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7 results on '"Temporal analysi"'

1. LOTVS: A global collection of permanent vegetation plots

Author

Marta Gaia Sperandii, Francesco de Bello, Enrique Valencia, Lars Götzenberger, Manuele Bazzichetto, Thomas Galland, Anna E‐Vojtkó, Luisa Conti, Peter B. Adler, Hannah Buckley, Jiří Danihelka, Nicola J. Day, Jürgen Dengler, David J. Eldridge, Marc Estiarte, Ricardo García‐González, Eric Garnier, Daniel Gómez‐García, Lauren Hallett, Susan Harrison, Tomas Herben, Ricardo Ibáñez, Anke Jentsch, Norbert Juergens, Miklós Kertész, Duncan M. Kimuyu, Katja Klumpp, Mike Le Duc, Frédérique Louault, Rob H. Marrs, Gábor Ónodi, Robin J. Pakeman, Meelis Pärtel, Begoña Peco, Josep Peñuelas, Marta Rueda, Wolfgang Schmidt, Ute Schmiedel, Martin Schuetz, Hana Skalova, Petr Šmilauer, Marie Šmilauerová, Christian Smit, Ming‐Hua Song, Martin Stock, James Val, Vigdis Vandvik, Karsten Wesche, Susan K. Wiser, Ben A. Woodcock, Truman P. Young, Fei‐Hai Yu, Amelia A. Wolf, Martin Zobel, Jan Lepš, Centro de Investigaciones sobre Desertificacion (CIDE), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Universidad Rey Juan Carlos [Madrid] (URJC), Institute of Botany of the Czech Academy of Sciences (IB / CAS), Czech Academy of Sciences [Prague] (CAS), UNIVERSITY OF SOUTH BOHEMIA CESKE BUDEJOVICE CZE, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Czech University of Life Sciences Prague (CZU), Utah State University (USU), Auckland University of Technology (AUT), Masaryk University [Brno] (MUNI), Victoria University of Wellington, Zürich University of Applied Sciences (ZHAW), University of New South Wales [Kensington], CREAF - Centre for Ecological Research and Applied Forestries, Instituto Pirenaico de Ecologìa = Pyrenean Institute of Ecology [Zaragoza] (IPE - CSIC), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), University of Oregon, Eugene, OR 97403, United States, University of California (UC), Department of Zoology, Charles University in Prague, Faculty of Science, Viniicna 7, 128 43 Praha 2, Universidad Pública de Navarra [Espagne] = Public University of Navarra (UPNA), University of Hamburg, Hungarian Academy of Sciences (MTA), University of Liverpool, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), The James Hutton Institute, University of Tartu, Autonomous University of Madrid, Faculty of Sciences, Department of Ecology, 28049 Madrid, Spain, Universidad de Sevilla / University of Sevilla, Centre for Biodiversity and Sustainable Land-use [University of Göttingen] (CBL), Georg-August-University = Georg-August-Universität Göttingen, Hamburg University of Applied Sciences [Hamburg], Swiss Federal Institute for Forest, Snow and Landscape Research WSL, University of South Bohemia, Groningen Institute for Evolutionary Life Sciences [Groningen] (GELIFES), University of Groningen [Groningen], Chinese Academy of Agricultural Sciences (CAAS), Wadden Sea National Park of Schleswig-Holstein, University of Bergen (UiB), Senckenberg Museum of Natural History Görlitz, Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, Manaaki Whenua – Landcare Research [Lincoln], Center for Ecology and Hydrology, Taizhou University, University of Texas-Pan, Smit group, Royal Society of New Zealand, Czech Science Foundation, Academy of Sciences of the Czech Republic, Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), Institut National de la Recherche Agronomique (France), Federal Ministry of Education and Research (Germany), Oberfranken Stiftung, Agence Nationale de la Recherche (France), Scottish Government's Rural and Environment Science and Analytical Services, Estonian Research Council, European Commission, Fundación Ramón Areces, Generalitat de Catalunya, European Research Council, Dresden University of Technology, Ministry of Business, Innovation, and Employment (New Zealand), Natural Environment Research Council (UK), Biotechnology and Biological Sciences Research Council (UK), Comunidad de Madrid, Universidad Rey Juan Carlos, National Science Foundation (US), South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses [University of South Bohemia] (CENAKVA), Faculty of Fisheries and Protection of Waters [University of South Bohemia], University of South Bohemia -University of South Bohemia, Desertification Research Centre (CIDE), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Universitat de València (UV), University of Bayreuth, German Centre for Integrative Biodiversity Research (iDiv), University of New South Wales [Sydney] (UNSW), Centre for Ecological Research and Forestry Applications (CREAF), Unit CREAF-CSIC-UABB, Global Ecology Unit (CREAF-CSIC-UAB), Université de Montpellier (UM), Institut de Recherche pour le Développement (IRD), Department of Mathematics, University of Oregon [Eugene], University of Oregon [Eugene], Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), Charles University [Prague] (CU), Distributed Events Analysis Research Group (MTA SZTAKI Hungarian Academy of Sciences), Mpala Research Centre, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Université Clermont Auvergne (UCA), Institute of Computer Science [University of Tartu, Estonie], Centre de Recerca Ecològica i Aplicacions Forestals - Centre for Ecological Research and Forestry Applications, Partenaires INRAE, University of Chinese Academy of Sciences [Beijing] (UCAS), Lake Ecosystems Group [Lancaster, U.K.] (Centre for Ecology & Hydrology), Lancaster Environment Centre [Lancaster, U.K.], Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China, Department of Electrical and Computer Engineering - University of Texas (ECE), University of Texas at Austin [Austin], ANR-11-INBS-0001,ANAEE-FR,ANAEE-Services(2011), Sperandii, M. G., de Bello, F., Valencia, E., Gotzenberger, L., Bazzichetto, M., Galland, T., E-Vojtko, A., Conti, L., Adler, P. B., Buckley, H., Danihelka, J., Day, N. J., Dengler, J., Eldridge, D. J., Estiarte, M., Garcia-Gonzalez, R., Garnier, E., Gomez-Garcia, D., Hallett, L., Harrison, S., Herben, T., Ibanez, R., Jentsch, A., Juergens, N., Kertesz, M., Kimuyu, D. M., Klumpp, K., Le Duc, M., Louault, F., Marrs, R. H., Onodi, G., Pakeman, R. J., Partel, M., Peco, B., Penuelas, J., Rueda, M., Schmidt, W., Schmiedel, U., Schuetz, M., Skalova, H., Smilauer, P., Smilauerova, M., Smit, C., Song, M. -H., Stock, M., Val, J., Vandvik, V., Wesche, K., Wiser, S. K., Woodcock, B. A., Young, T. P., Yu, F. -H., Wolf, A. A., Zobel, M., and Leps, J.

