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A geographical and content-based approach to prioritize relevant and reliable tweets for emergency management / A. Marcela Suarez in Cartography and Geographic Information Science, Vol 49 n° 5 (September 2022)
[article]
Titre : A geographical and content-based approach to prioritize relevant and reliable tweets for emergency management Type de document : Article/Communication Auteurs : A. Marcela Suarez, Auteur ; Keith C. Clarke, Auteur Année de publication : 2022 Article en page(s) : pp 443 - 463 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] catastrophe naturelle
[Termes IGN] classement
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] Etats-Unis
[Termes IGN] fiabilité des données
[Termes IGN] filtrage d'information
[Termes IGN] gestion de crise
[Termes IGN] pertinence
[Termes IGN] qualité des données
[Termes IGN] secours d'urgence
[Termes IGN] tempête
[Termes IGN] TwitterRésumé : (auteur) Tweets posted by the general public during disaster events represent timely, up-to-date, and on-site data that may be useful for emergency responders. However, since Twitter data has been deemed to be unverifiable and untrustworthy, it is challenging to identify those reliable and relevant tweets that can inform emergency response operations. Although computational methods exist both to classify overwhelming amounts of tweets and to filter those relevant to emergency response, using contextual geographic information regarding the disaster event to filter tweets has been overlooked. We review the existing research on the quality of data contributed by the general public from a geographical perspective, and then propose an approach to prioritize tweets for emergency response based on their relevance and reliability. The novelty of the approach is twofold: a) the use of both authoritative data such as hazard-related information and on-the-ground reports provided by weather spotters and validated by the National Weather Service; and b) the fact that it leverages tweets content as well as their geographical context and location. Using Hurricane Harvey in 2017 as a case study, results show that by following the proposed approach 79% of tweets sent from post-identified flooded areas were classified as of high or medium relevance and reliability. This suggests that the proposed approach can provide an accurate prioritization of tweets to be used for real time emergency management. Numéro de notice : A2022-633 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2022.2081257 En ligne : https://doi.org/10.1080/15230406.2022.2081257 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101399
in Cartography and Geographic Information Science > Vol 49 n° 5 (September 2022) . - pp 443 - 463[article]Identification of urban sectors prone to solid waste accumulation: A machine learning approach based on social indicators / Luis Izquierdo-Horna in Computers, Environment and Urban Systems, vol 96 (September 2022)
[article]
Titre : Identification of urban sectors prone to solid waste accumulation: A machine learning approach based on social indicators Type de document : Article/Communication Auteurs : Luis Izquierdo-Horna, Auteur ; Miker Damazo, Auteur ; Deyvis Yanayaco, Auteur Année de publication : 2022 Article en page(s) : n° 101834 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] déchet
[Termes IGN] densité de population
[Termes IGN] données socio-économiques
[Termes IGN] Pérou
[Termes IGN] régression logistique
[Termes IGN] zone urbaineRésumé : (auteur) In the last decades, the accumulation of municipal solid waste in urban areas has become a latent concern in our society due to its implications for the exposed population and the possible health and environmental issues it may cause. In this sense, this research study contributes to the timely identification of these sectors according to the anthropogenic characteristics of their residents as dictated by 10 social indicators (i.e., age, education, income, among others) sorted into three assessment categories (sociodemographic, sociocultural, and socioeconomic). Then, the data collected was processed and analyzed using two machine learning algorithms (random forest (RF) and logistic regression (LR)). The primary information that fed the machine learning model was collected through field visits and local/national reports. For this research, the Puente Piedra and Chaclacayo districts, both located in the province of Lima, Peru, were selected as case studies. Results suggest that the most relevant social indicators that help identifying these sectors are monthly income, consumption patterns, age, and household population density. The experiments showed that the RF algorithm has the best performance, since it efficiently identified 63% of the possible solid waste accumulation zones. In addition, both models were capable of determining different classes (AUC – RF = 0.65, AUC – LR = 0.71). Finally, the proposed approach is applicable and reproducible in different sectors of the national Peruvian territory. Numéro de notice : A2022-512 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101834 Date de publication en ligne : 10/06/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101834 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101052
