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Features predisposing forest to bark beetle outbreaks and their dynamics during drought / M. Müller in Forest ecology and management, vol 523 (1 November 2022)  

Public [article]  inForest ecology and management > vol 523 (1 November 2022) . - n° 120480 Titre : Features predisposing forest to bark beetle outbreaks and their dynamics during drought Type de document : Article/Communication Auteurs : M. Müller, Auteur ; P.O. Olsson, Auteur ; Lars Eklundh, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120480 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse des risques [Termes IGN] canopée [Termes IGN] changement climatique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données météorologiques [Termes IGN] humidité du sol [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] Scolytinae [Termes IGN] sécheresse [Termes IGN] Suède [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Climate change is estimated to increase the risk of the bark beetle (Ips typographus L.) mass outbreaks in Norway Spruce (Picea abies (L.) Karst) forests. Habitats that are thermally suitable for bark beetles may expand, and an increase in the frequency and intensity of droughts can promote drought stress on host trees. Drought affects tree vigor and in unison with environmental features it influences the local predisposition risk of forest stands to bark beetle attacks. We aimed to study how various environmental features influence the risk of bark beetle attacks during a drought year and the following years with more normal weather conditions but with higher bark beetle populations. We included features representing local forest stand attributes, topography, soil type and wetness, the proximity of clear-cuts and previous bark beetle attacks, and a machine learning algorithm (random forest) was applied to study the variation of predisposition risk across a 48,600 km2 study area in SE Sweden. Forest stands with increased risk of bark beetle attack were distinguished with high accuracy both during drought and in normal weather conditions. The results show that during both study periods, spruce and mixed coniferous forests had elevated risk of attack, while forests with a mix of deciduous and coniferous trees had a lower risk. Forests with high average canopy height were strongly predisposed to bark beetle attacks. However, during the drought year risk was more similar between stands with lower and higher canopy height, suggesting that during drought periods younger trees can be predisposed to bark beetle attacks. The importance of soil moisture and position within the local landscape were highlighted as important features during the drought year. Identifying areas with increased risk, supported by information on how environmental features control the predisposition risk during drought, could aid adaptation strategies and forest management intervention efforts. We conclude that geospatial data and machine learning have the potential to further support the digitalization of the forest industry, facilitating development of methods capable to quantify importance and dynamics of environmental features controlling the risk in local context. Corresponding methods could help to direct management actions more effectively and offer information for decision-making in changing climate. Numéro de notice : A2022-731 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120480 Date de publication en ligne : 07/09/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120480 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101687 [article]

Evapotranspiration mapping of cotton fields in Brazil: comparison between SEBAL and FAO-56 method / Juan Vicente Liendro Moncada in Geocarto international, Vol 37 n° 17 ([20/08/2022])  

Public [article]  inGeocarto international > Vol 37 n° 17 [20/08/2022] . - pp 5133 - 5149 Titre : Evapotranspiration mapping of cotton fields in Brazil: comparison between SEBAL and FAO-56 method Type de document : Article/Communication Auteurs : Juan Vicente Liendro Moncada, Auteur ; Tonny José Araújo da Silva, Auteur ; Jefferson Vieira José, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 5133 - 5149 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] carte thématique [Termes IGN] corrélation [Termes IGN] données météorologiques [Termes IGN] évapotranspiration [Termes IGN] Gossypium (genre) [Termes IGN] GRASS [Termes IGN] image Landsat-8 [Termes IGN] Mato Grosso [Termes IGN] modèle de Monteith [Termes IGN] phénologie [Termes IGN] QGIS [Termes IGN] régression logistique [Termes IGN] SEBAL (algorithme) [Termes IGN] système d'information géographique Résumé : (auteur) The objective was to compare the evapotranspiration of cotton (Gossypium sp. L.) estimated by the SEBAL model and the FAO-56 method, throughout the phenological cycle of the plant on eight fields located in the upper area of the Rio das Mortes basin, State of Mato Grosso—Brazil. Images from the Landsat 8 satellite were used under the Geographic Information Systems environment through the capabilities of the QGIS 3.6.2 and GRASS 7.6.1 software. The reference evapotranspiration was determined by the FAO Penman–Monteith method implementing the Ref-ET software and data from the Campo Verde meteorological station of INMET—Brazil. The R software was applied to the statistical analyses of correlation and regression. The dataset of the available stages of the cotton phenological cycle shows a strong positive correlation, with approximately 68% of the evapotranspiration variation of the SEBAL model related to the estimates of the FAO-56 method. Numéro de notice : A2022-700 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1920633 Date de publication en ligne : 06/05/2021 En ligne : https://doi.org/10.1080/10106049.2021.1920633 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101559 [article]

