Descripteur
Termes IGN > 1- Outils - instruments et méthodes > document > document géographique > document cartographique
document cartographique |
Documents disponibles dans cette catégorie (3557)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Forest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data / Selina Ganz in Forests, vol 11 n° 12 (December 2020)
[article]
Titre : Forest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data Type de document : Article/Communication Auteurs : Selina Ganz, Auteur ; Petra Adler, Auteur ; Gerald Kändler, Auteur Année de publication : 2020 Article en page(s) : n° 1322 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] Bade-Wurtemberg (Allemagne)
[Termes IGN] carte forestière
[Termes IGN] image aérienne
[Termes IGN] image Sentinel-MSI
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle numérique de surface
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Research Highlights: This study developed the first remote sensing-based forest cover map of Baden-Württemberg, Germany, in a very high level of detail.
Background and Objectives: As available global or pan-European forest maps have a low level of detail and the forest definition is not considered, administrative data are often oversimplified or out of date. Consequently, there is an important need for spatio-temporally explicit forest maps. The main objective of the present study was to generate a forest cover map of Baden-Württemberg, taking the German forest definition into account. Furthermore, we compared the results to NFI data; incongruences were categorized and quantified. Materials and
Methods: We used a multisensory approach involving both aerial images and Sentinel-2 data. The applied methods are almost completely automated and therefore suitable for area-wide forest mapping.
Results: According to our results, approximately 37.12% of the state is covered by forest, which agrees very well with the results of the NFI report (37.26% ± 0.44%). We showed that the forest cover map could be derived by aerial images and Sentinel-2 data including various data acquisition conditions and settings. Comparisons between the forest cover map and 34,429 NFI plots resulted in a spatial agreement of 95.21% overall. We identified four reasons for incongruences: (a) edge effects at forest borders (2.08%), (b) different forest definitions since NFI does not specify minimum tree height (2.04%), (c) land cover does not match land use (0.66%) and (d) errors in the forest cover layer (0.01%).
Conclusions: The introduced approach is a valuable technique for mapping forest cover in a high level of detail. The developed forest cover map is frequently updated and thus can be used for monitoring purposes and for assisting a wide range of forest science, biodiversity or climate change-related studies.Numéro de notice : A2020-845 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f11121322 Date de publication en ligne : 12/12/2020 En ligne : https://doi.org/10.3390/f11121322 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98633
in Forests > vol 11 n° 12 (December 2020) . - n° 1322[article]Legal aspects of registration the time of cadastral data creation or modification / Joanna Reczyńska in Reports on geodesy and geoinformatics, vol 110 n° 1 (December 2020)
[article]
Titre : Legal aspects of registration the time of cadastral data creation or modification Type de document : Article/Communication Auteurs : Joanna Reczyńska, Auteur ; Pawel Hanus, Auteur Année de publication : 2020 Article en page(s) : pp 9 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger
[Termes IGN] base de données foncières
[Termes IGN] données cadastrales
[Termes IGN] droit foncier
[Termes IGN] enregistrement immobilier
[Termes IGN] INSPIRE
[Termes IGN] norme ISO
[Termes IGN] parcelle cadastrale
[Termes IGN] PologneRésumé : (auteur) In Poland, the cadastre is the basic register which is the source of information on cadastral entities and their property. Therefore, it should constitute a reliable source of information in the scope of establishing the range of law, its nature, but also the subject of its ownership. However, it is necessary to be able to not only check the current information on the legal status and its scope, but also review past statuses or determine the rights that will influence real estate in the future. The cadastre and related rights are changing very dynamically over time, and each state has a very strict reference to the previous state. Therefore, in order to manage real estate in the most effective way, it is necessary to record temporal attributes of cadastre objects. The main objective of this paper is to define the legal issues related to the possibility of registration at the time of creation or modification of object in the Polish cadastre. This paper includes analyses of both Polish legal regulations and European standards and norms. Moreover, the article presents the results of comparative analyses concerning the data model of cadastre and INSPIRE and Land Administration Domain Model (LADM) data models for the theme cadastral parcel in terms of temporal aspect. Numéro de notice : A2020-786 Affiliation des auteurs : non IGN Nature : Article DOI : 10.2478/rgg-2020-0007 Date de publication en ligne : 25/09/2020 En ligne : https://doi.org/10.2478/rgg-2020-0007 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96532
