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Regional-scale forest mapping over fragmented landscapes using global forest products and Landsat time series classification / Viktor Myroniuk in Remote sensing, vol 12 n° 1 (January 2020)
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Titre : Regional-scale forest mapping over fragmented landscapes using global forest products and Landsat time series classification Type de document : Article/Communication Auteurs : Viktor Myroniuk, Auteur ; Mykola Kutia, Auteur ; Arbi J. Sarkissian, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 24 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande infrarouge
[Termes IGN] carte forestière
[Termes IGN] changement climatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] Google Earth Engine
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Landsat
[Termes IGN] image proche infrarouge
[Termes IGN] image RVB
[Termes IGN] image satellite
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] plaine
[Termes IGN] série temporelle
[Termes IGN] surveillance forestière
[Termes IGN] UkraineRésumé : (auteur) Satellite imagery of 25–30 m spatial resolution has been recognized as an effective tool for monitoring the spatial and temporal dynamics of forest cover at different scales. However, the precise mapping of forest cover over fragmented landscapes is complicated and requires special consideration. We have evaluated the performance of four global forest products of 25–30 m spatial resolution within three flatland subregions of Ukraine that have different forest cover patterns. We have explored the relationship between tree cover extracted from the global forest change (GFC) and relative stocking density of forest stands and justified the use of a 40% tree cover threshold for mapping forest in flatland Ukraine. In contrast, the canopy cover threshold for the analogous product Landsat tree cover continuous fields (LTCCF) is found to be 25%. Analysis of the global forest products, including discrete forest masks Global PALSAR-2/PALSAR Forest/Non-Forest Map (JAXA FNF) and GlobeLand30, has revealed a major misclassification of forested areas under severe fragmentation patterns of landscapes. The study also examined the effectiveness of forest mapping over fragmented landscapes using dense time series of Landsat images. We collected 1548 scenes of Landsat 8 Operational Land Imager (OLI) for the period 2014–2016 and composited them into cloudless mosaics for the following four seasons: yearly, summer, autumn, and April–October. The classification of images was performed in Google Earth Engine (GEE) Application Programming Interface (API) using random forest (RF) classifier. As a result, 30 m spatial resolution forest mask for flatland of Ukraine was created. The user’s and producer’s accuracy were estimated to be 0.910 ± 0.015 and 0.880 ± 0.018, respectively. The total forest area for the flatland Ukraine is 9440.5 ± 239.4 thousand hectares, which is 3% higher than official data. In general, we conclude that the Landsat-derived forest mask performs well over fragmented landscapes if forest cover of the territory is higher than 10–15% Numéro de notice : A2020-225 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs12010187 Date de publication en ligne : 05/01/2020 En ligne : https://doi.org/10.3390/rs12010187 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94940
in Remote sensing > vol 12 n° 1 (January 2020) . - 24 p.[article]
Titre : Remote Sensing Applications for Agriculture and Crop Modelling Type de document : Monographie Auteurs : Piero Toscano, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2020 Importance : 310 p. ISBN/ISSN/EAN : ISBN 978-3-03928-227-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte d'utilisation du sol
[Termes IGN] changement climatique
[Termes IGN] changement d'occupation du sol
[Termes IGN] engrais chimique
[Termes IGN] image infrarouge
[Termes IGN] image Landsat-OLI
[Termes IGN] image multibande
[Termes IGN] image satellite
[Termes IGN] image Sentinel-MSI
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surface cultivéeRésumé : (éditeur) Crop models and remote sensing techniques have been combined and applied in agriculture and crop estimation on local and regional scales, or worldwide, based on the simultaneous development of crop models and remote sensing. The literature shows that many new remote sensing sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. At the same time, remote sensing has been used in a staggering number of applications for agriculture. This book sets the context for remote sensing and modelling for agricultural systems as a mean to minimize the environmental impact, while increasing production and productivity. The eighteen papers published in this Special