GNSSseg, a statistical method for the segmentation of daily GNSS IWV time series / Annarosa Quarello in Remote sensing, vol 14 n° 14 (July-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 14 (July-2 2022) . - n° 3379 Titre : GNSSseg, a statistical method for the segmentation of daily GNSS IWV time series Type de document : Article/Communication Auteurs : Annarosa Quarello , Auteur ; Olivier Bock , Auteur ; Emilie Lebarbier, Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : n° 3379 Note générale : bibliographie This work was developed in the framework of the VEGA Project and supported by the CNRS Program LEFE/INSU. The contribution of the third author has been conducted as part of the Project Labex MME-DII (ANR11-LBX-0023-01) and within the FP2M Federation (CNRS FR 2036). Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] coordonnées GPS [Termes IGN] données météorologiques [Termes IGN] erreur systématique [Termes IGN] programmation dynamique [Termes IGN] R (langage) [Termes IGN] segmentation [Termes IGN] série temporelle [Termes IGN] teneur intégrée en vapeur d'eau Résumé : (auteur) Homogenization is an important and crucial step to improve the usage of observational data for climate analysis. This work is motivated by the analysis of long series of GNSS Integrated Water Vapour (IWV) data, which have not yet been used in this context. This paper proposes a novel segmentation method called segfunc that integrates a periodic bias and a heterogeneous, monthly varying, variance. The method consists in estimating first the variance using a robust estimator and then estimating the segmentation and periodic bias iteratively. This strategy allows for the use of the dynamic programming algorithm, which is the most efficient exact algorithm to estimate the change point positions. The performance of the method is assessed through numerical simulation experiments. It is implemented in the R package GNSSseg, which is available on the CRAN. This paper presents the application of the method to a real data set from a global network of 120 GNSS stations. A hit rate of 32% is achieved with respect to available metadata. The final segmentation is made in a semi-automatic way, where the change points detected by three different penalty criteria are manually selected. In this case, the hit rate reaches 60% with respect to the metadata. Numéro de notice : A2022-575 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs14143379 Date de publication en ligne : 13/07/2022 En ligne : https://doi.org/10.3390/rs14143379 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101294 [article]

GIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data / Wanqin He in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 6 (June 2022) . - n° 336 Titre : GIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data Type de document : Article/Communication Auteurs : Wanqin He, Auteur ; Sara Shirowzhan, Auteur ; Christopher Pettit, Auteur Année de publication : 2022 Article en page(s) : n° 336 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse diachronique [Termes IGN] apprentissage automatique [Termes IGN] brousse [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] coefficient de corrélation [Termes IGN] données météorologiques [Termes IGN] données spatiotemporelles [Termes IGN] humidité du sol [Termes IGN] incendie [Termes IGN] indice de végétation [Termes IGN] Nouvelle-Galles du Sud [Termes IGN] prévention des risques [Termes IGN] régression linéaire [Termes IGN] Spark [Termes IGN] système d'information géographique [Termes IGN] température de l'air Résumé : (auteur) The causes of bushfires are extremely complex, and their scale of burning and probability of occurrence are influenced by the interaction of a variety of factors such as meteorological factors, topography, human activity and vegetation type. An in-depth understanding of the combined mechanisms of factors affecting the occurrence and spread of bushfires is needed to support the development of effective fire prevention plans and fire suppression measures and aid planning for geographic, ecological maintenance and urban emergency management. This study aimed to explore how bushfires, meteorological variability and other natural factors have interacted over the past 40 years in NSW Australia and how these influencing factors synergistically drive bushfires. The CSIRO’s Spark toolkit has been used to simulate bushfire burning spread over 24 h. The study uses NSW wildfire data from 1981–2020, combined with meteorological factors (temperature, precipitation, wind speed), vegetation data (NDVI data, vegetation type) and topography (slope, soil moisture) data to analyse the relationship between bushfires and influencing factors quantitatively. Machine learning-random forest regression was then used to determine the differences in the influence of bushfire factors on the incidence and burn scale of bushfires. Finally, the data on each influence factor was imported into Spark, and the results of the random forest model were used to set different influence weights in Spark to visualise the spread of bushfires burning over 24 h in four hotspot regions of bushfire in NSW. Wind speed, air temperature and soil moisture were found to have the most significant influence on the spread of bushfires, with the combined contribution of these three factors exceeding 60%, determining the spread of bushfires and the scale of burning. Precipitation and vegetation showed a greater influence on the annual frequency of bushfires. In addition, burn simulations show that wind direction influences the main direction of fire spread, whereas the shape of the flame front is mainly due to the influence of land classification. Besides, the simulation results from Spark could predict the temporal and spatial spread of fire, which is a potential decision aid for fireproofing agencies. The results of this study can inform how fire agencies can better understand fire occurrence mechanisms and use bushfire prediction and simulation techniques to support both their operational (short-term) and strategic (long-term) fire management responses and policies. Numéro de notice : A2022-481 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11060336 Date de publication en ligne : 05/06/2022 En ligne : https://doi.org/10.3390/ijgi11060336 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100894 [article]

