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scientifique

Mapping active paddy rice area over monsoon asia using time-series Sentinel-2 images in Google earth engine : a case study over lower gangetic plain / Arabinda Maiti in Geocarto international, vol 38 n° inconnu ([01/01/2023])  

Public [article]  inGeocarto international > vol 38 n° inconnu [01/01/2023] Titre : Mapping active paddy rice area over monsoon asia using time-series Sentinel-2 images in Google earth engine : a case study over lower gangetic plain Type de document : Article/Communication Auteurs : Arabinda Maiti, Auteur ; Prasenjit Acharya, Auteur ; Srikanta Sannigrahi, Auteur ; et al., Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte thématique [Termes IGN] Gange (fleuve) [Termes IGN] Google Earth Engine [Termes IGN] image Sentinel-SAR [Termes IGN] Inde [Termes IGN] mousson [Termes IGN] plaine [Termes IGN] rizière Résumé : (auteur) We proposed a modification of the existing approach for mapping active paddy rice fields in monsoon-dominated areas. In the existing PPPM approach, LSWI higher than EVI at the transplantation stage enables the identification of rice fields. However, it fails to recognize the fields submerged later due to monsoon floods. In the proposed approach (IPPPM), the submerged fields, at the maximum greenness time, were excluded for better estimation. Sentinel–2A/2B time-series images were used for the year 2018 to map paddy rice over the Lower Gangetic Plain (LGP) using Google earth engine (GEE). The overall accuracy (OA) obtained from IPPPM was 85%. Further comparison with the statistical data reveals the IPPPM underestimates (slope (β1) = 0.77) the total reported paddy rice area, though R2 remains close to 0.9. The findings provide a basis for near real-time mapping of active paddy rice areas for addressing the issues of production and food security. Numéro de notice : A2022-924 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10106049.2022.2032396 En ligne : https://doi.org/10.1080/10106049.2022.2032396 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99963 [article]

Mitigating the risk of wind damage at the forest landscape level by using stand neighbourhood and terrain elevation information in forest planning / Roope Ruotsalainen in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)  

Public [article]  inForestry, an international journal of forest research > vol 96 n° 1 (January 2023) . - pp 121 - 134 Titre : Mitigating the risk of wind damage at the forest landscape level by using stand neighbourhood and terrain elevation information in forest planning Type de document : Article/Communication Auteurs : Roope Ruotsalainen, Auteur ; Timo Pukkala, Auteur ; Veli-Pekka Ikonen, Auteur Année de publication : 2023 Article en page(s) : pp 121 - 134 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] altitude [Termes IGN] canopée [Termes IGN] dommage forestier causé par facteurs naturels [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] gestion forestière [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle numérique de surface [Termes IGN] pondération [Termes IGN] prévention des risques [Termes IGN] topographie locale [Termes IGN] vent [Termes IGN] voisinage (relation topologique) [Vedettes matières IGN] Foresterie Résumé : (auteur) Wind damage and the bark beetle outbreaks associated with it are major threats to non-declining, long-term wood production in boreal forests. We studied whether the risk of wind damage in a forested landscape could be decreased by using stand neighbourhood information in conjunction with terrain elevation information. A reference management plan minimized the differences in canopy height at stand boundaries and did not utilize information on the topography of the terrain, overlooking the possibility that the risk of windthrow may depend on the elevation of the terrain. Alternative management plans were developed by using four different weighting schemes when minimizing differences in canopy height at stand boundaries: (1) no weight (reference); (2) mean terrain elevation at the stand boundary; (3) deviation of the mean elevation of the boundary from the mean elevation of the terrain within a 100-m radius and (4) multipliers that described the effect of topography on wind speed at the stand boundary. For each management plan, we calculated the total number of at-risk trees and the total area of vulnerable stand edge. These statistics were based on the calculated critical wind speeds needed to uproot trees in stand edge zones. Minimization of the weighted mean of canopy height differences between adjacent stands resulted in homogeneous landscapes in terms of canopy height. Continuous cover management was often preferred instead of rotation management due to smaller canopy height differences between adjacent stands and its economical superiority. The best weighting scheme for calculating the mean canopy height difference between adjacent stands was the deviation between the mean elevation of the boundary and the mean elevation of the terrain within 100 m of the boundary. However, the differences between the weighting schemes were small. It was found that reasonably simple methods, based on a digital terrain model, a stand map, and the canopy heights of stands, could be used in forest planning to minimize the risk of wind damage. Validation against actual wind damages is required to assess the reliability of the results and to further develop the methodology presented. Numéro de notice : A2023-114 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1093/forestry/cpac039 Date de publication en ligne : 08/10/2022 En ligne : https://doi.org/10.1093/forestry/cpac039 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102481 [article]

Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India / Rabin Chakrabortty in Geocarto international, vol 37 n° 23 ([15/10/2022])  

Public [article]  inGeocarto international > vol 37 n° 23 [15/10/2022] . - pp 6713 - 6735 Titre : Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India Type de document : Article/Communication Auteurs : Rabin Chakrabortty, Auteur ; Subodh Chandra Pal, Auteur ; Fatemeh Rezaie, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 6713 - 6735 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] cartographie des risques [Termes IGN] Inde [Termes IGN] inondation [Termes IGN] mousson [Termes IGN] optimisation par essaim de particules [Termes IGN] réseau neuronal artificiel [Termes IGN] réseau neuronal profond [Termes IGN] risque naturel [Termes IGN] vulnérabilité Résumé : (auteur) Flood-susceptibility mapping is an important component of flood risk management to control the effects of natural hazards and prevention of injury. We used a remote-sensing and geographic information system (GIS) platform and a machine-learning model to develop a flood susceptibility map of Kangsabati River Basin, India where flash flood is common due to monsoon precipitation with short duration and high intensity. And in this subtropical region, climate change’s impact helps to influence the distribution of rainfall and temperature variation. We tested three models-particle swarm optimization (PSO), an artificial neural network (ANN), and a deep-leaning neural network (DLNN)-and prepared a final flood susceptibility map to classify flood-prone regions in the study area. Environmental, topographical, hydrological, and geological conditions were included in the models, and the final model was selected based on the relations between potentiality of causative factors and flood risk based on multi-collinearity analysis. The model results were validated and evaluated using the area under receiver operating characteristic (ROC) curve (AUC), which is an indicator of the current state of the environment and a value >0.95 implies a greater risk of flash floods. The AUC values for ANN, DLNN, and PSO for training datasets were 0.914, 0.920, and 0.942, respectively. Among these three models, PSO showed the best performance with an AUC value of 0.942. The PSO approach is applicable for flood susceptibility mapping of the eastern part of India, a subtropical region, to allow flood mitigation and help to improve risk management in this region. Numéro de notice : A2022-750 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1953618 Date de publication en ligne : 26/07/2021 En ligne : https://doi.org/10.1080/10106049.2021.1953618 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101742 [article]

Impact assessment of the seasonal hydrological loading on geodetic movement and seismicity in Nepal Himalaya using GRACE and GNSS measurements / Devendra Shashikant Nagale in Geodesy and Geodynamics, vol 13 n° 5 (September 2022)  

Public [article]  inGeodesy and Geodynamics > vol 13 n° 5 (September 2022) . - pp 445 - 455 Titre : Impact assessment of the seasonal hydrological loading on geodetic movement and seismicity in Nepal Himalaya using GRACE and GNSS measurements Type de document : Article/Communication Auteurs : Devendra Shashikant Nagale, Auteur ; Suresh Kannaujiya, Auteur ; Param K. Gautam, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 445 - 455 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] coefficient de corrélation [Termes IGN] déformation de la croute terrestre [Termes IGN] données GNSS [Termes IGN] données GRACE [Termes IGN] International Terrestrial Reference Frame [Termes IGN] mousson [Termes IGN] Népal [Termes IGN] pondération [Termes IGN] série temporelle [Termes IGN] sismicité [Termes IGN] surcharge hydrologique [Termes IGN] variation saisonnière Résumé : (auteur) The Himalayan terrain is an epitome of ongoing convergence and geodetic deformation where both tectonic and non-tectonic forces prevail. In this study, the Gravity Recovery and Climate Experiment (GRACE) and Global Positioning System (GPS) datasets are used to assess the impact of seasonal loading on deformation with seismicity in Nepal. The recorded GPS data from 21 Global Navigation Satellite System (GNSS) stations during 2017–2020 are processed with respect to ITRF14 and the Indian reference frame, and the Center for Space Research (CSR) mascon RL06 during 2002–2020 is adopted to estimate the terrestrial water storage (TWS) change over the Ganga-Brahmaputra River basin. The results indicate that the hydrological loading effect or TWS change shows high negative, high positive, and moderately positive values in pre-monsoon, co-monsoon, and post-monsoon months, respectively. The detrended GPS data of both horizontal and vertical components correlate with the seasonal TWS change using the Pearson correlation coefficient at each GNSS site. In addition, the correlation coefficient has been interpolated using inverse distance weighting to investigate the regional TWS influence on geodetic displacement. In the north component, the correlation coefficient ranges from −0.6 to 0.6. At the same time, the TWS is positively correlated with geodetic displacement (0.82) in the east component, and the correlation coefficient is negative (−0.69) in the vertical component. The negative correlation signifies an inverse relationship between seasonal TWS variation and geodetic displacements. The strain rate is estimated, which shows higher negative values in pre-monsoon than in post-monsoon. Similarly, the effect of seismicity is 47.90% for pre-monsoon, 15.97% for co-monsoon, and 17.56% for post-monsoon. Thus we can infer that the seismicity decreases with the increase of seasonal hydrological loading. Furthermore, the effect of strain is much higher in pre-monsoon than in post-monsoon since the impact of co-monsoon continues to persist on a small scale in the post-monsoon season. Numéro de notice : A2022-762 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.geog.2022.02.006 Date de publication en ligne : 20/05/2022 En ligne : https://doi.org/10.1016/j.geog.2022.02.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101780 [article]

GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet / Milad Asgarimehr in Remote sensing of environment, vol 269 (February 2022)  

Public [article]  inRemote sensing of environment > vol 269 (February 2022) . - n° 112801 Titre : GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet Type de document : Article/Communication Auteurs : Milad Asgarimehr, Auteur ; Caroline Arnold, Auteur ; Tobias Weigel, Auteur ; Chris Ruf, Auteur ; Jens Wickert, Auteur Année de publication : 2022 Article en page(s) : n° 112801 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] apprentissage profond [Termes IGN] modèle numérique [Termes IGN] réflectométrie par GNSS [Termes IGN] réseau neuronal convolutif [Termes IGN] vent [Termes IGN] vitesse Résumé : (auteur) GNSS Reflectometry (GNSS-R) is a novel remote sensing technique for the monitoring of geophysical parameters using reflected GNSS signals from the Earth's surface. Ocean wind speed monitoring is the main objective of the recently launched Cyclone GNSS (CyGNSS), a GNSS-R constellation of eight microsatellites, launched in late 2016. In this study, the capability of deep learning, especially, for an operational wind speed data derivation from the measured Delay-Doppler Maps (DDMs) is characterized. CyGNSSnet is based on convolutional layers for the feature extraction from bistatic radar cross section (BRCS) DDMs, along with fully connected layers for processing ancillary technical and higher-level input parameters. The best architecture is determined on a validation set and is evaluated over a completely blind dataset from a different time span than that of the training data to validate the generality of the model for operational usage. After a data quality control, CyGNSSnet results in an RMSE of 1.36 m/s leading to a significant improvement by 28% in comparison to the officially operational retrieval algorithm. The RMSE is the lowest among those seen in the literature for any conventional or machine learning-based algorithm. The benefits of the convolutional layers, the advantages and weaknesses of the model are discussed. CyGNSSnet offers efficient processing of GNSS-R measurements for high-quality global ocean winds. Numéro de notice : A2022-079 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.rse.2021.112801 Date de publication en ligne : 23/11/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112801 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99764 [article]

Investigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations / E-Ping Rau (2022)  

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Modélisation temporelle du fouillis forestier radar / Xavier Husson (2022)  

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4 807,81 m, le sommet décline / Anonyme in Géomètre, n° 2195 (octobre 2021)

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EUREC4A / Bjorn Stevens in Earth System Science Data, vol 13 n° 8 (August 2021)  

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Role of maximum entropy and citizen science to study habitat suitability of jacobin cuckoo in different climate change scenarios / Priyinka Singh in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)  

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Comparing the performance of turbulent kinetic energy and K-profile parameterization vertical parameterization schemes over the tropical indian ocean / Lokesh Kumar Pandey in Marine geodesy, vol 44 n° 1 (January 2021)  

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

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Remote sensing analysis of small scale dynamic phenomena in the atmospheric boundary layer / Kostas Cheliotis (2021)  

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Calibration of frequency shift system of wind imaging interferometer / Yongqiang Sun in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 12 (December 2020)  

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The utility of fused airborne laser scanning and multispectral data for improved wind damage risk assessment over a managed forest landscape in Finland / Ranjith Gopalakrishnan in Annals of Forest Science, vol 77 n° 4 (December 2020)  

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