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Termes IGN > géomatique > base de données localisées > couche thématique > occupation du sol
occupation du sol
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Espace, organisation de l' Utilisation du sol Politique foncière Sol, Occupation du Sols -- Utilisation Sols -- Utilisation Terrains -- Utilisation Terrains, Utilisation des Utilisation du sol Espace (économie politique) >> Aménagement du territoire Paysage -- Évaluation Syndrome NIMBY >>Terme(s) spécifique(s) : Améliorations foncières Cadastres Décharges contrôlées Immobilier Photographie aérienne en utilisation du sol Politique forestière Promotion immobilière Propriété foncière Propriété immobilière -- Acquisition par l'Administration Terres publiques Zones d'aménagement différé Equiv. LCSH : Land use Domaine(s) : 330 |
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Fungal perspective of pine and oak colonization in Mediterranean degraded ecosystems / Irene Adamo in Forests, vol 13 n° 1 (January 2022)
[article]
Titre : Fungal perspective of pine and oak colonization in Mediterranean degraded ecosystems Type de document : Article/Communication Auteurs : Irene Adamo, Auteur ; Svetlana Dashevskaya, Auteur ; Josu G. Alday, Auteur Année de publication : 2022 Article en page(s) : n° 88 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse
[Termes IGN] champignon mycorhizien
[Termes IGN] couvert végétal
[Termes IGN] écosystème forestier
[Termes IGN] forêt méditerranéenne
[Termes IGN] Fungi
[Termes IGN] humus
[Termes IGN] litière
[Termes IGN] Pinus sylvestris
[Termes IGN] Quercus ilex
[Termes IGN] Quercus pedunculata
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Forest restoration has become one of the most important challenges for restoration ecology in the recent years. In this regard, soil fungi are fundamental drivers of forest ecosystem processes, with significant implications for plant growth and survival. However, the post-disturbance recovery of belowground communities has been rarely assessed, especially in highly degraded systems such as mines. Our aim was to compare forests and mined systems for biomass and structure of fungal communities in soil during early stages of tree establishment after disturbance. We performed ergosterol analysis and PacBio and Illumina sequencing of internal transcribed spacer 2 amplicons across soil layers in P. sylvestris, Q. robur and Q. ilex (holm oak) forests and naturally revegetated mined sites. In pine forests, total fungal biomass was significantly higher in litter and humus compared to mineral layers, with dominance of the mycorrhizal genera Tomentella, Inocybe and Tricholoma. Conversely, in oak forests the most abundant mycorrhizal genera were Tomentella, Cortinarius and Sebacina, but the biomass of saprotrophic fungi was greater in the litter layer compared to mycorrhizal fungi, with the genus Preussia being the most abundant. In the revegetated mined sites, ectomycorrhizal fungi dominated in the humus and mineral layers, with the mycorrhizal genus Oidiodendron being dominant. In contrast, in holm oak forests saprotrophic fungi dominated both soil humus and mineral layers, with the genera of Alternaria, Bovista and Mycena dominating the soil humus forest layer, while the genus Cadophora dominated the mineral layer. The habitat-specific differences in soil fungal community composition and putative functions suggest that an understanding of soil–plant–microbial interactions for different tree species and use of specific soil/litter inoculum upon planting/seeding might help to increase the effectiveness of tree restoration strategies in Mediterranean degraded sites. Numéro de notice : A2022-081 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.3390/f13010088 Date de publication en ligne : 08/01/2022 En ligne : https://doi.org/10.3390/f13010088 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99474
in Forests > vol 13 n° 1 (January 2022) . - n° 88[article]Improving LSMA for impervious surface estimation in an urban area / Jin Wang in European journal of remote sensing, vol 55 n° 1 (2022)
[article]
Titre : Improving LSMA for impervious surface estimation in an urban area Type de document : Article/Communication Auteurs : Jin Wang, Auteur ; Yaolong Zhao, Auteur ; Yingchun Fu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 37 - 51 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] classification et arbre de régression
[Termes IGN] image Landsat-OLI
[Termes IGN] régression
[Termes IGN] signature spectrale
