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Linking structure and species richness to support forest biodiversity monitoring at large scales / Félix Storch in Annals of Forest Science, vol 80 n° 1 (2023)
[article]
Titre : Linking structure and species richness to support forest biodiversity monitoring at large scales Type de document : Article/Communication Auteurs : Félix Storch, Auteur ; Steffen Boch, Auteur ; Martin M. Gossner, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Allemagne
[Termes IGN] biodiversité végétale
[Termes IGN] botanique systématique
[Termes IGN] écosystème forestier
[Termes IGN] gestion forestière durable
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] peuplement mélangé
[Termes IGN] protection de la biodiversité
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] surveillance de la végétation
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Key message: Authors have analyzed the possible correlation between measurements/indicators of forest structure and species richness of many taxonomic or functional groups over three regions of Germany. Results show the potential to use structural attributes as a surrogate for species richness of most of the analyzed taxonomic and functional groups. This information can be transferred to large-scale forest inventories to support biodiversity monitoring.
Context: We are currently facing a dramatic loss in biodiversity worldwide and this initiated many monitoring programs aiming at documenting further trends. However, monitoring species diversity directly is very resource demanding, in particular in highly diverse forest ecosystems.
Aims: We investigated whether variables applied in an index of stand structural diversity, which was developed based on forest attributes assessed in the German National Forest Inventory, can be calibrated against richness of forest-dwelling species within a wide range of taxonomic and functional groups.
Methods: We used information on forest structure and species richness that has been comprehensively assessed on 150 forest plots of the German biodiversity exploratories project, comprising a large range of management intensities in three regions. We tested, whether the forest structure index calculated for these forest plots well correlate with the number of species across 29 taxonomic and functional groups, assuming that the structural attributes applied in the index represent their habitat requirements.
Results: The strength of correlations between the structural variables applied in the index and number of species within taxonomic or functional groups was highly variable. For some groups such as Aves, Formicidae or vascular plants, structural variables had a high explanatory power for species richness across forest types. Species richness in other taxonomic and functional groups (e.g., soil and root-associated fungi) was not explained by individual structural attributes of the index. Results indicate that some taxonomic and functional groups depend on a high structural diversity, whereas others seem to be insensitive to it or even prefer structurally poor stands.
Conclusion: Therefore, combinations of forest stands with different degrees of structural diversity most likely optimize taxonomic diversity at the landscape level. Our results can support biodiversity monitoring through quantification of forest structure in large-scale forest inventories. Changes in structural variables over inventory periods can indicate changes in habitat quality for individual taxonomic groups and thus points towards national forest inventories being an effective tool to detect unintended effects of changes in forest management on biodiversity.Numéro de notice : A2023-144 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s13595-022-01169-1 Date de publication en ligne : 19/01/2023 En ligne : https://doi.org/10.1186/s13595-022-01169-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102720
in Annals of Forest Science > vol 80 n° 1 (2023) . - n° 3[article]Mapping territorial vulnerability to wildfires: A participative multi-criteria analysis / Miguel Rivière in Forest ecology and management, vol 539 (July-1 2023)
[article]
Titre : Mapping territorial vulnerability to wildfires: A participative multi-criteria analysis Type de document : Article/Communication Auteurs : Miguel Rivière, Auteur ; Jonathan Lenglet, Auteur ; Adrien Noirault, Auteur ; et al., Auteur Année de publication : 2023 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse multicritère
[Termes IGN] cartographie des risques
[Termes IGN] incendie de forêt
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] Rhône-Méditerranée-Corse
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du sol
[Termes IGN] vulnérabilitéNuméro de notice : A2023-216 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1016/j.foreco.2023.121014 Date de publication en ligne : 22/04/2023 En ligne : https://doi.org/10.1016/j.foreco.2023.121014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103146
in Forest ecology and management > vol 539 (July-1 2023)[article]Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak / A.P. Rudke in Remote sensing of environment, vol 289 (May 2003)
[article]
