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Using LiDAR and Random Forest to improve deer habitat models in a managed forest landscape / Colin S. Shanley in Forest ecology and management, vol 499 (November-1 2021)
[article]
Titre : Using LiDAR and Random Forest to improve deer habitat models in a managed forest landscape Type de document : Article/Communication Auteurs : Colin S. Shanley, Auteur ; Daniel R. Eacker, Auteur ; Connor P. Reynolds, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119580 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Alaska (Etats-Unis)
[Termes IGN] Cervidae
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] coefficient de corrélation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt
[Termes IGN] géomorphométrie
[Termes IGN] habitat animal
[Termes IGN] habitat forestier
[Termes IGN] semis de pointsRésumé : (auteur) Conservation strategies are hindered by a lack of accurate maps of important habitat for many wildlife species, but especially for species inhabiting managed forest landscapes. Prioritizing restoration efforts on Alaska’s Tongass National Forest from past extensive clearcut logging is extremely challenging given the difficulty in accurately mapping its remote, rugged temperate rainforest landscapes. We tested the application of airborne light detection and ranging (LiDAR) technology to build a winter habitat model for Sitka black-tailed deer (Odocoileus hemionus sitkensis), the primary herbivore in the coastal temperate rainforest. We analyzed the importance of geomorphometric and forest structure characteristics as predictors of deer winter habitat selection using Random Forest applied to a 3-year GPS relocation dataset collected from 40 adult female deer. The LiDAR-based habitat model had a predictive performance of 94% (Out-of-bag error = 6%), a 10% lower model error compared to air-photo interpreted polygons and modeled plot data. Random Forest also outperformed analogous resource selection function models based on a comprehensive k-fold cross-validation. Deer habitat selection patterns in the LiDAR-based model were nonlinear across geomorphometric and forest structure predictive variables, and generally supported existing studies of deer habitat selection. Besides improving deer conservation and management on the Tongass National Forest, our approach could greatly enhance the accuracy and resolution of habitat maps used for conservation and restoration planning across large managed forest landscapes. Numéro de notice : A2021-696 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2021.119580 Date de publication en ligne : 26/08/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119580 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98529
in Forest ecology and management > vol 499 (November-1 2021) . - n° 119580[article]A vector-based method for drainage network analysis based on LiDAR data / Fangzheng Lyu in Computers & geosciences, vol 156 (November 2021)
[article]
Titre : A vector-based method for drainage network analysis based on LiDAR data Type de document : Article/Communication Auteurs : Fangzheng Lyu, Auteur ; Xinlin Ma, Auteur ; et al., Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse vectorielle
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] interpolation spatiale
[Termes IGN] modèle numérique de surface
[Termes IGN] réseau hydrographique
[Termes IGN] semis de pointsRésumé : (auteur) Drainage network analysis is fundamental to understanding the characteristics of surface hydrology. Based on elevation data, drainage network analysis is often used to extract key hydrological features like drainage networks and streamlines. Limited by raster-based data models, conventional drainage network algorithms typically allow water to flow in 4 or 8 directions (surrounding grids) from a raster grid. To resolve this limitation, this paper describes a new vector-based method for drainage network analysis that allows water to flow in any direction around each location. The method is enabled by rapid advances in Light Detection and Ranging (LiDAR) remote sensing and high-performance computing. The drainage network analysis is conducted using a high-density point cloud instead of Digital Elevation Models (DEMs) at coarse resolutions. Our computational experiments show that the vector-based method can better capture water flows without limiting the number of directions due to imprecise DEMs. Our case study applies the method to Rowan County watershed, North Carolina in the US. After comparing the drainage networks and streamlines detected with corresponding reference data from US Geological Survey generated from the Geonet software, we find that the new method performs well in capturing the characteristics of water flows on landscape surfaces in order to form an accurate drainage network. Numéro de notice : A2021-755 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104892 Date de publication en ligne : 24/07/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98733
