistry and physics > vol 19 n° 14 (July 2019) . - pp 9541 - 9561[article]Comprehensive evaluation of soil moisture retrieval models under different crop cover types using C-band synthetic aperture radar data / P. Kumar in Geocarto international, vol 34 n° 9 ([15/06/2019])
[article]
Titre : Comprehensive evaluation of soil moisture retrieval models under different crop cover types using C-band synthetic aperture radar data Type de document : Article/Communication Auteurs : P. Kumar, Auteur ; A. Choudhary, Auteur ; D. K. Gupta, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 1022-1041 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande C
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] couvert végétal
[Termes IGN] échantillonnage d'image
[Termes IGN] humidité du sol
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] image Sentinel-SAR
[Termes IGN] modèle de régression
[Termes IGN] polarisation
[Termes IGN] réseau neuronal artificiel
[Termes IGN] Uttar Pradesh (Inde ; état)Résumé : (auteur) In the present study, random forest regression (RFR), support vector regression (SVR) and artificial neural network regression (ANNR) models were evaluated for the retrieval of soil moisture covered by winter wheat, barley and corn crops. SVR with radial basis function kernel was provided the highest adj. R2 (0.95) value for soil moisture retrieval covered by the wheat crop at VV polarization. However, RFR provided the adj. R2 (0.94) value for soil moisture retrieval covered by barley crop at VV polarization using Sentinel-1A satellite data. The adj. R2 (0.94) values were found for the soil moisture covered by corn crop at VV polarization using RFR, SVR linear and radial basis function kernels. The least performance was reported using ANNR model for almost all the crops under investigation. The soil moisture retrieval outcomes were found better at VV polarization in comparison to VH polarization using three different models. Numéro de notice : A2019-517 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1464601 Date de publication en ligne : 03/05/2018 En ligne : https://doi.org/10.1080/10106049.2018.1464601 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93876
in Geocarto international > vol 34 n° 9 [15/06/2019] . - pp 1022-1041[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2019091 RAB Revue Centre de documentation En réserve L003 Disponible Using Sentinel-1A DInSAR interferometry and Landsat 8 data for monitoring water level changes in two lakes in Crete, Greece / D.D. Alexakis in Geocarto international, vol 34 n° 7 ([01/06/2019])
[article]
Titre : Using Sentinel-1A DInSAR interferometry and Landsat 8 data for monitoring water level changes in two lakes in Crete, Greece Type de document : Article/Communication Auteurs : D.D. Alexakis, Auteur ; E.G. Stavroulaki, Auteur ; I.K. Tsanis, Auteur Année de publication : 2019 Article en page(s) : pp 703 - 721 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande C
[Termes IGN] Crète (île)
[Termes IGN] données polarimétriques
[Termes IGN] image Landsat-8
[Termes IGN] image multitemporelle
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] lac
[Termes IGN] niveau de l'eau
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surveillance hydrologiqueRésumé : (auteur) Differential Interferometric Synthetic Aperture Radar (DInSAR) methodology has been successfully employed to detect water level changes and produce corresponding water level variation maps. In this study, Agia and Kournas lakes, located in Western Crete, Greece, were used as pilot areas to monitor water level change with means of SAR interferometry and auxiliary Earth Observation (EO) data. The water level variation was monitored for the period 2015–2016, using Sentinel-1A imageries and corresponding stage water level data. Landsat 8 data were additionally used to study vegetation regime and surface water extent and how these parameters affect interferograms performance. The results highlighted the fact that the combination of SAR backscattering intensity and unwrapped phase can provide additional insight into hydrological studies. The overall analysis of both interferometric characteristics and backscattering mechanism denoted their potential in enhancing the reliability of the water-level retrieval scheme and optimizing the capture of hydrological patterns spatial distribution. Numéro de notice : A2019-512 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1434685 Date de publication en ligne : 11/02/2018 En ligne : https://doi.org/10.1080/10106049.2018.1434685 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93821
in Geocarto international > vol 34 n° 7 [01/06/2019] . - pp 703 - 721[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2019071 RAB Livre Centre de documentation En réserve L003 Disponible Developing a subswath-based wind speed retrieval model for sentinel-1 VH-Polarized SAR data over the ocean surface / Kangyu Zhang in IEEE Transactions on geoscience and remote sensing, vol 57 n° 3 (March 2019)
[article]
Titre : Developing a subswath-based wind speed retrieval model for sentinel-1 VH-Polarized SAR data over the ocean surface Type de document : Article/Communication Auteurs : Kangyu Zhang, Auteur ; Jingfeng Huang, Auteur ; Lamin R. Mansaray, Auteur ; Qiaoying Guo, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 1561 - 1572 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande C
[Termes IGN] données polarimétriques
[Termes IGN] image Sentinel-SAR
[Termes IGN] polarimétrie radar
[Termes IGN] surface de la mer
[Termes IGN] vent
[Termes IGN] vitesseRésumé : (Auteur) This paper evaluates the capability of Sentinel-1 VH-polarized synthetic aperture radar signals, involving 738 scenes in the interferometric wide swath (IW) mode, for ocean surface wind speed retrieval using a novel subswath-based C-band cross-polarized ocean model. When compared with in situ measurements, it is observed that wind speed retrieval accuracy varies progressively along swath, with the most accurate wind speed retrievals being derived from subswath 3 [root-mean-square error (RMSE) of 1.82 m · s -1 ], followed by subswath 2 (RMSE of 1.92 m · s -1 ), while subswath 1 showed the lowest retrieval accuracy (RMSE of 2.37 m · s -1 ). The average RMSE of wind speeds retrieved from all the three subswaths is 2.08 m · s -1 under low-to-high wind speed regimes (wind speeds Numéro de notice : A2019-130 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2867438 Date de publication en ligne : 20/09/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2867438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92459
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 3 (March 2019) . - pp 1561 - 1572[article]Performance analysis of dual-frequency receiver using combinations of GPS L1, L5, and L2 civil signals / Padma Bolla in Journal of geodesy, vol 93 n° 3 (March 2019)PermalinkRadiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols / Sen Cao in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)PermalinkGeneration of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar / Yang Lei in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)PermalinkA modeling-based approach for soil frost detection in the northern boreal forest region with C-Band SAR / Juval Cohen in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)PermalinkSynergetic efficiency of Lidar and WorldView-2 for 3D urban cartography in Northeast Mexico / Fabiola D. Yepez-Rincon in Geocarto international, vol 34 n° 2 ([01/02/2019])PermalinkEarth observation, remote sensing and geoscientific ground investigations for archaeological and heritage research / Deodato Tapete (2019)PermalinkEvaluating SAR-optical sensor fusion for aboveground biomass estimation in a Brazilian tropical forest / Aline Bernarda Debastiani in Annals of forest research, vol 62 n° 1 (January - June 2019)PermalinkGeographic Information Systems in Geospatial Intelligence, ch. 5. Spectral optimization of airborne multispectral camera for land cover classification: automatic feature selection and spectral band clustering / Arnaud Le Bris (2019)PermalinkMicrowave indices from active and passive sensors for remote sensing applications / Emanuele Santi (2019)PermalinkPermalink