Titre : Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak Type de document : Article/Communication Auteurs : A.P. Rudke, Auteur ; J.A. Martins, Auteur ; R. Hallak, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] correction atmosphérique
[Termes IGN] dioxyde d'azote
[Termes IGN] épidémie
[Termes IGN] image Sentinel-5P-TROPOMI
[Termes IGN] image Terra-MODIS
[Termes IGN] pollution atmosphérique
[Termes IGN] qualité de l'air
[Termes IGN] Sao PauloRésumé : (auteur) Atmospheric pollutant data retrieved through satellite sensors are continually used to assess changes in air quality in the lower atmosphere. During the COVID-19 pandemic, several studies started to use satellite measurements to evaluate changes in air quality in many different regions worldwide. However, although satellite data is continuously validated, it is known that its accuracy may vary between monitored areas, requiring regionalized quality assessments. Thus, this study aimed to evaluate whether satellites could measure changes in the air quality of the state of São Paulo, Brazil, during the COVID-19 outbreak; and to verify the relationship between satellite-based data [Tropospheric NO2 column density and Aerosol Optical Depth (AOD)] and ground-based concentrations [NO2 and particulate material (PM; coarse: PM10 and fine: PM2.5)]. For this purpose, tropospheric NO2 obtained from the TROPOMI sensor and AOD retrieved from MODIS sensor data by using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm were compared with concentrations obtained from 50 automatic ground monitoring stations. The results showed low correlations between PM and AOD. For PM10, most stations showed correlations lower than 0.2, which were not significant. The results for PM2.5 were similar, but some stations showed good correlations for specific periods (before or during the COVID-19 outbreak). Satellite-based Tropospheric NO2 proved to be a good predictor for NO2 concentrations at ground level. Considering all stations with NO2 measurements, correlations >0.6 were observed, reaching 0.8 for specific stations and periods. In general, it was observed that regions with a more industrialized profile had the best correlations, in contrast with rural areas. In addition, it was observed about 57% reductions in tropospheric NO2 throughout the state of São Paulo during the COVID-19 outbreak. Variations in air pollutants were linked to the region economic vocation, since there were reductions in industrialized areas (at least 50% of the industrialized areas showed >20% decrease in NO2) and increases in areas with farming and livestock characteristics (about 70% of those areas showed increase in NO2). Our results demonstrate that Tropospheric NO2 column densities can serve as good predictors of NO2 concentrations at ground level. For MAIAC-AOD, a weak relationship was observed, requiring the evaluation of other possible predictors to describe the relationship with PM. Thus, it is concluded that regionalized assessment of satellite data accuracy is essential for assertive estimates on a regional/local level. Good quality information retrieved at specific polluted areas does not assure a worldwide use of remote sensor data. Numéro de notice : A2023-170 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2023.113514 Date de publication en ligne : 21/02/2023 En ligne : https://doi.org/10.1016/j.rse.2023.113514 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102930
in Remote sensing of environment > vol 289 (May 2003) . - n° 113514[article]Flood vulnerability assessment of urban buildings based on integrating high-resolution remote sensing and street view images / Ziyao Xing in Sustainable Cities and Society, vol 92 (May 2023)
[article]
Titre : Flood vulnerability assessment of urban buildings based on integrating high-resolution remote sensing and street view images Type de document : Article/Communication Auteurs : Ziyao Xing, Auteur ; Shuai Yang, Auteur ; Xuli Zan, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104467 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] bâtiment
[Termes IGN] Chine
[Termes IGN] gestion des risques
[Termes IGN] image Streetview
[Termes IGN] inondation
[Termes IGN] milieu urbain
[Termes IGN] planification urbaine
[Termes IGN] Quickbird
[Termes IGN] segmentation sémantique
[Termes IGN] vulnérabilitéRésumé : (auteur) Urban flood risk management requires an extensive investigation of the vulnerability characteristics of buildings. Large-scale field surveys usually cost a lot of time and money, while satellite remote sensing and street view images can provide information on the tops and facades of buildings respectively. Thereupon, this paper develops a building vulnerability assessment framework using remote sensing and street view features. Specifically, a UNet-based semantic segmentation model, FSA-UNet (Fusion-Self-Attention-UNet) is proposed to integrate remote sensing and street view features and the vulnerability information contained in the images is fully exploited. And the building vulnerability index is generated to provide the spatial distribution characteristics of urban building vulnerability. The experiment shows that the mIoU of the proposed model can reach 82% for building vulnerability classification