in Computers & geosciences > vol 156 (November 2021)[article]Age-dependence of stand biomass in managed boreal forests based on the Finnish National Forest Inventory data / Anna Repo in Forest ecology and management, vol 498 (October-15 2021)
[article]
Titre : Age-dependence of stand biomass in managed boreal forests based on the Finnish National Forest Inventory data Type de document : Article/Communication Auteurs : Anna Repo, Auteur ; Tuomas Rajala, Auteur ; Helena M. Henttonen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119507 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] âge du peuplement forestier
[Termes IGN] bilan du carbone
[Termes IGN] biomasse
[Termes IGN] changement climatique
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] gestion forestière
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modélisation de la forêt
[Termes IGN] puits de carbone
[Termes IGN] tourbière
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Information on carbon stocks and the rate of carbon accumulation is needed to harness the climate change mitigation potential of boreal forests. While previous studies have revealed general patterns and mechanisms for age-dependence of stand biomass, simple stand-level models that address the age-biomass relationship on average in managed boreal forests in different environmental conditions are largely missing. We developed models for the relationship between stand age and biomass by forest types on peatlands and mineral soils across climate zones in managed forests in Finland based on National Forest Inventory measurements from 1996 to 2018. In addition, we analyzed at which rate biomass accumulates when managed forest ages in different growth conditions. In northern Finland the maximum biomass change rate was one third, and the maximum biomass stock less than half of the corresponding values in sub-xeric heath forests on minerals soils in southern Finland. On drained peatlands the maximum biomass growth rate was approximately half, and on undrained peatlands one third of the maximum growth rate on mineral soils. On most fertile sites on mineral soils the maximum biomasses were three times larger than on the poorest sites. Correspondingly, the maximum biomass stock change rates were almost eight times faster on most fertile sites. In the example cases presented, the highest annual biomass change rates were achieved in young forests on average at the stand ages of 7–32 years, whereas the 95% of the maximum stock were reached on average in stands of 63–147 years. At the age of highest biomass growth rate stands contained 27–59% of the maximum biomass stocks. The developed models can be used in practical applications such as accounting of biogenic carbon in life-cycle assessments, mapping carbon, or creating simple predictions of biomass stock development in regions, or estimating the mitigation potential of afforestation and reforestation or estimating the magnitude of carbon offsets projects. Numéro de notice : A2021-659 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119507 Date de publication en ligne : 30/07/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119507 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98398
in Forest ecology and management > vol 498 (October-15 2021) . - n° 119507[article]4 807,81 m, le sommet décline / Anonyme in Géomètre, n° 2195 (octobre 2021)
[article]
Titre : 4 807,81 m, le sommet décline Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2021 Article en page(s) : pp 8-11 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Nivellement
[Termes IGN] calotte glaciaire
[Termes IGN] campagne d'observations
[Termes IGN] Mont-Blanc, massif du
[Termes IGN] positionnement par géodésie spatiale
[Termes IGN] précipitation
[Termes IGN] précision centimétrique
[Termes IGN] ventRésumé : (Auteur) Retour aux manuels scolaires... La onzième campagne de mesures du Mont-Blanc par les géomètres-experts confirme ses 4 807,81 m d'altitude. Avec cependant des variations permanentes. Numéro de notice : A2021-674 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98851
in Géomètre > n° 2195 (octobre 2021) . - pp 8-11[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 063-2021091 RAB Revue Centre de documentation En réserve L003 Disponible Anthropogenic degradation of dunes within a city: a disappearing feature of the cultural landscape of Toruń (Poland) / Pawel Molewski in Journal of maps, vol 17 n° 4 (October 2021)
[article]