in Reports on geodesy and geoinformatics > vol 110 n° 1 (December 2020) . - pp 9 - 17[article]Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks / Felix Schiefer in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)
[article]
Titre : Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks Type de document : Article/Communication Auteurs : Felix Schiefer, Auteur ; Teja Kattenborn, Auteur ; Annett Frick, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 205-215 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond
[Termes IGN] arbre (flore)
[Termes IGN] carte forestière
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] espèce végétale
[Termes IGN] Forêt-Noire, massif de la
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier local
[Termes IGN] segmentation sémantique
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The use of unmanned aerial vehicles (UAVs) in vegetation remote sensing allows a time-flexible and cost-effective acquisition of very high-resolution imagery. Still, current methods for the mapping of forest tree species do not exploit the respective, rich spatial information. Here, we assessed the potential of convolutional neural networks (CNNs) and very high-resolution RGB imagery from UAVs for the mapping of tree species in temperate forests. We used multicopter UAVs to obtain very high-resolution ( Numéro de notice : A2020-706 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.015 Date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.015 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96236
in ISPRS Journal of photogrammetry and remote sensing > vol 170 (December 2020) . - pp 205-215[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2020121 RAB Revue Centre de documentation En réserve L003 Disponible Mapping of land cover with open-source software and ultra-high-resolution imagery acquired with unmanned aerial vehicles / Ned Horning in Remote sensing in ecology and conservation, vol 6 n° 4 (December 2020)
[article]
Titre : Mapping of land cover with open-source software and ultra-high-resolution imagery acquired with unmanned aerial vehicles Type de document : Article/Communication Auteurs : Ned Horning, Auteur ; Erika Fleishman, Auteur ; Peter J. Ersts, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 487 - 497 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image aérienne
[Termes IGN] image captée par drone
[Termes IGN] Orfeo Tool Box
[Termes IGN] orthoimage
[Termes IGN] R (langage)Résumé : (auteur) The use of unmanned aerial vehicles (UAVs) to map and monitor the environment has increased sharply in the last few years. Many individuals and organizations have purchased consumer-grade UAVs, and commonly acquire aerial photographs to map land cover. The resulting ultra-high-resolution (sub-decimeter-resolution) imagery has high information content, but automating the extraction of this information to create accurate, wall-to-wall land-cover maps is quite difficult. We introduce image-processing workflows that are based on open-source software and can be used to create land-cover maps from ultra-high-resolution aerial imagery. We compared four machine-learning workflows for classifying images. Two workflows were based on random forest algorithms. Of these, one used a pixel-by-pixel approach available in ilastik, and the other used image segments and was implemented with R and the Orfeo ToolBox. The other two workflows used fully connected neural networks and convolutional neural networks implemented with Nenetic. We applied the four workflows to aerial photographs acquired in the Great Basin (western USA) at flying heights of 10 m, 45 m and 90 m above ground level. Our focal cover type was cheatgrass (Bromus tectorum), a non-native invasive grass that changes regional fire dynamics. The most accurate workflow for classifying ultra-high-resolution imagery depends on diverse factors that are influenced by image resolution and land-cover characteristics, such as contrast, landscape patterns and the spectral texture of the land-cover types being classified. For our application, the ilastik workflow yielded the highest overall accuracy (0.82–0.89) as assessed by pixel-based accuracy. Numéro de notice : A2020-853 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1002/rse2.144 Date de publication en ligne : 13/01/2020 En ligne : https://doi.org/10.1002/rse2.144 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98682