in Hefei, China, which is more accurate than the traditional semantic segmentation models. The results indicate that the integration of street view and remote sensing image features can improve the ability of building vulnerability assessment, and the model proposed in this study can better capture the correlation features of multi-angle images through the self-attention mechanism and combines hierarchy features and edge information to improve the classification effect. This study can support for disaster management and urban planning. Numéro de notice : A2023-152 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2023.104467 Date de publication en ligne : 23/02/2023 En ligne : https://doi.org/10.1016/j.scs.2023.104467 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102826
in Sustainable Cities and Society > vol 92 (May 2023) . - n° 104467[article]An improved MCDM combined with GIS for risk assessment of multi-hazards in Hong Kong / Hai-Min Lyu in Sustainable Cities and Society, vol 91 (April 2023)
[article]
Titre : An improved MCDM combined with GIS for risk assessment of multi-hazards in Hong Kong Type de document : Article/Communication Auteurs : Hai-Min Lyu, Auteur ; Zhen-Yu Yin, Auteur Année de publication : 2023 Article en page(s) : n° 104427 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse multicritère
[Termes IGN] Hong-Kong
[Termes IGN] processus de hiérarchisation analytique floue
[Termes IGN] risque naturel
[Termes IGN] système d'information géographique
[Termes IGN] zone à risqueRésumé : (auteur) Hong Kong frequently suffers from multi-hazards such as floods, muddy-water flows and landslides induced by rainstorms. This study presents an improved multi criteria decision making (MCDM) approach with integrating the interval numbers into fuzzy analytical hierarchy process (FAHP) to assess multi-hazard risks. To illustrate the efficiency of the improved MCDM method, the AHP, interval-FAHP and analytical network process (ANP) were incorporated into a geographical information system (GIS, abbreviated as AHP-GIS, interval-FAHP-GIS, and ANP-GIS) to assess the risks of multi-hazards (e.g., floods, muddy-water flows, and landslides) in Hong Kong. The assessed multi-risks indicated that the percentages of areas with a high risk of flood, muddy-water flow, and landslide were more than 15%, 17%, and 18%, respectively. The results demonstrated that MCDM methods considered multi-criteria contributions on multi hazards. Different assessment factors contributed different importance on different multi-hazard risks. The comparison indicates that interval-FAHP-GIS perform better than AHP-GIS and ANP-GIS in capturing high-risk areas. The interval-FAHP-GIS method adopts interval fuzzy numbers instead of crisp numbers in AHP-GIS to reflect the degree of importance of assessment factors, which increases the accuracy of the assessed multi-risks. Numéro de notice : A2023-150 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2023.104427 Date de publication en ligne : 27/01/2023 En ligne : https://doi.org/10.1016/j.scs.2023.104427 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102823
in Sustainable Cities and Society > vol 91 (April 2023) . - n° 104427[article]Impacts of forest management on stand and landscape-level microclimate heterogeneity of European beech forests / Joscha H. Menge in Landscape ecology, vol 38 n° 4 (April 2023)PermalinkKeeping thinning-derived deadwood logs on forest floor improves soil organic carbon, microbial biomass, and enzyme activity in a temperate spruce forest / Meisam Nazari in European Journal of Forest Research, vol 142 n° 2 (April 2023)PermalinkRegeneration in European beech forests after drought: the effects of microclimate, deadwood and browsing / Dominik Thom in European Journal of Forest Research, vol 142 n° 2 (April 2023)PermalinkSusceptibility of microseismic triggering to small sinusoidal stress perturbations at the laboratory scale / Martin Colledge in Journal of geophysical research : Solid Earth, vol 128 n° 4 (April 2023)PermalinkAutomatic detection of thin oil films on water surfaces in ultraviolet imagery / Ming Xie in Photogrammetric record, vol 38 n° 181 (March 2023)PermalinkForests attenuate temperature and air pollution discomfort in montane tourist areas / Elena Gottardini in Forests, vol 14 n° 3 (March 2023)PermalinkA GIS-based model for automated land suitability assessment for main crops in north-western desert of Egypt (case study: south of Al-Dabaa Corridor) / Adel Shalaby in Applied geomatics, vol 15 n° 1 (March 2023)PermalinkDes mesures au sol aux images satellite : quelles données pour étudier la pollution lumineuse ? / Christophe Plotard in XYZ, n° 174 (mars 2023)PermalinkPeut-on prédire les séismes ? / Laurent Polidori in Géomètre, n° 2211 (mars 2023)PermalinkResilience of Pyrenean forests after recurrent historical deforestations / Valenti Rull in Forests, vol 14 n° 3 (March 2023)PermalinkUne sylviculture dynamique des chênaies sessiliflores favorise la résilience des arbres après une forte sécheresse / Anna Schmitt in Revue forestière française, vol 74 n° 1 (2023)PermalinkThe 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)PermalinkA 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)PermalinkA