The effects of fire on Pinus sylvestris L. as determined by dendroecological analysis (Sierra de Gredos, Spain) / Mar Génova in iForest, biogeosciences and forestry, vol 15 (June 2022)  

Public [article]  iniForest, biogeosciences and forestry > vol 15 (June 2022) . - pp 171 - 178 Titre : The effects of fire on Pinus sylvestris L. as determined by dendroecological analysis (Sierra de Gredos, Spain) Type de document : Article/Communication Auteurs : Mar Génova, Auteur ; Paula Ortega, Auteur ; Enrique Sadornil, Auteur Année de publication : 2022 Article en page(s) : pp 171 - 178 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique [Termes IGN] cerne [Termes IGN] croissance des arbres [Termes IGN] dendrochronologie [Termes IGN] données météorologiques [Termes IGN] Espagne [Termes IGN] incendie de forêt [Termes IGN] Pinus sylvestris [Vedettes matières IGN] Botanique Résumé : (auteur) Iberian populations of Scots pine (Pinus sylvestris L.) have been declining since the late-glacial period; among those that remain, relict stands have great biological and ecological value. This paper investigates the effects of a 2009 fire on tree growth in one of these small populations in the Sierra de Gredos (Spain) by examining the responses recorded in the tree-ring width series of the surviving trees. The current status and distribution of these surviving trees reveal the severity of the fire; indeed most show scars or other evidence of fire damage. Dendroecological analysis revealed narrower tree rings, indicating negative pointer years for the year of the fire and the following year. A very significant reduction in growth was recorded for the years after the fire, both in terms of tree-ring width and basal area increment; incomplete and even absent rings were also recorded. No relationship was seen between these effects and climatic events. The dates and geographical extension of former possible disturbances were also investigated, using the data from these same trees plus information collected from others in the region. The vulnerability of these populations to past fires was evident. Lastly, given the problems affecting the regeneration of these relict populations, it is strongly suggested to urgently include all these populations in conservation and environmental management programs. Numéro de notice : A2022-569 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtSansCL DOI : 10.3832/ifor3727-015 Date de publication en ligne : 09/05/2022 En ligne : https://doi.org/10.3832/ifor3727-015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101255 [article]

Assessment of land suitability potentials for winter wheat cultivation by using a multi criteria decision Support-Geographic information system (MCDS-GIS) approach in Al-Yarmouk Basin (Syria) / Safwan Mohammed in Geocarto international, vol 37 n° 6 ([01/04/2022])  

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Detecting and mapping drought severity using multi-temporal Landsat data in the uMsinga region of KwaZulu-Natal, South Africa / Shenelle Lottering in Geocarto international, vol 37 n° 6 ([01/04/2022])  

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

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An improved vertical correction method for the inter-comparison and inter-validation of Integrated Water Vapour measurements [under review] / Olivier Bock in Atmospheric measurement techniques, vol 15 n° inconnu ([01/04/2022])  

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Projections of climate change impacts on flowering-veraison water deficits for Riesling and Müller-Thurgau in Germany / Chenyao Yang in Remote sensing, vol 14 n° 6 (March-2 2022)  

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Classification of Eucalyptus plantation Site Index (SI) and Mean Annual Increment (MAI) prediction using DEM-based geomorphometric and climatic variables in Brazil / Aliny Aparecida Dos Reis in Geocarto international, vol 37 n° 5 ([01/03/2022])  

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Comprehensive study on the tropospheric wet delay and horizontal gradients during a severe weather event / Victoria Graffigna in Remote sensing, vol 14 n° 4 (February-2 2022)  

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3D geovisualization for visual analysis of urban climate / Sidonie Christophe in Cybergeo, European journal of geography, vol 2022 ([01/01/2022])  

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Apport de la télédétection et des variables auxiliaires dans l'étude de l'évolution des périodes de sécheresse / Nesrine Farhani (2022)  

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Precipitation frequency in MED and EURO-CORDEX ensembles from 0.44° to convective permitting resolution: Impact of model resolution and convection representation / Minh Ha-Truong (2022)  

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