in Remote sensing in ecology and conservation > vol 6 n° 4 (December 2020) . - pp 487 - 497[article]A la recherche des "bornes cadastrales" / Michel Ravelet in Géomètre, n° 2186 (décembre 2020)
[article]
Titre : A la recherche des "bornes cadastrales" Type de document : Article/Communication Auteurs : Michel Ravelet, Auteur Année de publication : 2020 Article en page(s) : pp 12 - 15 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Cadastre
[Termes IGN] BD Parcellaire
[Termes IGN] borne cadastrale
[Termes IGN] géolocalisation
[Termes IGN] plan cadastral
[Termes IGN] représentation parcellaire cadastrale uniqueRésumé : (Auteur) Un partenariat exemplaire se met en place entre l'IGN et l'OGE afin d'accroître la précision géographique du cadastre dans le cadre de la RPCU en s'appuyant sur la recherche des bornes anciennes. Numéro de notice : A2020-765 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96560
in Géomètre > n° 2186 (décembre 2020) . - pp 12 - 15[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 063-2020111 RAB Revue Centre de documentation En réserve L003 Disponible The effect of different sampling schemes on estimation precision of snow water equivalent (SWE) using geostatistics techniques in a semi-arid region of Iran / Hojatolah Ganjkhanlo in Geocarto international, vol 35 n° 16 ([01/12/2020])PermalinkAnalyse de la déforestation dans la périphérie ouest de la réserve de biosphère du Dja au Cameroun, à partir d'une série multi-annuelle d'images Landsat / Eric Wilson Tegno Nguekam in Revue Française de Photogrammétrie et de Télédétection, n° 222 (novembre 2020)PermalinkCartographie des cultures dans le périmètre du Loukkos (Maroc) : apport de la télédétection radar et optique / Siham Acharki in Revue Française de Photogrammétrie et de Télédétection, n° 222 (novembre 2020)PermalinkBretagne, la végétation cartographiée / Marielle Mayo in Géomètre, n° 2185 (novembre 2020)PermalinkCombination of Landsat 8 OLI and Sentinel-1 SAR time-series data for mapping paddy fields in parts of West and Central Java provinces, Indonesia / Sanjiwana Arjasakusuma in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkEnlightened mapping? Maps in the Europe of the enlightenment / Peter Michael Barber in Cartographic journal (the), Vol 57 n° 4 (November 2020)PermalinkLandslide susceptibility mapping using Naïve Bayes and Bayesian network models in Umyeonsan, Korea / Sunmin Lee in Geocarto international, vol 35 n° 15 ([01/11/2020])PermalinkMapping the fantastic great Southern continent, 1760–1777: A study in enlightenment geography / Vanessa Collingridge in Cartographic journal (the), Vol 57 n° 4 (November 2020)PermalinkMapping tree species deciduousness of tropical dry forests combining reflectance, spectral unmixing, and texture data from high-resolution imagery / Astrid Helena Huechacona-Ruiz in Forests, vol 11 n°11 (November 2020)PermalinkWorldwide detection of informal settlements via topological analysis of crowdsourced digital maps / Satej Soman in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkObject-based classification of mixed forest types in Mongolia / E. Nyamjargal in Geocarto international, vol 35 n° 14 ([15/10/2020])PermalinkTime series potential assessment for biophysical characterization of orchards and crops in a mixed scenario with Sentinel-1A SAR data / Hemant Sahu in Geocarto international, vol 35 n° 14 ([15/10/2020])PermalinkFollow the road: historical GIS for evaluating the development of routes in the Negev region during the twentieth century / Motti Zohar in Cartography and Geographic Information Science, vol 47 n° 6 (October 2020)PermalinkForest clear-cuts as habitat for farmland birds and butterflies / Dafne Ram in Forest ecology and management, vol 473 ([01/10/2020])PermalinkGEBCO Gridded Bathymetric Datasets for mapping Japan Trench geomorphology by means of GMT scripting toolset / Polina Lemenkova in Geodesy and cartography, vol 46 n° 3 (October 2020)PermalinkNew measures for analysis and comparison of shape distortion in world map projections / Melih Basaraner in Cartography and Geographic Information Science, vol 47 n° 6 (October 2020)PermalinkReflecting on the purpose of mapwork in primary schooling / Simon Catling in International journal of cartography, vol 6 n° 3 (October 2020)PermalinkRoad network simplification for location-based services / Abdeltawab M. Hendawi in Geoinformatica, vol 24 n° 4 (October 2020)PermalinkSchool cartography in Brazil and its inclusive perspective / Imre Josef Demhardt in International journal of cartography, vol 6 n° 3 (October 2020)PermalinkUncertainty of forested wetland maps derived from aerial photography / Stephen P. Prisley in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)Permalink