[Termes IGN] surface imperméable
[Termes IGN] Yunnan (Chine)
[Termes IGN] zone urbaineRésumé : (auteur) Linear spectral mixture analysis (LSMA) and regression analysis are the two most conventionally used methods to estimate impervious surfaces at the subpixel scale in an urban area. However, LSMA lacks the sensitivity to pixel brightness, which leads to inter variability of endmembers and affects the ability to distinguish features with a similar spectral signature. This research aims to develop LSMA aided by a regression analysis model to estimate impervious surfaces with higher accuracy. A spectral angle mapping (SAM) based regression analysis model is introduced to reduce errors. Based on high-resolution images and field survey data, the SAM-based regression analysis can estimate non-impervious surface and high-impervious surface densities with high accuracy, while less accurate in impervious surfaces with low/medium density. In contrast, LSMA is able to estimate low/medium-density impervious surfaces with higher accuracy. We propose an improved approach by integrating the two methods, regression analysis aided LSMA, for impervious surface estimation. The proposed method increases the overall accuracy of the impervious surface estimation to 85.24%, which is significantly greater than that of the conventional methods. Numéro de notice : A2022-098 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1080/22797254.2021.2018666 Date de publication en ligne : 05/01/2022 En ligne : https://doi.org/10.1080/22797254.2021.2018666 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99548
in European journal of remote sensing > vol 55 n° 1 (2022) . - pp 37 - 51[article]Italian National Forest Inventory: Methods and results of the third survey / Patrizia Gasparini (2022)
Titre : Italian National Forest Inventory: Methods and results of the third survey Titre original : Inventario Nazionale delle Foreste e dei serbatoi forestali di carbonio : Metodi e risultati della terza indagine Type de document : Monographie Auteurs : Patrizia Gasparini, Auteur ; Lucio Di Cosmo, Auteur ; Antonio Floris, Auteur ; Davide De Laurentis, Auteur Editeur : Springer Nature Année de publication : 2022 Importance : 576 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-98678-0 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biodiversité végétale
[Termes IGN] changement climatique
[Termes IGN] défoliation
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] exploitation forestière
[Termes IGN] gestion forestière durable
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Italie
[Termes IGN] occupation du sol
[Termes IGN] placette d'échantillonnage
[Termes IGN] politique forestière
[Termes IGN] protection des forêts
[Termes IGN] puits de carbone
[Termes IGN] régénération (sylviculture)
[Termes IGN] santé des forêts
[Termes IGN] site Natura 2000
[Termes IGN] statistiques
[Termes IGN] utilisation du sol
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) This open access book deals with the methods and the results of the third Italian national forest inventory (INFC2015). Arma dei Carabinieri is entrusted with the realisation of the National Forest Inventory and with the decisions about the aims of the survey and data treatment. National forest inventories produce statistically based information on forests over country areas. Such information is used either at subnational or at supranational level in a great number of spheres and processes, included possibility to depict the status of the world forests. Italy conducted its first forest inventory in 1985 and in 2001 a permanent national forest inventory was launched to have periodically updated statistics. Due to the growing concern about the environment and especially the climate change, estimating forests carbon pools was a stated main objective and it was accordingly named Italian National Inventory of Forest and Forest Carbon Pools (INFC). The book begins with a description of the general organisation, the definitions, the methods and the estimation procedures. It proceeds showing the main estimates produced by INFC2015, in tables that are given in the book chapters. The estimates are presented through texts that introduce the subject matter, explain the way the related variables were surveyed and comment on the main outcomes with the help of graphics. The estimates presented include forest area, management and production, biodiversity and protection, forest health, protective and socio-economics functions. Role of forest in the carbon balance was analysed in a specific Chapter, as this is important for its role in the climate change mitigation. The book ends providing an understanding of the current dynamics of Italian forests by comparing the estimates obtained from INFC2005 and INFC2015, the last two national surveys. Note de contenu : 1- The Italian Forest Inventory in brief
