Centre dedocumentation
scientifique

Fusion of SAR and multi-spectral time series for determination of water table depth and lake area in peatlands / Katrin Krzepek in PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, vol 90 n° 6 (December 2022)  

Public [article]  inPFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science > vol 90 n° 6 (December 2022) . - pp 561 - 575 Titre : Fusion of SAR and multi-spectral time series for determination of water table depth and lake area in peatlands Type de document : Article/Communication Auteurs : Katrin Krzepek, Auteur ; Jacob Schmidt, Auteur ; Dorota Iwaszczuk, Auteur Année de publication : 2022 Article en page(s) : pp 561 - 575 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] apprentissage non-dirigé [Termes IGN] aquifère [Termes IGN] Bade-Wurtemberg (Allemagne) [Termes IGN] bande C [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] fusion d'images [Termes IGN] image multibande [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] Normalized Difference Water Index [Termes IGN] puits de carbone [Termes IGN] seuillage d'image [Termes IGN] théorie de Dempster-Shafer [Termes IGN] tourbière Résumé : (auteur) Peatlands as natural carbon sinks have a major impact on the climate balance and should therefore be monitored and protected. The hydrology of the peatland serves as an indicator of the carbon storage capacity. Hence, we investigate the question how suitable different remote sensing data are for monitoring the size of open water surface and the water table depth (WTD) of a peatland ecosystem. Furthermore, we examine the potential of combining remote sensing data for this purpose. We use C-band synthetic aperture radar (SAR) data from Sentinel-1 and multi-spectral data from Sentinel-2. The radar backscatter σ0, the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) are calculated and used for consideration of the WTD and the lake size. For the measurement of the lake size, we implement and investigate the methods: random forest, adaptive thresholding and an analysis according to the Dempster–Shafer theory. Correlations between WTD and the remote sensing data σ0 as well as NDWI are investigated. When looking at the individual data sets the results of our case study show that the VH polarized σ0 data produces the clearest delineation of the peatland lake. However the adaptive thresholding of the weighted fusion image of σ0-VH, σ0-VV and MNDWI, and the random forest algorithm with all three data sets as input proves to be the most suitable for determining the lake area. The correlation coefficients between σ0/NDWI and WTD vary greatly and lie in ranges of low to moderate correlation. Numéro de notice : A2022-942 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s41064-022-00216-w Date de publication en ligne : 06/09/2022 En ligne : https://doi.org/10.1007/s41064-022-00216-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102876 [article]

Multi-modal temporal attention models for crop mapping from satellite time series / Vivien Sainte Fare Garnot in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 187 (May 2022) . - pp 294 - 305 Titre : Multi-modal temporal attention models for crop mapping from satellite time series Type de document : Article/Communication Auteurs : Vivien Sainte Fare Garnot , Auteur ; Loïc Landrieu , Auteur ; Nesrine Chehata , Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : pp 294 - 305 Note générale : bibliographie This work was partly supported by ASP, the French Payment Agency. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] attention (apprentissage automatique) [Termes IGN] bande C [Termes IGN] carte agricole [Termes IGN] fusion d'images [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] parcelle agricole [Termes IGN] Pastis [Termes IGN] segmentation d'image [Termes IGN] série temporelle [Termes IGN] surface cultivée Résumé : (auteur) Optical and radar satellite time series are synergetic: optical images contain rich spectral information, while C-band radar captures useful geometrical information and is immune to cloud cover. Motivated by the recent success of temporal attention-based methods across multiple crop mapping tasks, we propose to investigate how these models can be adapted to operate on several modalities. We implement and evaluate multiple fusion schemes, including a novel approach and simple adjustments to the training procedure, significantly improving performance and efficiency with little added complexity. We show that most fusion schemes have advantages and drawbacks, making them relevant for specific settings. We then evaluate the benefit of multimodality across several tasks: parcel classification, pixel-based segmentation, and panoptic parcel segmentation. We show that by leveraging both optical and radar time series, multimodal temporal attention-based models can outmatch single-modality models in terms of performance and resilience to cloud cover. To conduct these experiments, we augment the PASTIS dataset (Garnot and Landrieu, 2021a) with spatially aligned radar image time series. The resulting dataset, PASTIS-R, constitutes the first large-scale, multimodal, and open-access satellite time series dataset with semantic and instance annotations. (Dataset available at: https://zenodo.org/record/5735646) Numéro de notice : A2022-157 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers ArXiv Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.03.012 Date de publication en ligne : 24/03/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.03.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100365 [article]

