Centre de documentation
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Tree species growth response to climate in mixtures of Quercus robur/Quercus petraea and Pinus sylvestris across Europe - a dynamic, sensitive equilibrium / Sonja Vospernik in Forest ecology and management, vol 530 (February-15 2023)  

Public [article]  inForest ecology and management > vol 530 (February-15 2023) . - n° 120753 Titre : Tree species growth response to climate in mixtures of Quercus robur/Quercus petraea and Pinus sylvestris across Europe - a dynamic, sensitive equilibrium Type de document : Article/Communication Auteurs : Sonja Vospernik, Auteur ; Michael Heym, Auteur ; Hans Pretzsch, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120753 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] climat [Termes IGN] croissance des arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] Europe (géographie politique) [Termes IGN] évapotranspiration [Termes IGN] forêt inéquienne [Termes IGN] modèle dynamique [Termes IGN] peuplement mélangé [Termes IGN] Pinus sylvestris [Termes IGN] Quercus pedunculata [Termes IGN] Quercus sessiliflora [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Quercus robur/Quercus petraea and Pinus sylvestris are widely distributed and economically important tree species in Europe co-occurring on mesotrophic, xeric and mesic sites. Increasing dry conditions may reduce their growth, but growth reductions may be modified by mixture, competition and site conditions. The annual diameter growth in monospecific and mixed stands along an ecological gradient with mean annual temperatures ranging from 5.5 °C to 11.5 °C was investigated in this study. On 36 triplets (108 plots), trees were cored and the year-ring series were cross-dated, resulting in year-ring series of 785 and 804 trees for Q. spp. and P. sylvestris, respectively. A generalized additive model with a logarithmic link was fit to the data with random effects for the intercept at the triplet, year and tree level and a random slope for the covariate age for each tree; the Tweedie-distribution was used. The final model explained 87 % of the total variation in diameter increment for both tree species. Significant covariates were age, climate variables (long-term mean, monthly), local competition variables, relative dbh, mixture, stand structure and interactions thereof. Tree growth declined with age and local density and increased with social position. It was positively influenced by mixture and structural diversity (Gini coefficient); mixture effects were significant for P. sylvestris only. The influence of potential evapotranspiration (PET) in spring and autumn on tree growth was positive and non-linear, whereas tree growth sharply decreased with increasing PET in June, which proved to be the most influential month on tree growth along the whole ecological gradient. Interactions of PET with tree social position (relative dbh) were significant in July and September for Q. spp. and in April for P. sylvestris. Interactions of climate with density or mixture were not significant. Climatic effects found agree well with previous results from intra-annual growth studies and indicate that the model captures the causal factors for tree growth well. Furthermore, the interaction between climate and relative dbh might indicate a longer growth duration for trees of higher social classes. Analysis of random effects across time and space showed highly dynamic patterns, with competitive advantages changing annually between species and spatial patterns showing no large-scale trends but pointing to the prevalence of local site factors. In mixed-species stands, the tree species have the same competitivity in the long-term, which is modified by climate each year. Climate warming will shift the competitive advantages, but the direction will be highly site-specific. Numéro de notice : A2023-108 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120753 Date de publication en ligne : 29/12/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102443 [article]

The cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 1 (January 2023)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 1 (January 2023) . - pp 47 - 55 Titre : The cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan Type de document : Article/Communication Auteurs : Muhammad Nasar Ahmad, Auteur ; Zhenfeng Shao, Auteur ; Akib Javed, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 47 - 55 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] automate cellulaire [Termes IGN] carte thématique [Termes IGN] classification semi-dirigée [Termes IGN] détection de changement [Termes IGN] données vectorielles [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] MNS SRTM [Termes IGN] modèle dynamique [Termes IGN] occupation du sol [Termes IGN] Pakistan [Termes IGN] surveillance de l'urbanisation [Termes IGN] utilisation du sol Résumé : (auteur) Rapid urbanization has become an immense problem in Lahore city, causing various socio-economic and environmental problems. Therefore, it is noteworthy to monitor land use/land cover (LULC) change detection and future LULC patterns in Lahore. The present study focuses on evaluating the current extent and modeling the future LULC developments in Lahore, Pakistan. Therefore, the semi-automatic classification model has been applied for the classification of Landsat satellite imagery from 2000 to 2020. And the Modules of Land Use Change Evaluation (MOLUSCE) cellular automata (CA-ANN) model was implemented to simulate future land use trends for the years 2030 and 2040. This study project made use of Landsat, Shuttle Radar Topography Mission Digital Elevation Model, and vector data. The research methodology includes three main steps: (i) semi-automatic land use classification using Landsat data from 2000 to 2020; (ii) future land use prediction using the CA-ANN (MOLUSCE) model; and (iii) monitoring change detection and interpretation of results. The research findings indicated that there was a rise in urban areas and a decline in vegetation, barren land, and water bodies for both the past and future projections. The results also revealed that about 27.41% of the urban area has been increased from 2000 to 2020 with a decrease of 42.13% in vegetation, 2.3% in barren land, and 6.51% in water bodies, respectively. The urban area is also expected to grow by 23.15% between 2020 and 2040, whereas vegetation, barren land, and water bodies will all decline by 28.05%, 1.8%, and 12.31%, respectively. Results can also aid in the long-term, sustainable planning of the city. It was also observed that the majority of the city's urban area expansion was found to have occurred in the city's eastern and southern regions. This research also suggests that decision-makers and municipal Government should reconsider city expansion strategies. Moreover, the future city master plans of 2050 must emphasize the relevance of rooftop urban planting and natural resource conservation. Numéro de notice : A2023-047 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.14358/PERS.22-00102R2 Date de publication en ligne : 01/01/2023 En ligne : https://doi.org/10.14358/PERS.22-00102R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102357 [article]

