Centre dedocumentation
scientifique

An open science and open data approach for the statistically robust estimation of forest disturbance areas / Saverio Francini in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 106 (February 2022) . - n° 102663 Titre : An open science and open data approach for the statistically robust estimation of forest disturbance areas Type de document : Article/Communication Auteurs : Saverio Francini, Auteur ; Ronald E. McRoberts, Auteur ; Giovanni d' Amico, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102663 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] changement climatique [Termes IGN] coupe rase (sylviculture) [Termes IGN] détection de changement [Termes IGN] estimation statistique [Termes IGN] Fagus sylvatica [Termes IGN] Google Earth Engine [Termes IGN] image Sentinel-MSI [Termes IGN] Italie [Termes IGN] méthode robuste [Termes IGN] perturbation écologique [Termes IGN] Quercus cerris [Termes IGN] Quercus pedunculata [Termes IGN] Quercus pubescens [Termes IGN] Quercus sessiliflora [Termes IGN] surveillance forestière Résumé : (auteur) Forest disturbance monitoring is critical for understanding forest-related greenhouse gas emissions and for determining the role of forest management in mitigating climate change. Multiple algorithms for the automated mapping of forest disturbance using remotely sensed imagery have been developed and applied; however, variability in natural and anthropogenic disturbance phenomena, as well as image acquisition conditions, can result in maps that may be incomplete or that contain inaccuracies that prevent their use for directly estimating areas of disturbance. To reduce errors in reporting disturbance areas, stratified estimators can be applied to obtain statistically robust area estimates, while simultaneously circumventing the need to conduct a complete census or in situations where such a census may not be possible. We present a semi-automated procedure for implementation in Google Earth Engine, 3I3D-GEE, for regional to global mapping of forest disturbance (including clear-cut harvesting, fire, and wind damage) and sample-based estimation of related areas using data from the processing capacity of Google Earth Engine. Documentation for the application is also provided in Appendix A. Using Sentinel-2 (S2) imagery, our procedure was applied and tested for 2018 in Italy for which the approximately 11 million ha of forests (mostly Q. pubescens, Q. robur, Q. cerris, Q. petraea, and Fagus sylvatica) serve as an appropriate case study because national statistics on forest disturbance areas are not available. To decrease the overall standard errors of the area estimates, the sampling intensities in areas where greater variability in the form of greater commission and omission errors are expected can be increased. To this end, we augmented the predicted forest disturbance map with a buffer class consisting of a two-pixel buffer (20 m) on each side of the disturbance class boundary. We selected a reference sample of 19,300 points: a simple random sample of 9,300 points from the buffer and simple random samples of 5000 from each of the undisturbed and disturbed classes. The reference sample was photointerpreted using fine resolution orthophotos (30 cm) and S2 imagery. While the estimate of the disturbed area obtained by adding the areas of pixels classified as disturbed was 41,732 ha, the estimate obtained using the unbiased stratified estimator was 27% greater at 57,717716 ha. Regarding map accuracy, we found several omission errors in the buffer (53.4%) but none (0%) in the undisturbed map class. Similarly, among the 1035 commission errors, the majority (7 4 4) were in the buffer class. The methods presented herein provide a useful tool that can be used to estimate areas of forest disturbance, which many nations must report as part of their commitment to international conventions and treaties. In addition, the information generated can support forest management, enabling the forest sector to monitor stand-replacing forest harvesting over space and time. Numéro de notice : A2022-072 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2021.102663 En ligne : https://doi.org/10.1016/j.jag.2021.102663 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99437 [article]

Flood mapping using multi-temporal Sentinel-1 SAR images: A case study—Inaouene watershed from Northeast of Morocco / Brahim Benzougagh in Iranian Journal of Science and Technology - Transactions of Civil Engineering, n° inconnu (2021)  

Public [article]  inIranian Journal of Science and Technology - Transactions of Civil Engineering > n° inconnu (2021) . - n° inconnu Titre : Flood mapping using multi-temporal Sentinel-1 SAR images: A case study—Inaouene watershed from Northeast of Morocco Type de document : Article/Communication Auteurs : Brahim Benzougagh, Auteur ; Pierre-Louis Frison , Auteur ; Sarita Gajbhiye Meshram, Auteur ; Larbi Boudad, Auteur ; Abdallah Dridri, Auteur ; Driss Sadkaoui, Auteur ; Khalid Mimich, Auteur ; Khaled Mohamed Khedher, Auteur Année de publication : 2022 Article en page(s) : n° inconnu Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bassin hydrographique [Termes IGN] cartographie des risques [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] inondation [Termes IGN] Maroc [Termes IGN] plan de prévention des risques [Termes IGN] prévention des risques [Termes IGN] risque naturel Résumé : (auteur) Natural disasters like floods are happening worldwide. Due to their negative impact on different social, economic and environmental aspects need to monitor and map these phenomena have increased. In fact, to access the zones affected by the flood, we use open source remote sensing (RS) images acquired by optical and radar sensors. Furthermore, we present a method using Sentinel-1 images; we suggest applying Ground Range Detected (GRD) images. For this purpose, pre-processed built and provided by the European Space Agency (ESA), preserved by free software Sentinel Application Platform (SNAP) for data extraction around appropriate demand. Moreover, the principal objective of this article is to assess the capability of Sentinel-1 Synthetic Aperture Radar (SAR) images in order to visualize flood areas in the Inaouene watershed located in north-eastern of Morocco. The origin of this natural hazard is the combination of natural and anthropogenic factors that makes the watershed vulnerable with a sub-annual frequency. The results of this work help decision-makers and managers in the field of natural risk management and land-use planning to implement a strategy and action plan for the protection of the populations and the environment against the negative impact of floods. Numéro de notice : A2021-937 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.1007/s40996-021-00683-y Date de publication en ligne : 18/06/2021 En ligne : https://doi.org/10.1007/s40996-021-00683-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99581 [article]