Voir aussi

• Multi-modal temporal attention models for crop mapping from satellite time series / Vivien Sainte Fare Garnot (2021)  

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2022051	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2022053	DEP-RECP	Revue	LaSTIG	Dépôt en unité	Exclu du prêt
081-2022052	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Examining the integration of Landsat operational land imager with Sentinel-1 and vegetation indices in mapping southern yellow pines (Loblolly, Shortleaf, and Virginia pines) / Clement E. Akumu in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 1 (January 2022) . - pp 29 - 38 Titre : Examining the integration of Landsat operational land imager with Sentinel-1 and vegetation indices in mapping southern yellow pines (Loblolly, Shortleaf, and Virginia pines) Type de document : Article/Communication Auteurs : Clement E. Akumu, Auteur ; Eze O. Amadi, Auteur Année de publication : 2022 Article en page(s) : pp 29 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] bande C [Termes IGN] canopée [Termes IGN] carte de la végétation [Termes IGN] coefficient de rétrodiffusion [Termes IGN] image Landsat-OLI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de végétation [Termes IGN] intégration de données [Termes IGN] inventaire forestier local [Termes IGN] Pinus (genre) [Termes IGN] Pinus ponderosa [Termes IGN] précision de la classification [Termes IGN] Soil Adjusted Vegetation Index Résumé : (Auteur) The mapping of southern yellow pines (loblolly, shortleaf, and Virginia pines) is important to supporting forest inventory and the management of forest resources. The overall aim of this study was to examine the integration of Landsat Operational Land Imager (OLI ) optical data with Sentinel-1 microwave C-band satellite data and vegetation indices in mapping the canopy cover of southern yellow pines. Specifically, this study assessed the overall mapping accuracies of the canopy cover classification of southern yellow pines derived using four data-integration scenarios: Landsat OLI alone; Landsat OLI and Sentinel-1; Landsat OLI with vegetation indices derived from satellite data—normalized difference vegetation index, soil-adjusted vegetation index, modified soil-adjusted vegetation index, transformed soil-adjusted vegetation index, and infrared percentage vegetation index; and 4) Landsat OLI with Sentinel-1 and vegetation indices. The results showed that the integration of Landsat OLI reflectance bands with Sentinel-1 backscattering coefficients and vegetation indices yielded the best overall classification accuracy, about 77%, and standalone Landsat OLI the weakest accuracy, approximately 67%. The findings in this study demonstrate that the addition of backscattering coefficients from Sentinel-1 and vegetation indices positively contributed to the mapping of southern yellow pines. Numéro de notice : A2022-062 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00024R2 Date de publication en ligne : 01/01/2022 En ligne : https://doi.org/10.14358/PERS.21-00024R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99706 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2022011	SL	Revue	Centre de documentation	Revues en salle	Disponible

In situ C-band data for wheat physiological functioning monitoring in the South Mediterranean region / Nadia Ouaadi (2022)  

Public Titre : In situ C-band data for wheat physiological functioning monitoring in the South Mediterranean region Type de document : Article/Communication Auteurs : Nadia Ouaadi, Auteur ; Ludovic Villard, Auteur ; Saïd Khabba, Auteur ; Pierre-Louis Frison , Auteur ; Jamal Ezzahar, Auteur ; Mohamed Kasbani, Auteur ; Adnane Chakir , Auteur ; Pascal Fanise, Auteur ; Valérie Le Dantec, Auteur ; Mehrez Zribi, Auteur ; Salah Er-Raki, Auteur ; Lionel Jarlan, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2022 Projets : 2-Pas d'info accessible - article non ouvert / Conférence : IGARSS 2022, IEEE International Geoscience And Remote Sensing Symposium 17/07/2022 22/07/2022 Kuala Lumpur Malaysie Proceedings IEEE Importance : pp 4951 - 4954 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] blé (céréale) [Termes IGN] coefficient de rétrodiffusion [Termes IGN] cohérence photométrique [Termes IGN] variation diurne Résumé : (auteur) Irrigated agriculture is the largest consumer of freshwater in the world, particularly in the South Mediterranean region that is already suffering from water shortages. Monitoring the water stress status of plants can contribute to an optimal use of irrigation. C-band radar data have shown great potential for monitoring soil and vegetation hydric conditions. While a diurnal cycle up to 1 dB has been observed over tropical forests, the behavior of annual crops is yet to be investigated. In this context, an experiment composed of a radar setup with 6 C-band antennas was installed in Morocco over a wheat field. 15 minutes full polarization acquisitions of the backscattering coefficient and the interferometric coherence are analyzed in relation with the physiological functioning of wheat. In this paper, the first results from the analysis of data collected during the 2020 growing season are presented. The results reveal the existence of a diurnal cycle of the interferometric coherence and the backscattering coefficient (up to 0.45 and 1.5 dB, respectively) with amplitudes increase in relation with vegetation development. Numéro de notice : C2022-041 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS46834.2022.9884289 Date de publication en ligne : 28/09/2022 En ligne : https://doi.org/10.1109/IGARSS46834.2022.9884289 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101769

Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations / Caglar Bayik in Natural Hazards, vol 109 n° 1 (October 2021)  

Public [article]  inNatural Hazards > vol 109 n° 1 (October 2021) . - pp 1201 - 1220 Titre : Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations Type de document : Article/Communication Auteurs : Caglar Bayik, Auteur ; Saygin Abdikan, Auteur ; Alpay Ozdemir, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1201 - 1220 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse diachronique [Termes IGN] bande C [Termes IGN] bande L [Termes IGN] données géologiques [Termes IGN] données GNSS [Termes IGN] effondrement de terrain [Termes IGN] image ALOS [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] Istanbul (Turquie) [Termes IGN] surveillance géologique [Termes IGN] urbanisation Résumé : (auteur) This study aims to detect recent landslide displacements caused by geological structure of the region where there is intense urbanization using advanced Interferometric Synthetic Aperture Radar (InSAR) techniques and with Global Navigation Satellite Systems (GNSS) observations in the Beylikdüzü and Esenyurt districts in Istanbul megacity, Turkey. In this study, multiple satellites with different frequencies (C-band, L-band) and periodic GNSS observations were employed. For the entire peninsula, we processed 149 images from the ascending orbit, 144 images from the descending orbit of Sentinel-1 (C-Band) and 24 ALOS-2 (L-band) images from the ascending orbit. The evaluations were carried out in the period between 2015 and 2020 for Sentinel-1 imagery and 2015–2020 for ALOS-2 imagery respectively. Since the study area is covered by dense settlements, the Persistent Scatterer InSAR (PSI) technique was utilized to determine the landslide behaviors. According to the results, for both orbits of the Sentinel-1, the horizontal displacement and the vertical displacement were observed in the range of − 10 to 6 mm. Compared to the magnitude of displacement signal measured by Sentinel-1, ALOS-2 data has higher values due to the high surface penetration of the L-band. The results showed that most of the old landslide regions are reactivated. Horizontal movement derived through Sentinel-1 showed that the highest movement overlaps with old landslides. L-band ALOS-2 provided better spatial coverage of landslide movement than C-band Sentinel-1 data, especially at the rural Numéro de notice : A2021-752 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT/URBANISME Nature : Article DOI : 10.1007/s11069-021-04875-7 Date de publication en ligne : 20/06/2021 En ligne : https://doi.org/10.1007/s11069-021-04875-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98737 [article]

Sentinel-1 sensitivity to soil moisture at high incidence angle and the impact on retrieval over seasonal crops / Davide Palmisano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

Permalink

Estimation of surface deformation due to Pasni earthquake using RADAR interferometry / Muhammad Ali in Geocarto international, vol 36 n° 14 ([01/08/2021])  

Permalink

Aboveground biomass estimates of tropical mangrove forest using Sentinel-1 SAR coherence data : The superiority of deep learning over a semi-empirical model / S.M. Ghosh in Computers & geosciences, vol 150 (May 2021)  

Permalink

A soil texture categorization mapping from empirical and semi-empirical modelling of target parameters of synthetic aperture radar / Shoba Periasamy in Geocarto international, vol 36 n° 5 ([15/03/2021])  

Permalink

Cluster-based empirical tropospheric corrections applied to InSAR time series analysis / Kyle Dennis Murray in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

Permalink

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)  

Permalink

Deep learning for wildfire progression monitoring using SAR and optical satellite image time series / Puzhao Zhang (2021)  

Permalink

Diurnal cycles of C-band temporal coherence and backscattering coefficient over an olive orchard in a semi-arid area: Comparison of in situ and Sentinel-1 radar observations / Adnane Chakir (2021)  

Permalink

Diurnal cycles of C-band temporal coherence and backscattering coefficient over a wheat field in a semi-arid area / Nadia Ouaadi (2021)  

Permalink

Flood mapping from radar remote sensing using automated image classification techniques / Lisa Landuyt (2021)  

Permalink