in Computers, Environment and Urban Systems > vol 96 (September 2022) . - n° 101834[article]Large-scale diachronic surveys of the composition and dynamics of plant communities in Pyrenean snowbeds / Thomas Masclaux in Plant ecology, Vol 223 n° 9 (September 2022)
[article]
Titre : Large-scale diachronic surveys of the composition and dynamics of plant communities in Pyrenean snowbeds Type de document : Article/Communication Auteurs : Thomas Masclaux, Auteur ; Gérard Largier, Auteur ; Jocelyne Cambecèdes, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1103 - 1119 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] botanique systématique
[Termes IGN] changement climatique
[Termes IGN] dynamique de la végétation
[Termes IGN] manteau neigeux
[Termes IGN] névé
[Termes IGN] phytosociologie
[Termes IGN] Pyrénées (montagne)
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) The impact of ongoing climate change on plant communities varies according to vegetation type and location across the globe. Snowbed flora count among the most sensitive vegetation due to their dependence on long-lasting snow patches. This is especially the case toward their rear distribution edge, where warming has already induced a marked decrease in snow deposition. Thus, analysing the dynamics of snowbed plant communities is crucial for understanding the ecological processes that condition their persistence under new environmental conditions. The Pyrenees represent the southern distribution limit of several eurosiberian snowbed species. We surveyed eight snowbeds based on permanent plots, where the presence of each taxon was recorded annually between 2012 and 2019. We analysed vegetation patterns between sites and plots, related them to environmental gradients, and assessed temporal trends of community dynamics. We detected important between-site differences regarding species composition. However, these differences were not supported by species' biogeographical patterns, which suggests that local abiotic factors filter species with distinct autecology. In parallel, temporal community turnover was observed through the expansion of widespread grassland species, which supports the hypothesis of colonisation of snowbeds by common alpine taxa. Such changes could be related to a decrease in snow cover over recent times, which releases extreme environmental constraints to plant growth. Therefore, it is crucial to characterise fine-scale ecological conditions to forecast plant community dynamics and provide reliable information for conserving snowbed vegetation across the Palearctic. Numéro de notice : A2022-711 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s11258-022-01261-6 Date de publication en ligne : 16/08/2022 En ligne : https://doi.org/10.1007/s11258-022-01261-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101589
in Plant ecology > Vol 223 n° 9 (September 2022) . - pp 1103 - 1119[article]Comparison of PBIA and GEOBIA classification methods in classifying turbidity in reservoirs / Douglas Stefanello Facco in Geocarto international, vol 37 n° 16 ([15/08/2022])
[article]
Titre : Comparison of PBIA and GEOBIA classification methods in classifying turbidity in reservoirs Type de document : Article/Communication Auteurs : Douglas Stefanello Facco, Auteur ; Laurindo Antonio Guasselli, Auteur ; Luis Fernando Chimelo Ruiz, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 4762 - 4783 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse d'image orientée objet
[Termes IGN] bande spectrale
[Termes IGN] Brésil
[Termes IGN] centrale hydroélectrique
[Termes IGN] classification bayesienne
[Termes IGN] classification dirigée
[Termes IGN] classification et arbre de régression
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Landsat-OLI
[Termes IGN] segmentation d'image
[Termes IGN] turbidité des eauxRésumé : (auteur) Our goal is to compare the performance of Classification and Regression Tree, Naive Bayes and Random Forest algorithms, from supervised image classification, and approaches on Pixel-Based Image analysis (PBIA) and Geographic Object-Based Image Analysis (GEOBIA), to classify turbidity in reservoirs. Tod do so, we use Landsat 8 image and bands and spectral indices, as predictive parameters, as well as the classification algorithms based on PBIA and GEOBIA. The Brazilian Itaipu reservoir was adopted, as a case study. Our results show that the RF classifier obtained the highest accuracy in both classification approaches, followed by CART and NB. The KA and OA indices of the GEOBIA classifications were superior to the PBIA classifications in both algorithms. This study contributes with an approach to quickly and accurately delineating turbidity spectral limits in reservoirs. Numéro de notice : A2022-668 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1899302 Date de publication en ligne : 22/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1899302 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101519
in Geocarto international > vol 37 n° 16 [15/08/2022] . - pp 4762 - 4783[article]Climatic sensitivities derived from tree rings improve predictions of the forest vegetation simulator growth and yield model / Courtney L. Giebink in Forest ecology and management, vol 517 (August-1 2022)
[article]
Titre : Climatic sensitivities derived from tree rings improve predictions of the forest vegetation simulator growth and yield model Type de document : Article/Communication Auteurs : Courtney L. Giebink, Auteur ; R. Justin DeRose, Auteur ; Mark Castle, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120256 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cerne