Automatic extraction of damaged houses by earthquake based on improved YOLOv5: A case study in Yangbi / Yafei Jing in Remote sensing, vol 14 n° 2 (January 2 2022)  

Public [article]  inRemote sensing > vol 14 n° 2 (January 2 2022) . - n° 382 Titre : Automatic extraction of damaged houses by earthquake based on improved YOLOv5: A case study in Yangbi Type de document : Article/Communication Auteurs : Yafei Jing, Auteur ; Yuhuan Ren, Auteur ; Yalan Liu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 382 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] détection d'objet [Termes IGN] détection de cible [Termes IGN] dommage matériel [Termes IGN] extraction automatique [Termes IGN] image captée par drone [Termes IGN] orthoimage [Termes IGN] séisme [Termes IGN] Yunnan (Chine) Résumé : (auteur) Efficiently and automatically acquiring information on earthquake damage through remote sensing has posed great challenges because the classical methods of detecting houses damaged by destructive earthquakes are often both time consuming and low in accuracy. A series of deep-learning-based techniques have been developed and recent studies have demonstrated their high intelligence for automatic target extraction for natural and remote sensing images. For the detection of small artificial targets, current studies show that You Only Look Once (YOLO) has a good performance in aerial and Unmanned Aerial Vehicle (UAV) images. However, less work has been conducted on the extraction of damaged houses. In this study, we propose a YOLOv5s-ViT-BiFPN-based neural network for the detection of rural houses. Specifically, to enhance the feature information of damaged houses from the global information of the feature map, we introduce the Vision Transformer into the feature extraction network. Furthermore, regarding the scale differences for damaged houses in UAV images due to the changes in flying height, we apply the Bi-Directional Feature Pyramid Network (BiFPN) for multi-scale feature fusion to aggregate features with different resolutions and test the model. We took the 2021 Yangbi earthquake with a surface wave magnitude (Ms) of 6.4 in Yunan, China, as an example; the results show that the proposed model presents a better performance, with the average precision (AP) being increased by 9.31% and 1.23% compared to YOLOv3 and YOLOv5s, respectively, and a detection speed of 80 FPS, which is 2.96 times faster than YOLOv3. In addition, the transferability test for five other areas showed that the average accuracy was 91.23% and the total processing time was 4 min, while 100 min were needed for professional visual interpreters. The experimental results demonstrate that the YOLOv5s-ViT-BiFPN model can automatically detect damaged rural houses due to destructive earthquakes in UAV images with a good performance in terms of accuracy and timeliness, as well as being robust and transferable. Numéro de notice : A2022-104 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14020382 Date de publication en ligne : 14/01/2022 En ligne : https://doi.org/10.3390/rs14020382 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99577 [article]

Co-seismic ionospheric disturbances following the 2016 West Sumatra and 2018 Palu earthquakes from GPS and GLONASS measurements / Mokhamad Nur Cahyadi in Remote sensing, vol 14 n° 2 (January 2 2022)  

Public [article]  inRemote sensing > vol 14 n° 2 (January 2 2022) . - n° 401 Titre : Co-seismic ionospheric disturbances following the 2016 West Sumatra and 2018 Palu earthquakes from GPS and GLONASS measurements Type de document : Article/Communication Auteurs : Mokhamad Nur Cahyadi, Auteur ; Buldan Muslim, Auteur ; Danar Guruh Pratomo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 401 Note générale : biliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] déformation verticale de la croute terrestre [Termes IGN] diffusion de Rayleigh [Termes IGN] données GLONASS [Termes IGN] données GNSS [Termes IGN] Indonésie [Termes IGN] onde acoustique [Termes IGN] perturbation ionosphérique [Termes IGN] propagation ionosphérique [Termes IGN] séisme [Termes IGN] Sumatra [Termes IGN] teneur totale en électrons [Termes IGN] tsunami Résumé : (auteur) The study of ionospheric disturbances associated with the two large strike-slip earthquakes in Indonesia was investigated, which are West Sumatra on 2 March 2016 (Mw = 7.8), and Palu on 28 September 2018 (Mw = 7.5). The anomalies were observed by measuring co-seismic ionospheric disturbances (CIDs) using the Global Navigation Satellite System (GNSS). The results show positive and negative CIDs polarization changes for the 2016 West Sumatra earthquake, depending on the position of the satellite line-of-sight, while the 2018 Palu earthquake shows negative changes only due to differences in co-seismic vertical crustal displacement. The 2016 West Sumatra earthquake caused uplift and subsidence, while the 2018 Palu earthquake was dominated by subsidence. TEC anomalies occurred about 10 to 15 min after the two earthquakes with amplitude of 2.9 TECU and 0.4 TECU, respectively. The TEC anomaly amplitude was also affected by the magnitude of the earthquake moment. The disturbance signal propagated with a velocity of ~1–1.72 km s−1 for the 2016 West Sumatra earthquake and ~0.97–1.08 km s−1 for the 2018 Palu mainshock earthquake, which are consistent with acoustic waves. The wave also caused an oscillation signal of ∼4 mHz, and their azimuthal asymmetry of propagation confirmed the phenomena in the Southern Hemisphere. The CID signal could be identified at a distance of around 400–1500 km from the epicenter in the southwestern direction. Numéro de notice : A2022-103 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.3390/rs14020401 Date de publication en ligne : 16/01/2022 En ligne : https://doi.org/10.3390/rs14020401 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99571 [article]