2- Definitions and sampling design
3- Land use and land cover photointerpretation
4- Field assessment-survey protocols and data collection
5- Procedures for the estimation of forest inventory quantities
6- Plot level estimation procedures and models
7- Area and characteristics of Italian forests
8- Forest management and productive function
9- Biodiversity and protected wooded lands
10- Forest health
11- Protective function and primary designated management objective
12- Forest carbon stock
13- Changes of Italian forests over time captured by the National Forest InventoriesNuméro de notice : 24084 Affiliation des auteurs : non IGN Thématique : FORET Nature : Monographie DOI : 10.1007/978-3-030-98678-0 En ligne : https://doi.org/10.1007/978-3-030-98678-0 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102410 The use of volunteer geographic information for producing and maintaining authoritative land use and land cover data / Ana-Maria Olteanu-Raimond (2022)
Titre : The use of volunteer geographic information for producing and maintaining authoritative land use and land cover data : EuroSDR and LandSense Workshop, November 24th - 25th 2020, Online Conference Type de document : Actes de congrès Auteurs : Ana-Maria Olteanu-Raimond , Auteur ; Joep Crompvoets, Auteur ; Inian Moorthy, Auteur ; Clément Mallet , Auteur ; Bénédicte Bucher , Auteur Editeur : Dublin : European Spatial Data Research EuroSDR Année de publication : 2022 Collection : EuroSDR Workshop report Projets : Landsense / Raimond, Ana-Maria Conférence : VGI4LULC 2020, The use of volunteer geographic information for producing and maintaining authoritative land use and land cover data 24/11/2020 25/11/2020 online OA Proceedings Importance : 40 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] approche participative
[Termes IGN] cartographie collaborative
[Termes IGN] collecte de données
[Termes IGN] Corine Land Cover
[Termes IGN] détection de changement
[Termes IGN] données localisées des bénévoles
[Termes IGN] intégration de données
[Termes IGN] occupation du sol
[Termes IGN] OpenStreetMap
[Termes IGN] science citoyenne
[Termes IGN] utilisation du solRésumé : (éditeur) The report refers to the workshop that was organized on behalf of EuroSDR and the LandSense project (24-25 November 2020). LandSense aims to build a citizen observatory for Land Use and Land Cover (LULC) monitoring by proposing innovate technologies for data collection, change detection, data quality assessment and offering tools and systems to empower different communities (e.g., private companies, Non Governmental Organisation, National Mapping Agencies, research, public authorities) to monitor and report on LULC. The workshop was co-organized by the LASTIG laboratory of the University Gustave Eiffel and IGN-ENSG, the French National Mapping agency (Ana-Maria Olteanu-Raimond, Clément Mallet, Bénédicte Bucher), the Katholieke Universiteit Leuven (Joep Crompvoets), the International Institute for Applied Systems Analysis (Inian Moorthy) and EuroSDR. Note de contenu : INTRODUCTION GENERALE
1. Introduction
1.1 Land Use and Land Cover data: specificities and challenges
1.2 VGI and citizen science for LULC monitoring
2. Session 1: Use of VGI for LULC data production
2.1 National Land Cover and Land Use Information System of Spain (SIOSE)- Coordination,
production, maintenance and VGI
2.2 A fusion data approach for integrating VGI to update and enrich authoritative LULC data
2.3 OpenStreetMap for Earth Observation (OSM4EO) land use application and benchmark
2.4 Using OpenStreetMap as a data source for training classifiers to generate LULC maps
3. Session 2: Data collection and validation
3.1 A mapping prototype for land use mapping by land users
3.2 A mobile application for collecting snow data in support to satellite remote sensing
3.3 Global land cover monitoring, validation and participation: experiences from several case studies
4. Session 3: Sustainability
4.1 Crowdsourcing reference data collection for land cover and land use mapping: Findings from Picture Pile and FotoquestGo
4.2 Land Cover Monitoring System with Sentinel-Hub and Python Machine Learning Library eo-learn. Is it possible to build a fast and cost-effective LCMS?