Titre : Anthropogenic degradation of dunes within a city: a disappearing feature of the cultural landscape of Toruń (Poland) Type de document : Article/Communication Auteurs : Pawel Molewski, Auteur Année de publication : 2021 Article en page(s) : pp 162 - 169 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] anthropisation
[Termes IGN] carte ancienne
[Termes IGN] dune
[Termes IGN] modèle numérique de terrain
[Termes IGN] morphologie urbaine
[Termes IGN] paysage urbain
[Termes IGN] Pologne
[Termes IGN] système d'information historiqueRésumé : (auteur) The article presents changes in the topography of the Toruń area due to the degradation of dunes by human activity, and a reconstruction of their earlier location and morphology. The reconstruction was made on the basis of historical maps and plans from the end of the eighteenth century, as well as contemporary cartographic materials and digital terrain models (DTM). Analysis of the sources showed that the main period of anthropogenic degradation of dunes in the city was the second half of the twentieth century. The balance of changes in the share of dunes within city limits is estimated to be a decrease of about 26.5% over the study period, and by around 60.2% in the part that is presently urbanised. Numéro de notice : A2021-924 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2020.1736196 Date de publication en ligne : 10/03/2020 En ligne : https://doi.org/10.1080/17445647.2020.1736196 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99283
in Journal of maps > vol 17 n° 4 (October 2021) . - pp 162 - 169[article]Automatic detection of inland water bodies along altimetry tracks for estimating surface water storage variations in the Congo basin / Frédéric Frappart in Remote sensing, vol 13 n° 19 (October-1 2021)PermalinkComparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada / Bernadett Dobre in Transactions in GIS, vol 25 n° 5 (October 2021)PermalinkDisaster intensity-based selection of training samples for remote sensing building damage classification / Luis Moya in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)PermalinkEvaluation of methods for connecting InSAR to a terrestrial reference frame in the Latrobe Valley, Australia / P.J. Johnston in Journal of geodesy, vol 95 n° 10 (October 2021)PermalinkFlood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model / Gaurav Talukdar in Natural Hazards, vol 109 n° 1 (October 2021)PermalinkGeomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques / Peter G. Chirico in Journal of maps, vol 17 n° 4 (October 2021)PermalinkImproving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency / Jiaqi Tian in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)PermalinkA methodology for producing realistic hill-shading map based on shaded relief map, digital orthophotographic map fusion and IHS transformation / Hongyun Zeng in Annals of GIS, vol 27 n° 4 (October 2021)PermalinkOn the TEC bias of altimeter satellites / Francisco Azpilicueta in Journal of geodesy, vol 95 n° 10 (October 2021)PermalinkPredicting total electron content in ionosphere using vector autoregression model during geomagnetic storm / Sumitra Iyer in Journal of applied geodesy, vol 15 n° 4 (October 2021)PermalinkProduction potential, biodiversity and soil properties of forest reclamations: Opportunities or risk of introduced coniferous tree species under climate change? / Zdeněk Vacek in European Journal of Forest Research, vol 140 n° 5 (October 2021)PermalinkRecognition of crevasses with high-resolution digital elevation models: Application of geomorphometric modeling and texture analysis / Olga T. Ishalina in Transactions in GIS, vol 25 n° 5 (October 2021)PermalinkSeawater Debye model function at L-band and its impact on salinity retrieval from Aquarius satellite data / Yiwen Zhou in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)PermalinkSentinel-6A precise orbit determination using a combined GPS/Galileo receiver / Oliver Montenbruck in Journal of geodesy, vol 95 n° 10 (October 2021)PermalinkThe impact of air pollution on the growth of scots pine stands in poland on the basis of dendrochronological analyses / Longina Chojnacka-Ożga in Forests, vol 12 n° 10 (October 2021)PermalinkUrban geomorphology of a historical city straddling the Tanaro River (Alessandria, NW Italy) / Andrea Mandarino in Journal of maps, vol 17 n° 4 (October 2021)PermalinkVariation in downed deadwood density, biomass, and moisture during decomposition in a natural temperate forest / Tomas Přívětivý in Forests, vol 12 n° 10 (October 2021)PermalinkAerial and UAV images for photogrammetric analysis of Belvedere Glacier evolution in the period 1977–2019 / Carlo Lapige De Gaetani in Remote sensing, vol 13 n° 18 (September-2 2021)PermalinkAssessing the land expectation value of even-aged vs coppice-with-standards