Monitoring and analysis of crop irrigation dynamics in Central Italy through the use of MODIS NDVI data / Marta Chiesi in European journal of remote sensing, vol 55 n° 1 (January 2022)  

Public [article]  inEuropean journal of remote sensing > vol 55 n° 1 (January 2022) . - pp 23 - 36 Titre : Monitoring and analysis of crop irrigation dynamics in Central Italy through the use of MODIS NDVI data Type de document : Article/Communication Auteurs : Marta Chiesi, Auteur ; Luca Angeli, Auteur ; Piero Battista, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 23 - 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bilan hydrique [Termes IGN] carte agricole [Termes IGN] cultures irriguées [Termes IGN] image Aqua-MODIS [Termes IGN] image Sentinel-MSI [Termes IGN] image Terra-MODIS [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Toscane (Italie) Résumé : (auteur) A recent study has proposed and tested a semi-empirical method to estimate crop irrigation based on a water balance logic and Sentinel-2 Multi Spectral Instrument (MSI) NDVI imagery. The current paper aims at extending the same approach to the analysis of the main irrigation patterns occurred in Tuscany (Central Italy) during the 2000–2019 period. This operation was made possible by feeding the irrigation water (IW) estimation method with 250-m spatial resolution Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI images. The results of this operation were first assessed versus various reference datasets available for the region; next, the annual maps of IW estimated for the 20 study years were analyzed at province scale in conjunction with relevant agricultural statistics. The use of MODIS in place of MSI images reduces the IW estimation accuracy irregularly at local scale, depending on the size and spatial arrangement of irrigated and non-irrigated fields; the reduction in accuracy is, however, marginal over relatively large areas. Irrigated crops are decreasing throughout most Tuscany provinces, while they are increasing in the most southern and driest province. The possible reasons and implications of these findings are finally discussed in relation to the main environmental issues affecting the region. Numéro de notice : A2022-099 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2021.2013735 Date de publication en ligne : 05/01/2022 En ligne : https://doi.org/10.1080/22797254.2021.2013735 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99549 [article]

Fast local adaptive multiscale image matching algorithm for remote sensing image correlation / Niccolò Dematteis in Computers & geosciences, vol 159 (February 2022)  

Permalink

Latent heat flux variability and response to drought stress of black poplar: A multi-platform multi-sensor remote and proximal sensing approach to relieve the data scarcity bottleneck / Flavia Tauro in Remote sensing of environment, vol 268 (January 2022)  

Permalink

MLMT-CNN for object detection and segmentation in multi-layer and multi-spectral images / Majedaldein Almahasneh in Machine Vision and Applications, vol 33 n° 1 (January 2022)  

Permalink

Competition and climate influence in the basal area increment models for Mediterranean mixed forests / Diego Rodríguez de Prado in Forest ecology and management, vol 506 (15 February 2022)  

Permalink

Fungal perspective of pine and oak colonization in Mediterranean degraded ecosystems / Irene Adamo in Forests, vol 13 n° 1 (January 2022)  

Permalink

Detection of windthrown tree stems on UAV-orthomosaics using U-Net convolutional networks / Stefan Reder in Remote sensing, vol 14 n° 1 (January-1 2022)  

Permalink

A GIS-based landslide susceptibility mapping and variable importance analysis using artificial intelligent training-based methods / Pengxiang Zhao in Remote sensing, vol 14 n° 1 (January-1 2022)  

Permalink

Multi-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana / Ram Avtar in Geocarto international, vol 37 n° 2 ([06/01/2022])  

Permalink

Comparison of atmospheric mass density models using a new data source: COSMIC satellite ephemerides / Yang Yang in IEEE Aerospace and Electronic Systems Magazine, vol 37 n° inconnu ([04/01/2022])  

Permalink

Growing stock monitoring by European National Forest Inventories: Historical origins, current methods and harmonisation / Thomas Gschwantner in Forest ecology and management, vol 505 (1 February 2022)  

Permalink