Subjects
Plant communities, temporal analysis, Plant community, Plant Science, ecological succession, Permanent plot, ecoinformatic, plant communitie, Ecology and Environment, ecoinformatics, vegetation, Ecological succession, Ecoinformatics, Global scale, 577: Ökologie, time-serie, Vegetation, ecosystem stability, Ecology, time-series, Temporal analysis, permanent plot, plant diversity, plant communities, temporal analysi, 580: Pflanzen (Botanik), Plant diversity, global scale, Ecosystem stability, Permanent plots, Time-series, permanent plots, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology., The authors acknowledge institutional support as follows. Nicola J. Day: Te Apārangi Royal Society of New Zealand (Rutherford Postdoctoral Fellowship). Jiří Danihelka: Czech Science Foundation (project no. 19-28491X) and Czech Academy of Sciences (project no. RVO 67985939). Francesco de Bello: Spanish Plan Nacional de I+D+i (project PGC2018-099027-B-I00). Eric Garnier: La Fage INRA experimental station. Tomáš Herben: GAČR grant 20-02901S. Anke Jentsch: German Federal Ministry of Education and Research (grant 031B0516C - SUSALPS) and Oberfrankenstiftung (grant OFS FP00237). Norbert Juergens: German Federal Ministry of Education and Research (grant 01LG1201N - SASSCAL ABC). Frédérique Louault and Katja Klumpp: AnaEE-France (ANR-11-INBS-0001). Robin J. Pakeman: Strategic Research Programme of the Scottish Government's Rural and Environment Science and Analytical Services Division. Meelis Pärtel: Estonian Research Council (PRG609) and European Regional Development Fund (Centre of Excellence EcolChange). Josep Peñuelas: Spanish Government (grant PID2019-110521GB-I00), Fundación Ramon Areces (grant ELEMENTAL-CLIMATE), Catalan Government (grant SGR 2017-1005), and European Research Council (Synergy grant ERC-SyG-2013-610028, IMBALANCE-P). Ute Schmiedel: German Federal Ministry of Education and Research (Promotion numbers 01LC0024, 01LC0024A, 01LC0624A2, 01LG1201A, 01LG1201N). Hana Skálová: GAČR grant 20-02901S. Karsten Wesche: International Institute Zittau, Technische Universität Dresden. Susan K. Wiser: New Zealand Ministry for Business, Innovation and Employment’s Strategic Science Investment Fund. Ben A. Woodcock: NERC and BBSRC (NE/N018125/1 LTS-M ASSIST - Achieving Sustainable Agricultural Systems). Enrique Valencia: Program for attracting and retaining talent of Comunidad de Madrid (no. 2017-T2/AMB-5406) and Community of Madrid and Rey Juan Carlos University (Young Researchers R&D Project. Ref. M2165 – INTRANESTI). Truman P. Young: National Science Foundation (LTREB DEB 19-31224).