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Climate envelope analyses suggests significant rearrangements in the distribution ranges of Central European tree species / Gàbor Illés in Annals of Forest Science, vol 79 n° 1 (2022)  

Public [article]  inAnnals of Forest Science > vol 79 n° 1 (2022) . - n° 35 Titre : Climate envelope analyses suggests significant rearrangements in the distribution ranges of Central European tree species Type de document : Article/Communication Auteurs : Gàbor Illés, Auteur ; Norbert Móricz, Auteur Année de publication : 2022 Article en page(s) : n° 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] adaptation (biologie) [Termes IGN] bioclimatologie [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] Europe centrale [Termes IGN] Fagus sylvatica [Termes IGN] gestion forestière durable [Termes IGN] INSPIRE [Termes IGN] modèle dynamique [Termes IGN] modélisation de la forêt [Termes IGN] Picea abies [Termes IGN] Quercus cerris [Termes IGN] Quercus pubescens [Termes IGN] Quercus sessiliflora [Termes IGN] répartition géographique [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Key message: Climate envelope analysis of nine tree species shows that Fagus sylvatica L. and Picea abies H. Karst could lose 58% and 40% of their current distribution range. Quercus pubescens Willd and Quercus cerris L. may win areas equal with 47% and 43% of their current ranges. The ratio of poorly predictable areas increases by 105% in southern and south-eastern Europe. Context: Climate change requires adaptive forest management implementations. To achieve climate neutrality, we have to maintain and expand forest areas. Impact assessments have great importance. Aims: The study estimates the potential climate envelopes of nine European tree species for a past period (1961–1990) and for three future periods (2011–2040, 2041–2070, 2071–2100) under two emission scenarios (RCP4.5 and RCP8.5) based on the current species distribution. Methods: Climate envelopes were estimated simultaneously using the random forest method. Multi-resolution segmentation was used to determine the climatic characteristics of each species and their combinations. Models were limited to the geographical area within which the climatic conditions correspond to the climatic range of the training areas. Results: Results showed remarkable changes in the extent of geographic areas of all the investigated species’ climate envelopes. Many of the tree species of Central Europe could lose significant portions of their distribution range. Adhering to the shift in climate, these tree species shift further north as well as towards higher altitudes. Conclusion: European forests face remarkable changes, and the results support climate envelope modelling as an important tool that provides guidelines for climate adaptation to identify threatened areas or to select source and destination areas for reproductive material. Numéro de notice : A2022-631 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s13595-022-01154-8 Date de publication en ligne : 09/08/2022 En ligne : https://doi.org/10.1186/s13595-022-01154-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101395 [article]

Human mobility and COVID-19 transmission: a systematic review and future directions / Mengxi Zhang in Annals of GIS, vol 28 n° 4 (November 2022)  

Public [article]  inAnnals of GIS > vol 28 n° 4 (November 2022) . - pp 501 - 514 Titre : Human mobility and COVID-19 transmission: a systematic review and future directions Type de document : Article/Communication Auteurs : Mengxi Zhang, Auteur ; Siqin Wang, Auteur ; Tao Hu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 501 - 514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] corrélation automatique de points homologues [Termes IGN] données spatiotemporelles [Termes IGN] épidémie [Termes IGN] hétérogénéité spatiale [Termes IGN] littérature [Termes IGN] maladie virale [Termes IGN] mobilité humaine [Termes IGN] mobilité territoriale [Termes IGN] modèle dynamique [Termes IGN] modélisation spatio-temporelle [Termes IGN] régression linéaire Résumé : (auteur) Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To better understand the role of human mobility in the pandemic, we conducted a systematic review of articles that measure the relationship between human mobility and COVID-19 in terms of their data sources, mathematical models, and key findings. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we selected 47 articles from the Web of Science Core Collection up to September 2020. Restricting human mobility reduced the transmission of COVID-19, although the effectiveness and stringency of policy implementation vary temporally and spatially across different stages of the pandemic. We call for prompt and sustainable measures to control the pandemic. We also recommend researchers 1) to enhance multi-disciplinary collaboration; 2) to adjust the implementation and stringency of mobility-control policies in corresponding to the rapid change of the pandemic; 3) to improve mathematical models used in analysing, simulating, and predicting the transmission of the disease; and 4) to enrich the source of mobility data to ensure data accuracy and suability. Numéro de notice : A2022-863 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475683.2022.2041725 Date de publication en ligne : 03/03/2022 En ligne : https://doi.org/10.1080/19475683.2022.2041725 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102153 [article]

