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Species distribution modelling under climate change scenarios for maritime pine (Pinus pinaster Aiton) in Portugal / Cristina Alegria in Forests, vol 14 n° 3 (March 2023)
[article]
Titre : Species distribution modelling under climate change scenarios for maritime pine (Pinus pinaster Aiton) in Portugal Type de document : Article/Communication Auteurs : Cristina Alegria, Auteur ; Alice M. Almeida, Auteur ; Natalia Roque, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 591 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] distribution spatiale
[Termes IGN] entropie maximale
[Termes IGN] gestion forestière
[Termes IGN] modèle de simulation
[Termes IGN] modélisation de la forêt
[Termes IGN] Pinus pinaster
[Termes IGN] Portugal
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) To date, a variety of species potential distribution mapping approaches have been used, and the agreement in maps produced with different methodological approaches should be assessed. The aims of this study were: (1) to model Maritime pine potential distributions for the present and for the future under two climate change scenarios using the machine learning Maximum Entropy algorithm (MaxEnt); (2) to update the species ecological envelope maps using the same environmental data set and climate change scenarios; and (3) to perform an agreement analysis for the species distribution maps produced with both methodological approaches. The species distribution maps produced by each of the methodological approaches under study were reclassified into presence–absence binary maps of species to perform the agreement analysis. The results showed that the MaxEnt-predicted map for the present matched well the species’ current distribution, but the species ecological envelope map, also for the present, was closer to the species’ empiric potential distribution. Climate change impacts on the species’ future distributions maps using the MaxEnt were moderate, but areas were relocated. The 47.3% suitability area (regular-medium-high), in the present, increased in future climate change scenarios to 48.7%–48.3%. Conversely, the impacts in species ecological envelopes maps were higher and with greater future losses than the latter. The 76.5% suitability area (regular-favourable-optimum), in the present, decreased in future climate change scenarios to 58.2%–51.6%. The two approaches combination resulted in a 44% concordance for the species occupancy in the present, decreasing around 30%–35% in the future under the climate change scenarios. Both methodologies proved to be complementary to set species’ best suitability areas, which are key as support decision tools for planning afforestation and forest management to attain fire-resilient landscapes, enhanced forest ecosystems biodiversity, functionality and productivity. Numéro de notice : A2023-167 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f14030591 Date de publication en ligne : 16/03/2023 En ligne : https://doi.org/10.3390/f14030591 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102904
in Forests > vol 14 n° 3 (March 2023) . - n° 591[article]The potential of combining satellite and airborne remote sensing data for habitat classification and monitoring in forest landscapes / Anna Iglseder in International journal of applied Earth observation and geoinformation, vol 117 (March 2023)
[article]
Titre : The potential of combining satellite and airborne remote sensing data for habitat classification and monitoring in forest landscapes Type de document : Article/Communication Auteurs : Anna Iglseder, Auteur ; Markus Immitzer, Auteur ; Alena Dostalova, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 103131 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte thématique
[Termes IGN] cartographie écologique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données Copernicus
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt
[Termes IGN] habitat (nature)
[Termes IGN] habitat forestier
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] modèle numérique de surface
[Termes IGN] protection de la biodiversité
[Termes IGN] site Natura 2000
[Termes IGN] Vienne (capitale Autriche)Résumé : (auteur) Mapping and monitoring of habitats are requirements for protecting biodiversity. In this study, we investigated the benefit of combining airborne (laser scanning, image-based point clouds) and satellite-based (Sentinel 1 and 2) data for habitat classification. We used a two level random forest 10-fold leave-location-out cross-validation workflow to model Natura 2000 forest and grassland habitat types on a 10 m pixel scale at two study sites in Vienna, Austria. We showed that models using combined airborne and satellite-based remote sensing data perform significantly better for forests than airborne or satellite-based data alone. For frequently occurring classes, we reached class accuracies with F1-scores from 0.60 to 0.87. We identified clear difficulties of correctly assigning rare classes with model-based classification. Finally, we demonstrated the potential of the workflow to identify errors in reference data and point to the opportunities for integration in habitat mapping and monitoring. Numéro de notice : A2023-128 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.103131 Date de publication en ligne : 12/01/2023 En ligne : https://doi.org/10.1016/j.jag.2022.103131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102512
in International journal of applied Earth observation and geoinformation > vol 117 (March 2023) . - n° 103131[article]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)
[article]
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 climatiqueRésumé : (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
in Forest ecology and management > vol 530 (February-15 2023) . - n° 120753[article]A GIS-based method for modeling methane emissions from paddy fields by fusing multiple sources of data / Linhua Ma in Science of the total environment, vol 859 n° 1 (February 2023)
[article]
Titre : A GIS-based method for modeling methane emissions from paddy fields by fusing multiple sources of data Type de document : Article/Communication Auteurs : Linhua Ma, Auteur ; Yuanlai Cui, Auteur ; Bo Liu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 159917 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatio-temporelle
[Termes IGN] Chine
[Termes IGN] Corée
[Termes IGN] données multisources
[Termes IGN] Etats-Unis
[Termes IGN] humidité du sol
[Termes IGN] image à haute résolution
[Termes IGN] image infrarouge
[Termes IGN] Italie
[Termes IGN] méthane
[Termes IGN] modélisation
[Termes IGN] réflectance du sol
[Termes IGN] rizière
[Termes IGN] système d'information géographique
