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Assessing spatio-temporal mapping and monitoring of climatic variability using SPEI and RF machine learning models / Saadia Sultan Wahlaa in Geocarto international, vol 37 n° 27 ([20/12/2022])  

Public [article]  inGeocarto international > vol 37 n° 27 [20/12/2022] . - pp Titre : Assessing spatio-temporal mapping and monitoring of climatic variability using SPEI and RF machine learning models Type de document : Article/Communication Auteurs : Saadia Sultan Wahlaa, Auteur ; Jamil Hasan Kazmi, Auteur ; Alireza Sharifi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] changement climatique [Termes IGN] classification par arbre de décision [Termes IGN] évapotranspiration [Termes IGN] Indice de précipitations antérieures [Termes IGN] modèle de simulation [Termes IGN] Pakistan [Termes IGN] prévision météorologique [Termes IGN] sécheresse Résumé : (auteur) Droughts may inflict significant damage to agricultural and water supplies, resulting in substantial financial losses as well as the death of people and livestock. This study intends to anticipate droughts by studying the changes of an acceptable index using appropriate climatic factors. This study was divided into three phases, first being the determination of the Standardized Precipitation Evapotranspiration (SPEI) index for the Cholistan, Punjab, Pakistan area based on a dataset spanning 1980 to 2020. The indices are calculated at different monthly intervals which could to predict short-term periods for the Cholistan in Pakistan, we selected two distinctive time periods of one month (SPEI–1) and three months (SPEI–3). The second phase involved dividing the data into three sample sizes, which were used for training data from 1980 to 2010, testing data from 2011 to 2015 and validation data from 2016 to 2020. The utilization of the random forest (RF) algorithm to train and evaluate the data using a variety of climate variables e.g. potential evapotranspiration, rainfall, vapor pressure cloud cover, and mean, minimum and maximum, temperature. The final phase was to analyze the performance of the model based on statistical metrics and drought classes. Based on these considerations, statistical measures, such as the Coefficient of Determination (R2) and the Root Mean Square Error (RMSE) approach, were used to evaluate the performance of the test group throughout the testing period. The model's performance revealed the satisfactory results with R2 values of 0.80 and 0.78, for SPEI–1 and SPEI–3 situations, respectively. Following the data analysis, it was discovered that the validation period had a receiving operating curve and area under the Curve (ROC-AUC) of 0.87 for the SPEI–1 case and 0.85 for the SPEI–3 case. In this context, the results indicate that the SPEI may be useful as a prediction tool for drought prediction and the performances the RF model was suitable for both timescales. However, a more rigorous analysis with a larger dataset or a combination of datasets from different areas might be more beneficial for generalization over more extended time periods provide additional insights. Numéro de notice : A2022-934 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2022.2093411 Date de publication en ligne : 30/06/2022 En ligne : https://doi.org/10.1080/10106049.2022.2093411 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102672 [article]

Effect of climate change on the growth of tree species: Dendroclimatological analysis / Archana Gauli in Forests, vol 13 n° 4 (April 2022)  

Public [article]  inForests > vol 13 n° 4 (April 2022) . - n° 496 Titre : Effect of climate change on the growth of tree species: Dendroclimatological analysis Type de document : Article/Communication Auteurs : Archana Gauli, Auteur ; Prem Raj Neupane, Auteur ; Philip Mundhenk, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 496 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Allemagne [Termes IGN] analyse diachronique [Termes IGN] croissance des arbres [Termes IGN] dendrochronologie [Termes IGN] dendrologie [Termes IGN] données météorologiques [Termes IGN] échantillonnage [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] prévision météorologique [Termes IGN] Pseudotsuga menziesii [Termes IGN] sécheresse [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Tree ring analyses can assist in revealing the effect of gradual change in climatic variables on tree growth. Dendroclimatic analyses are of particular importance in evaluating the climate variables that affect growth significantly and in determining the relative strength of different climatic factors. In this study, we investigated the growth performance of Pinus sylvestris, Picea abies, and Pseudotsuga menziesii in northern Germany using standard dendrochronological methods. The study further analyzed tree growth responses to different climatic variables over a period of a hundred years. Both response function analysis and moving correlation analysis confirmed that the climate and growth relationship is species-specific and variable and inconsistent over time. Scots pine and Douglas fir growth were stimulated mainly by the increase in winter temperatures, particularly the January, February, and March temperatures of the current year. In contrast, Norway spruce growth was stimulated mainly by the increase in precipitation in May, June, and July and the increase in temperature in March of the current year. Climate projections for central Europe foresee an increase in temperature and a decrease in the amount of summer precipitation. In a future, warmer climate with drier summers, the growth of Norway spruce might be negatively affected. Numéro de notice : A2022-259 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f13040496 Date de publication en ligne : 22/03/2022 En ligne : https://doi.org/10.3390/f13040496 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100237 [article]