Multiscale assimilation of Sentinel and Landsat data for soil moisture and Leaf Area Index predictions using an ensemble-Kalman-filter-based assimilation approach in a heterogeneous ecosystem / Nicola Montaldo in Remote sensing, vol 14 n° 14 (July-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 14 (July-2 2022) . - n° 3458 Titre : Multiscale assimilation of Sentinel and Landsat data for soil moisture and Leaf Area Index predictions using an ensemble-Kalman-filter-based assimilation approach in a heterogeneous ecosystem Type de document : Article/Communication Auteurs : Nicola Montaldo, Auteur ; Andrea Gaspa, Auteur ; Roberto Corona, Auteur Année de publication : 2022 Article en page(s) : n° 3458 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] assimilation des données [Termes IGN] bassin méditerranéen [Termes IGN] écosystème [Termes IGN] filtre de Kalman [Termes IGN] humidité du sol [Termes IGN] image Landsat-8 [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] Leaf Area Index [Termes IGN] modèle dynamique [Termes IGN] modèle hydrographique [Termes IGN] Sardaigne [Termes IGN] zone semi-aride Résumé : (auteur) Data assimilation techniques allow researchers to optimally merge remote sensing observations in ecohydrological models, guiding them for improving land surface fluxes predictions. Presently, freely available remote sensing products, such as those of Sentinel 1 radar, Landsat 8 sensors, and Sentinel 2 sensors, allow the monitoring of land surface variables (e.g., radar backscatter for soil moisture and the normalized difference vegetation index (NDVI) and for leaf area index (LAI)) at unprecedentedly high spatial and time resolutions, appropriate for heterogeneous ecosystems, typical of semiarid ecosystems characterized by contrasting vegetation components (grass and trees) competing for water use. A multiscale assimilation approach that assimilates radar backscatter and grass and tree NDVI in a coupled vegetation dynamic–land surface model is proposed. It is based on the ensemble Kalman filter (EnKF), and it is not limited to assimilating remote sensing data for model predictions, but it uses assimilated data for dynamically updating key model parameters (the ENKFdc approach), including saturated hydraulic conductivity and grass and tree maintenance respiration coefficients, which are highly sensitive parameters of soil–water balance and biomass budget models, respectively. The proposed EnKFdc assimilation approach facilitated good predictions of soil moisture, grass, and tree LAI in a heterogeneous ecosystem in Sardinia for a 3-year period with contrasting hydrometeorological (dry vs. wet) conditions. Contrary to the EnKF-based approach, the proposed EnKFdc approach performed well for the full range of hydrometeorological conditions and parameters, even assuming extremely biased model conditions with very high or low parameter values compared with the calibrated (“true”) values. The EnKFdc approach is crucial for soil moisture and LAI predictions in winter and spring, key seasons for water resources management in Mediterranean water-limited ecosystems. The use of ENKFdc also enabled us to predict evapotranspiration and carbon flux well, with errors of less than 4% and 15%, respectively; such results were obtained even with extremely biased initial model conditions. Numéro de notice : A2022-574 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14143458 En ligne : https://doi.org/10.3390/rs14143458 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101293 [article]

Global forecasting of ionospheric vertical total electron contents via ConvLSTM with spectrum analysis / Jinpei Chen in GPS solutions, vol 26 n° 3 (July 2022)  

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Trade-offs between sustainable development goals in systems of cities / Juste Raimbault in Journal of Urban Management, vol 11 n° 2 (June 2022)  

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Simulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data / Zihao Huang in Remote sensing, vol 14 n° 7 (April-1 2022)  

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Cartographie dynamique de la topographie de l'océan de surface par assimilation de données altimétriques / Florian Le Guillou (2022)  

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Investigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations / E-Ping Rau (2022)  

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Calibration of cellular automata urban growth models from urban genesis onwards - a novel application of Markov chain Monte Carlo approximate Bayesian computation / Jingyan Yu in Computers, Environment and Urban Systems, vol 90 (November 2021)  

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Geoglam, l'agriculture par satellite / Laurent Polidori in Géomètre, n° 2194 (septembre 2021)

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A hybrid data model for dynamic GIS: application to marine geomorphological dynamics / Younes Hamdani in International journal of geographical information science IJGIS, vol 35 n° 8 (August 2021)  

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Dynamic optimization models for displaying outdoor advertisement at the right time and place / Meng Huang in International journal of geographical information science IJGIS, vol 35 n° 6 (June 2021)  

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Numerical modelling for analysis of the effect of different urban green spaces on urban heat load patterns in the present and in the future / Tamás Gál in Computers, Environment and Urban Systems, vol 87 (May 2021)  

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