spatial distribution: Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil / Jiawei Liu in Science of the total environment, vol 859 n° 1 (February 2023)PermalinkCan 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)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)PermalinkA GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level / Laxmi Gupta in Journal of maps, vol 18 n° 2 (February 2023)PermalinkLarge-scale burn severity mapping in multispectral imagery using deep semantic segmentation models / Xikun Hu in ISPRS Journal of photogrammetry and remote sensing, vol 196 (February 2023)PermalinkSpecies-specific deadwood density, its controlling factors and its role in the estimation of deadwood C stock of a Virgin European Beech-Silver Fir Mixed Forest in the Southern Carpathians / Ion Catalin Petritan in SSRN [preprint electronic journal], vol 2023 ([01/02/2023])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)PermalinkGIS-based planning of buffer zones for protection of boreal streams and their riparian forests / Heikki Mykrä in Forest ecology and management, vol 528 (January-15 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)PermalinkPerspectives: Critical zone perspectives for managing changing forests / Marissa Kopp in Forest ecology and management, vol 528 (January-15 2023)PermalinkBIM et enjeux climatiques, ch. City Information Modelling pour des aménagements sobres et durables : potentiel du CIM pour calculer l’intensité urbaine / Adeline Deprêtre (2023)PermalinkDecision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis / Haifa Tamiminia in Geocarto international, vol 38 n° inconnu ([01/01/2023])PermalinkEvaluation of GNSS-based volunteered geographic information for assessing visitor spatial distribution within protected areas: A case study of the Bavarian Forest National Park, Germany / Laura Horst in Applied Geography, vol 150 (January 2023)PermalinkLa forêt progresse mais la mortalité des arbres s’accroît / Anonyme in Géomètre, n° 2209 (janvier 2023)PermalinkA GIS-based study on the layout of the ecological monitoring system of the Grain for Green project in China / Ke Guo in Forests, vol 14 n° 1 (January 2023)PermalinkMachine learning remote sensing using the random forest classifier to detect the building damage caused by the Anak Krakatau Volcano tsunami / Riantini Virtriana in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)PermalinkManagement of birch spruce mixed stands with consideration of carbon stock in biomass and harvested wood products / Jānis Vuguls in Forests, vol 14 n° 1 (January 2023)PermalinkA new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing / Yali Zhang in GIScience and remote sensing, vol 60 n° 1 (2023)PermalinkPermalinkPrescribed fire after thinning increased resistance of sub-Mediterranean pine forests to drought events and wildfires / Lena Vilà-Vilardell in Forest ecology and management, vol 527 (January-1 2023)PermalinkRapid mapping of seismic intensity assessment using ground motion data calculated from early aftershocks selected by GIS spatial analysis / Huaiqun Zhao in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)PermalinkRemote sensing techniques for water management and climate change monitoring in drought areas: case studies in Egypt and Tunisia / Lifan Ji in European journal of remote sensing, vol 56 n° 1 (2023)PermalinkSensing urban soundscapes from street view imagery / Tianhong Zhao in Computers, Environment and Urban Systems, vol 99 (January 2023)PermalinkSimplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area / David Marín-García in Sustainable Cities and Society, vol 88 (January 2023)PermalinkSolid waste mapping based on very high resolution remote sensing imagery and a novel deep learning approach / Bowen Niu in Geocarto international, vol 38 n° 1 ([01/01/2023])PermalinkTree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data / Ying Quan in GIScience and remote sensing, vol 60 n° 1 (2023)PermalinkUrban infrastructure expansion and artificial light pollution degrade coastal ecosystems, increasing natural-to-urban structural connectivity / Moisés A. Aguilera in Landscape and Urban Planning, vol 229 (January 2023)PermalinkWavelet-like denoising of GNSS data through machine learning. Application to the time series of the Campi Flegrei volcanic area (Southern Italy) / Rolando Carbonari in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)PermalinkAutomatic detection of suspected sewage discharge from coastal outfalls based on Sentinel-2 imagery / Yuxin Wang in Science of the total environment, vol 853 (December 2022)PermalinkConsistency assessment of multi-date PlanetScope imagery for seagrass percent cover mapping in different seagrass meadows / Pramaditya Wicaksono in Geocarto international, vol 37 n° 27 ([20/12/2022])PermalinkEco-environment and coupling coordination and quantification of urbanization in Yangtze River delta considering spatial non-stationarity / Yaqiu Zhang in Geocarto international, vol 37 n° 27 ([20/12/2022])PermalinkGeospatial modelling of overlapping habitats for identification of tiger corridor networks in the Terai Arc landscape of India / Nupur Rautela in Geocarto international, vol 37 n° 27 ([20/12/2022])Permalink