Assessing ZWD models in delay and height domains using data from stations in different climate regions / Thainara Munhoz Alexandre de Lima in Applied geomatics, vol 14 n° 1 (March 2022)  

Public [article]  inApplied geomatics > vol 14 n° 1 (March 2022) . - pp 93 - 103 Titre : Assessing ZWD models in delay and height domains using data from stations in different climate regions Type de document : Article/Communication Auteurs : Thainara Munhoz Alexandre de Lima, Auteur ; Marcelo Santos, Auteur ; Daniele Barroca Marra Alves, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 93 - 103 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] climat [Termes IGN] correction du signal [Termes IGN] données GNSS [Termes IGN] modèle atmosphérique [Termes IGN] modèle empirique [Termes IGN] modèle météorologique [Termes IGN] positionnement ponctuel précis [Termes IGN] prévision météorologique [Termes IGN] radiosondage [Termes IGN] retard troposphérique zénithal Résumé : (auteur) Global Navigation Satellite System (GNSS) has revolutionized activities involving geodetic positioning. To achieve a desired accuracy, it is essential to model the atmosphere in an appropriate way. With respect to the neutral atmosphere, the signal sent by the satellite suffers a delay when crossing this layer during its travel to the receiver on the surface, the so-called neutral atmospheric delay. Although empirical models exist, they may not be suitable to represent microclimatic variations in different regions of the globe due to peculiarities that exist in diverse areas. To minimize this limitation, correction models based on numerical weather prediction (NWP) emerge. They allow the assessment of the delay from local atmospheric parameters and the evaluation of atmospheric particularities of each region. In addition, another way to obtain neutral atmosphere delay is by making use of data from radiosondes, which measure atmospheric data at various altitude levels. The main objective of this article is to investigate the performance of different models using GNSS data collected in countries with different climatic conditions. Assessment is performed on the positioning domain using the precise point positioning (PPP) technique. The results show that the proximity between the NWP-based models and radiosondes was approximately 3 cm, and that between empirical models was 5 cm, with variations that depended on the model and the region. Regarding the impact on the height component, the difference between the accuracy of the empirical and NWP models was approximately 16 cm. Numéro de notice : A2022-219 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s12518-021-00414-y En ligne : https://doi.org/10.1007/s12518-021-00414-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100088 [article]

Development of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan / Eunbeen Park in GIScience and remote sensing, vol 59 n° 1 (2022)  