[Termes IGN] croissance des arbres
[Termes IGN] gestion forestière
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle de simulation
[Termes IGN] Picea (genre)
[Termes IGN] Pinus ponderosa
[Termes IGN] Pseudotsuga menziesii
[Termes IGN] puits de carbone
[Termes IGN] rendement
[Termes IGN] Utah (Etas-Unis)
[Termes IGN] variation saisonnière
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Forest management has the potential to contribute to the removal of greenhouse gasses from the atmosphere via carbon sequestration and storage. To identify management actions that will maximize carbon removal and storage over the long term, models are needed that accurately and realistically represent forest responses to changing climate. The most widely used growth and yield model in the United States (U.S.), the Forest Vegetation Simulator (FVS), which also forms the basis for several forest carbon calculators, does not currently include the direct effect of climate variation on tree growth. We incorporated the effects of climate on tree diameter growth by combining tree-ring data with forest inventory data to parameterize a suite of alternative models characterizing the growth of three dominant tree species in the arid and moisture-limited state of Utah. These species, Pinus ponderosa Dougl. ex Laws, Pseudotsuga menziesii var. glauca Mayr (Franco), and Picea engelmannii Parry ex Engelm., encompass the full elevational range of montane forest types. The alternative models we considered differed progressively from the current FVS large-tree diameter growth model, first by changing to an annual time step, then by adding interannual climate effects, followed by model simplification (removal of predictors), and finally, complexification, including effects of spatial variation in climate and two-way interactions between predictors. We validated diameter growth predictions from these models with independent observations, and evaluated model performance in terms of accuracy, precision, and bias. We then compared predictions of future growth made by the existing large-tree diameter growth model used in FVS, i.e., without climate effects, to those of our updated models, including those with climate effects. We found that simpler models of tree growth outperform the current FVS model, and that the incorporation of climate effects improves model performance for two out of three species, in which growth is currently overpredicted by FVS. Diameter growth projected with improved, climate-sensitive models is less than the future tree growth projected by the current climate-insensitive FVS model. Tree rings can be used to identify and incorporate drivers of growth variation into a stand-level growth and yield model, giving more accurate predictions of the carbon uptake potential of forests under climate change. Numéro de notice : A2022-390 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120256 Date de publication en ligne : 12/05/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120256 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100681
in Forest ecology and management > vol 517 (August-1 2022) . - n° 120256[article]Influence of the declaration of protected natural areas on the evolution of forest fires in collective lands in Galicia (Spain) / Gervasio Lopez Rodriguez in Forests, Vol 13 n° 8 (August 2022)PermalinkMainstreaming remotely sensed ecosystem functioning in ecological niche models / Adrián Regos in Remote sensing in ecology and conservation, vol 8 n° 4 (August 2022)PermalinkMapping land-use intensity of grasslands in Germany with machine learning and Sentinel-2 time series / Maximilian Lange in Remote sensing of environment, vol 277 (August 2022)PermalinkMeasuring COVID-19 vulnerability for Northeast Brazilian municipalities: Social, economic, and demographic factors based on multiple criteria and spatial analysis / Ciro José Jardim De Figueiredo in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)PermalinkRemote sensing and phytoecological methods for mapping and assessing potential ecosystem services of the Ouled Hannèche Forest in the Hodna Mountains, Algeria / Amal Louail in Forests, Vol 13 n° 8 (August 2022)PermalinkSimulation of the potential impact of urban expansion on regional ecological corridors: A case study of Taiyuan, China / Wei Hou in Sustainable Cities and Society, vol 83 (August 2022)PermalinkSpatial assessment of ecosystem services provisioning changes in a forest-dominated protected area in NE Turkey / Can Vatandaslar in Environmental Monitoring and Assessment, vol 194 n° 8 (August 2022)PermalinkTracing drought effects from the tree to the stand growth in temperate and Mediterranean forests: insights and consequences for forest ecology and management / Hans Pretzsch in European Journal of Forest Research, vol 141 n° 4 (August 2022)PermalinkTracking annual dynamics of mangrove forests in mangrove National Nature Reserves of China based on time series Sentinel-2 imagery during 2016–2020 / Rong Zhang in International journal of applied Earth observation and geoinformation, vol 112 (August 2022)PermalinkTransfer learning from citizen science photographs enables plant species identification in UAV imagery / Salim Soltani in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)Permalink