Published
2022
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2. TEMPORANA: Flexible Temporal Query Processing for Supporting System Behavior Detection across Complex Scenarios

Author

Maria Luisa Villani, Alfredo Cuzzocrea, Antonio De Nicola, Hugo Maldini, Ilaria D'Elia, Villani, M. L., De Nicola, A., D'Elia, I., Cuzzocrea, Alfredo Massimiliano, D’Elia, Ilaria, Nicola, Antonio De, Maldini, Hugo, and Villani, Maria Luisa

Subjects
Computer science, business.industry, Temporal Analysis, Scenarios Management, Environmental Modeling, 02 engineering and technology, computer.software_genre, Field (computer science), Set (abstract data type), Operator (computer programming), Software, Temporal Analysi, Linear temporal logic, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Environmental Modeling, Temporal Analysis, Scenarios Management, Data mining, business, computer, Energy (signal processing)
Abstract

We propose the TEMPORANA framework foranalysis of integrated scenarios aiming at studying the possibleeffects on the society of sustainable innovation policies. Theframework consists of a set of advanced temporal queries forscenario analysis and a software application. Integrated scenariosare possible future states of different aspects of the world(e.g., energy, environment, technology, economy, societal system) representing plausible conditions under different assumptions. Temporal scenario queries aim at detecting a specified behaviorfor the system over time and, hence, at verifying that a temporalproperty holds. A preliminary set of queries, each involving onetemporal operator from the Linear Temporal Logic, were definedby field experts and used in a preliminary experimentation todemonstrate the applicability of the approach. © 2016 IEEE.

Published
2017
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3. Recurrence time distribution and temporal clustering properties of a cellular automaton modelling landslide events

Author

R. Di Maio, Adolfo Avella, Ester Piegari, Piegari, Ester, DI MAIO, Rosa, and Avella, A.

Subjects
landslide, Fano factor, Series (mathematics), probability, Crossover, lcsh:QC801-809, modeling, Landslide, Poisson distribution, Cellular automaton, lcsh:QC1-999, Physics::Geophysics, temporal analysi, symbols.namesake, lcsh:Geophysics. Cosmic physics, Statistics, symbols, Probability distribution, lcsh:Q, cellular automaton, lcsh:Science, Weibull theory, Geology, lcsh:Physics, Weibull distribution
Abstract

Reasonable prediction of landslide occurrences in a given area requires the choice of an appropriate probability distribution of recurrence time intervals. Although landslides are widespread and frequent in many parts of the world, complete databases of landslide occurrences over large periods are missing and often such natural disasters are treated as processes uncorrelated in time and, therefore, Poisson distributed. In this paper, we examine the recurrence time statistics of landslide events simulated by a cellular automaton model that reproduces well the actual frequency-size statistics of landslide catalogues. The complex time series are analysed by varying both the threshold above which the time between events is recorded and the values of the key model parameters. The synthetic recurrence time probability distribution is shown to be strongly dependent on the rate at which instability is approached, providing a smooth crossover from a power-law regime to a Weibull regime. Moreover, a Fano factor analysis shows a clear indication of different degrees of correlation in landslide time series. Such a finding supports, at least in part, a recent analysis performed for the first time of an historical landslide time series over a time window of fifty years.