Public [article]  inGIScience and remote sensing > vol 59 n° 1 (2022) . - pp 36 - 53 Titre : Development of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan Type de document : Article/Communication Auteurs : Eunbeen Park, Auteur ; Hyun-Woo Jo, Auteur ; Sujong Lee, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 36 - 53 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] changement climatique [Termes IGN] changement temporel [Termes IGN] image Terra-MODIS [Termes IGN] Indice de précipitations antérieures [Termes IGN] indice de végétation [Termes IGN] Kirghizistan [Termes IGN] message d'alerte [Termes IGN] modèle de simulation [Termes IGN] plan de prévention des risques [Termes IGN] prévision météorologique [Termes IGN] sécheresse Résumé : (auteur) Drought is a natural disaster that occurs globally and is a main trigger of secondary environmental and socio-economic damages, such as food insecurity, land degradation, and sand-dust storms. As climate change is being accelerated by human activities and environmental changes, both the severity and uncertainties of drought are increasing. In this study, a diagnostic drought prediction model (DDPM) was developed to reduce the uncertainties caused by environmental diversity at the regional level in Kyrgyzstan, by predicting drought with meteorological forecasts and satellite image diagnosis. The DDPM starts with applying a prognostic drought prediction model (PDPM) to 1) estimate future agricultural drought by explaining its relationship with the standardized precipitation index (SPI), an accumulated precipitation anomaly, and 2) compensate for regional variances, which were not reflected sufficiently in the PDPM, by taking advantage of preciseness in the time-series vegetation condition index (VCI), a satellite-based index representing land surface conditions. Comparing the prediction results with the monitored VCI from June to August, it was found that the DDPM outperformed the PDPM, which exploits only meteorological data, in both spatiotemporal and spatial accuracy. In particular, for June to August, respectively, the results of the DDPM (coefficient of determination [R2] = 0.27, 0.36, and 0.4; root mean squared error [RMSE] = 0.16, 0.13, and 0.13) were more effective in explaining the spatial details of drought severity on a regional scale than those of the PDPM (R2 = 0.09, 0.10, and 0.11; RMSE = 0.17, 0.15, and 0.16). The DDPM revealed the possibility of advanced drought assessment by integrating the earth observation big data comprising meteorological and satellite data. In particular, the advantage of data fusion is expected to be maximized in areas with high land surface heterogeneity or sparse weather stations by providing observational feedback to the PDPM. This research is anticipated to support policymakers and technical officials in establishing effective policies, action plans, and disaster early warning systems to reduce disaster risk and prevent environmental and socio-economic damage. Numéro de notice : A2022-132 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15481603.2021.2012370 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1080/15481603.2021.2012370 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99720 [article]

La campagne Caddiwa dans la région des îles du Cap-Vert / Cyrille Flamant in La Météorologie, n° 115 (2021)  

Public [article]  inLa Météorologie > n° 115 (2021) . - pp 2 - 5 Titre : La campagne Caddiwa dans la région des îles du Cap-Vert Type de document : Article/Communication Auteurs : Cyrille Flamant, Auteur ; Julien Delanoë, Auteur ; Jean-Pierre Chaboureau, Auteur ; Christophe Lavaysse, Auteur ; Marco Gaetani, Auteur ; Olivier Bock , Auteur Année de publication : 2021 Projets : 3-projet - voir note / Article en page(s) : pp 2 - 5 Note générale : bibliographie Le projet Clouds-Atmospheric Dynamics-Dust Interactions in West Africa (Caddiwa) est d’étudier les interactions « systèmes convectifs de méso-échelle-pousières-ondes tropicales » dans la zone de l’Atlantique Nord tropical située au large de l’Afrique de l’Ouest. Langues : Français (fre) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] aérosol [Termes IGN] campagne d'observations [Termes IGN] Cap-Vert [Termes IGN] convection [Termes IGN] image MSG [Termes IGN] lidar atmosphérique [Termes IGN] positionnement par GPS [Termes IGN] poussière [Termes IGN] prévision météorologique [Termes IGN] télédétection spatiale [Termes IGN] tempête Numéro de notice : A2021-978 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.37053/lameteorologie-2021-0081 Date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.37053/lameteorologie-2021-0081 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100756 [article]

A parameterization of the cloud scattering polarization signal derived from GPM observations for microwave fast radative transfer models / Victoria Sol Galligani in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)  

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

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Assessment of renewable energy resources with remote sensing / Fernando Ramos Martins (2021)  

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Copula-based modeling of dependence structure in geodesy and GNSS applications: case study for zenith tropospheric delay in complex terrain / Roya Mousavian in GPS solutions, vol 25 n° 1 (January 2021)  

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Impact of INSAT-3D/3DR radiance data assimilation in predicting tropical cyclone Titli over the bay of Bengal / Raghu Nadimpalli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Homogenizing GPS integrated water vapor time series: Benchmarking break detection methods on synthetic data sets / Roeland Van Malderen in Earth and space science, vol 7 n° 5 (May 2020)  

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Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network / Adil Alim in Geoinformatica, vol 24 n° 2 (April 2020)  

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Improving operational radar rainfall estimates using profiler observations over complex terrain in Northern California / Haonan Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Mapping precipitable water vapor time series from Sentinel-1 interferometric SAR / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)  

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Typology of meteorological weather forecast maps printed in world newspapers / Jaromir Kolejka in Cartographic journal (the), Vol 57 n° 1 (February 2020)  

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