4.3 Regular monitoring of landscape changes with Copernicus data- The German land cover change detection service
4.4 Authentication as a Service - A LandSense contribution to improve the FAIR principle in Citizen Science
5. ConclusionNuméro de notice : 28680 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Actes nature-HAL : DirectOuvrColl/Actes DOI : sans En ligne : http://www.eurosdr.net/sites/default/files/uploaded_files/eurosdr_vgi4lulc.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99973 A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping / Khalil Valizadeh Kamran in Applied geomatics, vol 13 n° 4 (December 2021)
[article]
Titre : A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping Type de document : Article/Communication Auteurs : Khalil Valizadeh Kamran, Auteur ; Bakhtiar Feizizadeh, Auteur ; Behnam Khorrami, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 837 - 851 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de sensibilité
[Termes IGN] apprentissage automatique
[Termes IGN] cartographie des risques
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] effondrement de terrain
[Termes IGN] fonction de base radiale
[Termes IGN] Iran
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] occupation du sol
[Termes IGN] pente
[Termes IGN] risque naturel
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (auteur) Landslides are among the most destructive natural hazards with severe socio-economic ramifications all around the world. Understanding the critical combination of geoenvironmental factors involved in the occurrence of landslides can mitigate the adverse impacts ascribed to them. Among the several scenarios for studying and investigating this phenomenon, landslide susceptibility mapping (LSM) is the most prominent method. Applying the machine learning (ML) algorithms integrated with the geographic information systems (GIS) has become a trending means for accurate and rapid landslide mapping practices in the scientific community. Support vector machine (SVM) has been the most commonly applied ML algorithm for LSM in recent years. The current study aims to implement different SVM kernel functions including polynomial kernel function (PKF) (degree 1 to 5), radial basis function (RBF), sigmoid, and linear kernels, for a GIS-based LSM over the Tabriz Basin (TB). To this end, a total number of 9 conditioning parameters being involved in the occurrence of the landslide events were determined and utilized. The LSM maps of the TB were generated based on the different SVM kernels and were statistically validated according to the landslide inventory. The findings revealed that the polynomial-degree-2 (PKF-2) model (AUC = 0.9688) outperforms the rest of the utilized kernels. According to the SLM map generated through PKF-2, the northernmost parts of the TB are extremely susceptible to slope failures than the rest; therefore, the developmental policies over these parts have to be taken into account with privileged priority to hinder any humanitarian as well as environmental catastrophes. Numéro de notice : A2021-858 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s12518-021-00393-0 Date de publication en ligne : 28/08/2021 En ligne : https://doi.org/10.1007/s12518-021-00393-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99066
in Applied geomatics > vol 13 n° 4 (December 2021) . - pp 837 - 851[article]Particle swarm optimization based water index (PSOWI) for mapping the water extents from satellite images / Mohammad Hossein Gamshadzaei in Geocarto international, vol 36 n° 20 ([01/12/2021])PermalinkExploring fuzzy local spatial information algorithms for remote sensing image classification / Anjali Madhu in Remote sensing, vol 13 n° 20 (October-2 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)PermalinkA 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)PermalinkImproving urban land cover classification with combined use of Sentinel-2 and Sentinel-1 imagery / Bin Hu in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)PermalinkPattern-based identification and mapping of landscape types using multi-thematic data / Jakub Nowosad in International journal of geographical information science IJGIS, vol 35 n° 8 (August 2021)PermalinkA hierarchical deep learning framework for the consistent classification of land use objects in geospatial databases / Chun Yang in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)PermalinkReview of spectral indices for urban remote sensing / Akib Javed in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)PermalinkSpatio-temporal-spectral observation model for urban remote sensing / Zhenfeng Shao in Geo-spatial Information Science, vol 24 n° 3 (July 2021)PermalinkDetection of suitable sites for rainwater harvesting planning in an arid region using geographic information system / Hadeel Qays Hashim in Applied geomatics, vol 13 n° 2 (June 2021)Permalink