stand management and long-term effects of whole-tree harvesting on forest productivity and profitability / Abdelwahad Bessaad in Annals of Forest Science, vol 78 n° 3 (September 2021)PermalinkCombining photogrammetric and bathymetric data to build a 3D model of a canal tunnel / Emmanuel Moisan in Photogrammetric record, Vol 36 n° 175 (September 2021)PermalinkDevelopment of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt / Soha A. Mohamed in Natural Hazards, vol 108 n° 3 (September 2021)PermalinkEstimating regional soil moisture with synergistic use of AMSR2 and MODIS images / Majid Rahimzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)PermalinkGIS models for vulnerability of coastal erosion assessment in a tropical protected area / Luís Russo Vieira in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)PermalinkMise en place d'un dispositif expérimental numérique pour l'enseignement des risques naturels avec le jeu vidéo Minetest / Jérôme Staub in Cartes & Géomatique, n° 245-246 (septembre - décembre 2021)PermalinkMulti-actor perspectives on afforestation and reforestation strategies in Central Europe under climate change / Reneema Hazarika in Annals of Forest Science, vol 78 n° 3 (September 2021)PermalinkA new approach for the development of grid models calculating tropospheric key parameters over China / Ge Zhu in Remote sensing, vol 13 n° 17 (September-1 2021)PermalinkPicea abies and Pseudotsuga menziesii radial growth in relation to climate: case study from South Bohemia / Jan Mondek in Austrian journal of forest science, vol 2021 n° 3 (2021)PermalinkProtection naturelle contre la submersion, apport de l'intelligence artificielle / Antoine Mury in Cartes & Géomatique, n° 245-246 (septembre - décembre 2021)PermalinkRelevés de la grotte Cosquer : partie 1, la grotte, les premiers relevés, un monument et une histoire chaotiques / Bertrand Chazaly in XYZ, n° 168 (septembre 2021)PermalinkRelevés de la grotte Cosquer : partie 2, vers une dématérialisation de la grotte par digitalisation des processus et numérisations 3D, comment offrir à la communauté scientifique et au grand public l’accès au plus inaccessible des grands sanctuaires ornés d’Europe / Bertrand Chazaly in XYZ, n° 168 (septembre 2021)PermalinkSensitivity of change-point detection and trend estimates to GNSS IWV time series properties / Khanh Ninh Nguyen in Atmosphere, vol 12 n° 9 (September 2021)PermalinkSentinel-1 sensitivity to soil moisture at high incidence angle and the impact on retrieval over seasonal crops / Davide Palmisano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)PermalinkShining light on danger / Anonyme in GEO: Geoconnexion international, Vol 20 n° 5 (Autumn 2021)PermalinkStochastic super-resolution for downscaling time-evolving atmospheric fields with a generative adversarial network / Jussi Leinonen in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)PermalinkUsing electrical resistivity tomography to detect wetwood and estimate moisture content in silver fir (Abies alba Mill.) / Ludovic Martin in Annals of Forest Science, vol 78 n° 3 (September 2021)PermalinkQuantifying coherence between TDM90, SRTM90 and ASTER90 / Umut Gunes Sefercik in Geocarto international, vol 36 n° 15 ([15/08/2021])PermalinkUnsupervised band selection of hyperspectral data based on mutual information derived from weighted cluster entropy for snow classification / Divyesh Varade in Geocarto international, vol 36 n° 15 ([15/08/2021])PermalinkCalibration of the process-based model 3-PG for major central European tree species / David I. Forrester in European Journal of Forest Research, vol 140 n° 4 (August 2021)PermalinkDeep learning-based image de-raining using discrete Fourier transformation / Prasen Kumar Sharma in The Visual Computer, vol 37 n° 8 (August 2021)PermalinkEstablishing vertical separation models for vulnerable coastlines in developing territories / Cassandra Nanlal in Marine geodesy, vol 44 n° 5 (September 2021)PermalinkEstimation of code observation-specific biases (OSBs) for the modernized multi-frequency and multi-GNSS signals: an undifferenced and uncombined approach / Teng Liu in Journal of geodesy, vol 95 n° 8 (August 2021)PermalinkPermalinkA high-efficiency global model of optimization design of impervious surfaces for alleviating urban waterlogging in urban renewal / Huafei Yu in Transactions in GIS, Vol 25 n° 4 (August 2021)PermalinkInvestigating the application of artificial intelligence for earthquake prediction in Terengganu / Suzlyana Marhain in Natural Hazards, vol 108 n° 1 (August 2021)PermalinkMeasuring shallow-water bathymetric signal strength in lidar point attribute data using machine learning / Kim Lowell in International journal of geographical information science IJGIS, vol 35 n° 8 (August 2021)Permalink