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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]

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]

The impact of drought stress on the height growth of young norway spruce full-sib and half-sib clonal trials in Sweden and Finland / Haleh Hayatgheibi in Forests, vol 12 n° 4 (April 2021)  

Public [article]  inForests > vol 12 n° 4 (April 2021) . - n° 498 Titre : The impact of drought stress on the height growth of young norway spruce full-sib and half-sib clonal trials in Sweden and Finland Type de document : Article/Communication Auteurs : Haleh Hayatgheibi, Auteur ; Matti Haapanen, Auteur ; Jenny Lundströmer, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 498 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] clonage [Termes IGN] croissance des arbres [Termes IGN] Finlande [Termes IGN] génétique forestière [Termes IGN] hauteur des arbres [Termes IGN] Indice de précipitations antérieures [Termes IGN] Picea abies [Termes IGN] stress hydrique [Termes IGN] Suède [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) The summer drought of 2018 was one of the most climatically severe events in Europe that led to record-breaking temperatures and wildfires in many parts of Europe. The main objective of this study was to assess the impact of the 2018 drought on the phenotypic and genetic response of Norway spruce height growth using the Standardized Precipitation-Evapotranspiration Index (SPEI). To achieve this, the total cumulative height growth of about 6000 clones from 2016 to 2019 in four full-sib trials in Sweden, aged 6–7 years, and from 2017 to 2019 in two half-sib trials in Finland, aged 8–9 years, were measured. The results indicate that the 2018 drought caused reductions in the increment of trees. Although heritability estimates were similar to other reports for Norway spruce, the additive genetic variance was highly inflated in one of the visibly drought-damaged trials in Southern Sweden. Similarly, the genotype by environment (G × E) interaction was highly significant in the drought-damaged Southern Swedish trials. Both additive genetic and phenotypic correlations obtained between height increments in 2019 and final heights were the weakest in all studied trials, implying that the drought legacies might have influenced the recovery of trees in 2019. We may conclude that the severe drought can be an underlying factor for a strong G × E interaction and changes in the ranking of genotypes. Therefore, a selection of drought-resistant genotypes with a good growth capacity tested in variables sites should be considered as an important criterion for future breeding of Norway spruce. Numéro de notice : A2021-348 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f12040498 Date de publication en ligne : 16/04/2021 En ligne : https://doi.org/10.3390/f12040498 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97595 [article]

An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards / Geraldo Moura Ramos Filho in Natural Hazards, Vol 105 n° 3 (February 2021)  

Public [article]  inNatural Hazards > Vol 105 n° 3 (February 2021) . - pp 2409 - 2429 Titre : An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards Type de document : Article/Communication Auteurs : Geraldo Moura Ramos Filho, Auteur ; Victor Hugo Rabelo Coelho, Auteur ; Emerson da Silva Freitas, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2409 - 2429 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] crue [Termes IGN] Indice de précipitations antérieures [Termes IGN] indice de risque [Termes IGN] inondation [Termes IGN] méthode robuste [Termes IGN] prévention des risques [Termes IGN] risque naturel [Termes IGN] Sao Paulo [Termes IGN] seuillage [Termes IGN] surveillance hydrologique Résumé : (auteur) This paper presents an improved method of using threshold of peak rainfall intensity for robust flood/flash flood evaluation and warnings in the state of São Paulo, Brazil. The improvements involve the use of two tolerance levels and the delineating of an intermediate threshold by incorporating an exponential curve that relates rainfall intensity and Antecedent Precipitation Index (API). The application of the tolerance levels presents an average increase of 14% in the Probability of Detection (POD) of flood and flash flood occurrences above the upper threshold. Moreover, a considerable exclusion (63%) of non-occurrences of floods and flash floods in between the two thresholds significantly reduce the number of false alarms. The intermediate threshold using the exponential curves also exhibits improvements for almost all time steps of both hydrological hazards, with the best results found for floods correlating 8-h peak intensity and 8 days API, with POD and Positive Predictive Value (PPV) values equal to 81% and 82%, respectively. This study provides strong indications that the new proposed rainfall threshold-based approach can help reduce the uncertainties in predicting the occurrences of floods and flash floods. Numéro de notice : A2020-204 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-020-04405-x Date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.1007/s11069-020-04405-x Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97167 [article]

Dynamique spatiale des précipitations en région Centre / Michael Berthelot in Géomatique expert, n° 64 (01/09/2008)

Public [article]  inGéomatique expert > n° 64 (01/09/2008) . - pp 58 - 63 Titre : Dynamique spatiale des précipitations en région Centre Type de document : Article/Communication Auteurs : Michael Berthelot, Auteur Année de publication : 2008 Article en page(s) : pp 58 - 63 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] Centre (France administrative) [Termes IGN] interpolation spatiale [Termes IGN] krigeage [Termes IGN] pluviométrie [Termes IGN] précipitation Résumé : (Editeur) Comparaison de la méthode de krigeage classique et de la méthode spécialisée Aurelhy pour estimer les quantités de précipitations en région Centre, et l'influence du relief sur celle-ci, à partir des données de quelques stations météo. [Aurelhy = Analyse Utilisant le RElief pour l'HYdrométéorologie] Numéro de notice : A2008-369 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29362 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
265-08051	RAB	Revue	Centre de documentation	En réserve L003	Disponible
IFN-DIR-P000143	RAB	Revue	Nogent-sur-Vernisson	En réserve L003	Exclu du prêt
IFN-DIR-P000142	RAB	Revue	Nogent-sur-Vernisson	En réserve L003	Exclu du prêt

Estimating soil wetness using satellite data / B.J. Choudhury in International Journal of Remote Sensing IJRS, vol 9 n° 7 (July 1988)  

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Quantifying spatial and temporal variabilities of microwave brightness temperature over the U.S. southern great plains / B.J. Choudhury in International Journal of Remote Sensing IJRS, vol 8 n° 2 (February 1987)  

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