[Termes IGN] variation saisonnièreRésumé : (auteur) Quantification of regional methane (CH4) gas emission in the paddy fields is critical under climate warming. Mechanism models generally require numerous parameters while empirical models are too coarse. Based on the mechanism and structure of the widely used model CH4MOD, a GIS-based Regional CH4 Emission Calculation (GRMC) method was put forward by introducing multiple sources of remote sensing images, including MOD09A1, MOD11A2, MOD15A2H as well as local water management standards. The stress of soil moisture condition (f(water)) on CH4 emissions was quantified by calculating the redox potential (Eh) from days after flooding or falling dry. The f(water)-t curve was calculated under different exogenous organic matter addition. Combining the f(water)-t curve with local water management standards, the seasonal variation of f(water) was obtained. It was proven that f(water) was effective in reflecting the regulation role of soil moisture condition. The GRMC was tested at four Eddy Covariance (EC) sites: Nanchang (NC) in China, Twitchell (TWT) in the USA, Castellaro (CAS) in Italy and Cheorwon (CRK) in Korea and has been proven to well track the seasonal dynamics of CH4 emissions with R2 ranges of 0.738–0.848, RMSE ranges of 31.94–149.22 mg C/m2d and MBE ranges of −66.42- -14.79 mg C/m2d. The parameters obtained in Nanchang (NC) site in China were then applied to the Ganfu Plain Irrigation System (GFPIS), a typical rice planting area of China, to analyse the spatial-temporal variations of CH4 emissions. The total CH4 emissions of late rice in the GFPIS from 2001 to 2013 was in the range of 14.47–20.48 (103 t CH4-C). Ts caused spatial variation of CH4 production capacity, resulting in the spatial variability of CH4 emissions. Overall, the GRMC is effective in obtaining CH4 emissions from rice fields on a regional scale. Numéro de notice : A2023-015 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1016/j.scitotenv.2022.159917 Date de publication en ligne : 04/11/2022 En ligne : https://doi.org/10.1016/j.scitotenv.2022.159917 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102133
in Science of the total environment > vol 859 n° 1 (February 2023) . - n° 159917[article]Analysing urban growth using machine learning and open data: An artificial neural network modelled case study of five Greek cities / Pavlos Tsagkis in Sustainable Cities and Society, vol 89 (February 2023)
[article]
Titre : Analysing urban growth using machine learning and open data: An artificial neural network modelled case study of five Greek cities Type de document : Article/Communication Auteurs : Pavlos Tsagkis, Auteur ; Efthimios Bakogiannis, Auteur ; Alexandros Nikitas, Auteur Année de publication : 2023 Article en page(s) : n° 104337 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] Corine (base de données)
[Termes IGN] croissance urbaine
[Termes IGN] données localisées libres
[Termes IGN] étalement urbain
[Termes IGN] Grèce
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle orienté agent
[Termes IGN] OpenStreetMap
[Termes IGN] planification urbaine
[Termes IGN] réseau neuronal artificielRésumé : (auteur) Urban development if not planned and managed adequately can be unsustainable. Urban growth models have been a powerful toolkit to help tackling this challenge. In this paper, we use a machine learning approach, to apply an urban growth model to five of the largest cities in Greece. Specifically, we first develop a methodology to collect, organise, handle and transform historical open spatial data, concerning various impact factors, into machine learning data. Such factors involve social, economic, biophysical, neighbouring-related and political driving forces, which must be transformed into tabular data. We also provide an artificial neural network (ANN) model and the methodology to train and evaluate it using goodness-of-fit metrics, which in turn provide the best weights of impact factors. Finally, we execute a prediction for 2030, presenting the results and output maps for each of the five case study cities. As our study is based on pan-European datasets, our model can be used for any area within Europe, using the open-source utility developed to support it. In this sense, our work provides local policy-makers and urban planners with an instrument that could help them analyse various future development scenarios and take the right decisions going forward. Numéro de notice : A2023-116 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.scs.2022.104337 Date de publication en ligne : 05/12/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104337 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102486
in Sustainable Cities and Society > vol 89 (February 2023) . - n° 104337[article]Can mixed forests sequester more CO2 than pure forests in future climate scenarios? A case study of Pinus sylvestris combinations in Spain / Diego Rodríguez de Prado in European Journal of Forest Research, vol 142 n° 1 (February 2023)PermalinkEvaluation of growth models for mixed forests used in Swedish and Finnish decision support systems / Jorge Aldea in Forest ecology and management, vol 529 (February-1 2023)PermalinkForest structure and fine root biomass influence soil CO2 efflux in temperate forests under drought / Antonios Apostolakis in Forests, vol 14 n° 2 (February 2023)PermalinkLong-term changes in 3D urban form in four Spanish cities / Dario Domingo in Landscape and Urban Planning, vol 230 (February 2023)PermalinkNonparametric upscaling of bark beetle infestations and management from plot to landscape level by combining individual-based with Markov chain models / Bruno Walter Pietzsch in European Journal of Forest Research, vol 142 n° 1 (February 2023)PermalinkStochastic multicriteria acceptability analysis as a forest management priority mapping approach based on airborne laser scanning and field inventory data / Parvez Rana in Landscape and Urban Planning, vol 230 (February 2023)PermalinkTesting the application of process-based forest growth model PREBAS to uneven-aged forests in Finland / Man Hu in Forest ecology and management, vol 529 (February-1 2023)PermalinkTree growth, wood anatomy and carbon and oxygen isotopes responses to drought in Mediterranean riparian forests / J. Julio Camarero in Forest ecology and management, vol 529 (February-1 2023)PermalinkModelling the dynamics of Pinus sylvestris forests after a die-off event under climate change scenarios / Jordi Margalef- Marrase in Science of the total environment, vol 856 n° 2 (January 2023)Permalink3D building metrics for urban morphology / Anna Labetski in International journal of geographical information science IJGIS, vol 37 n° 1 (January 2023)Permalink