Published
2013

4. Towards Temporal Analysis of Integrated Scenarios for Sustainable Innovation

Author

Maria Luisa Villani, Hugo Maldini, Alfredo Cuzzocrea, Ilaria D'Elia, Antonio De Nicola, Osvaldo Gervasi et al., Cuzzocrea, Alfredo Massimiliano, D’Elia, Ilaria, De Nicola, Antonio, Maldini, Hugo, and Villani, Maria Luisa

Subjects
Knowledge management, Property (philosophy), Computer science, Energy (esotericism), Sustainable innovation, Environmental modelling, 02 engineering and technology, Theoretical Computer Science, Set (abstract data type), Software, Temporal analysi, 020204 information systems, Scenarios management, 0202 electrical engineering, electronic engineering, information engineering, Scenario analysis, Temporal analysis, Computer Science (all), business.industry, 05 social sciences, 050301 education, Environmental economics, business, 0503 education
Abstract

We propose the TEMPORANA framework for analysis of integrated scenarios aiming at studying the possible effects on the society of sustainable innovation policies. The framework consists of a set of advanced temporal queries for scenario analysis and a software application. Integrated scenarios are possible future states of different aspects of the world (e.g., energy, environment, technology, economy, societal system) representing plausible conditions under different assumptions. Temporal scenario queries aim at detecting a specified behavior for the system over time and, hence, at verifying that a temporal property holds.

Published
2016
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5. An attempt to predict the failure time of abandoned mine pillars

Author

Roberto Nova, Eleni Gerolymatou, Riccardo Castellanza, Castellanza, R, Gerolymatou, E, and Nova, R

Subjects
Gypsum, pillar, water, Collapse, failure analysi, Weathering, Compressive strength, Experimental data, Mine, engineering.material, experimental study, chemistry.chemical_compound, Time to failure, Abandoned mines, anhydrite, Geotechnical engineering, Northern Italy, Bearing capacity, weathering rate, Weathering, Axisymmetric, Civil and Structural Engineering, Plane stress, Soil mechanic, Anhydrite, bearing capacity, testing method, Pillar, Geology, Room and pillar mining, modeling, mechanical strength, prediction, Geotechnical Engineering and Engineering Geology, Northern italy, Strength of material, failure time, temporal analysi, Sulfate mineral, chemistry, engineering, plane strain, ICAR/07 - GEOTECNICA, Closed form solution
Abstract

Left in place pillars of abandoned mines are subject to weathering (e.g action of water, bacteria) that degrades their mechanical strength and eventually leads to collapse. A simple weathering model is proposed, that is governed by two parameters: the rate of progression of weathered front and the rate of degradation of the compressive strength with time. Both plane strain and axisymmetric analyses are performed and closed form solutions of the variation with time of the bearing capacity of the pillar are given. Experimental data of the tests conducted on gypsum and anhydrite specimens attacked by water are presented. It is shown that in order to fit the experimental data a third parameter must be introduced. New closed form solutions are given and the data are used for estimating the time to failure of abandoned gypsum mines in Northern Italy. © 2007 Springer-Verlag.

Published
2008

6. An attempt to predict the failure time of abandoned mine pillars

Author

Castellanza, R, Gerolymatou, E, Nova, R, CASTELLANZA, RICCARDO PIETRO, Nova, R., Castellanza, R, Gerolymatou, E, Nova, R, CASTELLANZA, RICCARDO PIETRO, and Nova, R.

Abstract

Left in place pillars of abandoned mines are subject to weathering (e.g action of water, bacteria) that degrades their mechanical strength and eventually leads to collapse. A simple weathering model is proposed, that is governed by two parameters: the rate of progression of weathered front and the rate of degradation of the compressive strength with time. Both plane strain and axisymmetric analyses are performed and closed form solutions of the variation with time of the bearing capacity of the pillar are given. Experimental data of the tests conducted on gypsum and anhydrite specimens attacked by water are presented. It is shown that in order to fit the experimental data a third parameter must be introduced. New closed form solutions are given and the data are used for estimating the time to failure of abandoned gypsum mines in Northern Italy. © 2007 Springer-Verlag.

Published
2008

7. Accurate classification of bioclimatic data: Temporal analysis

Author

Passarella, G., Barca, E., Bruno, D., Sabino Maggi, Masciale, R., Lay-Ekuakille, A., Passarella, G., Barca, E., Bruno, D., Maggi, S., Masciale, R., and Lay-Ekuakille, A.

Subjects
temporal analysis, Temporal analysi, Bioclimatic indice, Time-serie, bioclimatic index, Trend test
Abstract

This paper presents a general methodology for processing bioclimatic data in the temporal domain. Two different methods are used to assess the presence of temporal trends in the time-series of bioclimatic indices at each mea- surement station. A preliminary stage checks for the statistical homogeneity in the data set and for the presence of serial autocorrelation in the data, applying the proper methods to remove these effects. The methodology has been applied to a case study in Apulia, Italy, using the popular De Martonne index as a bioclimatic indicator.

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