Issue, although not representative of all the work carried out in the field of Remote Sensing for agriculture and crop modeling, provide insight into the diversity and the complexity of developments of RS applications in agriculture. Five thematic focuses have emerged from the published papers: yield estimation, land cover mapping, soil nutrient balance, time-specific management zone delineation and the use of UAV as agricultural aerial sprayers. All contributions exploited the use of remote sensing data from different platforms (UAV, Sentinel, Landsat, QuickBird, CBERS, MODIS, WorldView), their assimilation into crop models (DSSAT, AQUACROP, EPIC, DELPHI) or on the synergy of Remote Sensing and modeling, applied to cardamom, wheat, tomato, sorghum, rice, sugarcane and olive. The intended audience is researchers and postgraduate students, as well as those outside academia in policy and practice. Numéro de notice : 25747 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif En ligne : https://www.mdpi.com/books/pdfview/book/2023 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94932 Satellite image time series classification with pixel-set encoders and temporal self-attention / Vivien Sainte Fare Garnot (2020)
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Titre : Satellite image time series classification with pixel-set encoders and temporal self-attention Type de document : Article/Communication Auteurs : Vivien Sainte Fare Garnot , Auteur ; Loïc Landrieu
, Auteur ; Sébastien Giordano
, Auteur ; Nesrine Chehata
, Auteur
Editeur : Computer vision foundation CVF Année de publication : 2020 Projets : 1-Pas de projet / Conférence : CVPR 2020, IEEE Conference on Computer Vision and Pattern Recognition 14/06/2020 19/06/2020 en ligne Chine Open Access Proceedings Importance : pp 12325 - 12334 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] classification automatique
[Termes IGN] classification orientée objet
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] géocodage
[Termes IGN] image multibande
[Termes IGN] image satellite
[Termes IGN] parcelle agricole
[Termes IGN] politique agricole commune
[Termes IGN] série temporelle
[Termes IGN] utilisation du solRésumé : (auteur) Satellite image time series, bolstered by their growing availability, are at the forefront of an extensive effort towards automated Earth monitoring by international institutions. In particular, large-scale control of agricultural parcels is an issue of major political and economic importance. In this regard, hybrid convolutional-recurrent neural architectures have shown promising results for the automated classification of satellite image time series.We propose an alternative approach in which the convolutional layers are advantageously replaced with encoders operating on unordered sets of pixels to exploit the typically coarse resolution of publicly available satellite images. We also propose to extract temporal features using a bespoke neural architecture based on self-attention instead of recurrent networks. We demonstrate experimentally that our method not only outperforms previous state-of-the-art approaches in terms of precision, but also significantly decreases processing time and memory requirements. Lastly, we release a large openaccess annotated dataset as a benchmark for future work on satellite image time series. Numéro de notice : C2020-016 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers ArXiv/vers CVF Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/CVPR42600.2020.01234 Date de publication en ligne : 05/08/2020 En ligne : https://doi.org/10.1109/CVPR42600.2020.01234 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94225 Documents numériques
en open access
Satellite image time series classification - pdf préprintAdobe Acrobat PDFStreambank topography: an accuracy assessment of UAV-based and traditional 3D reconstructions / Benjamin U. Meinen in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)
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Titre : Streambank topography: an accuracy assessment of UAV-based and traditional 3D reconstructions Type de document : Article/Communication Auteurs : Benjamin U. Meinen, Auteur ; Derek T. Robinson, Auteur Année de publication : 2020 Article en page(s) : pp 1 - 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] carte topographique
[Termes IGN] cours d'eau
[Termes IGN] détection de changement
[Termes IGN] érosion
[Termes IGN] hétérogénéité spatiale
[Termes IGN] image à très haute résolution
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de surface
[Termes IGN] photogrammétrie aérienne
[Termes IGN] reconstruction 3D
[Termes IGN] rive
[Termes IGN] structure-from-motion
[Termes IGN] télémètre laser terrestreRésumé : (auteur) Highly accurate digital surface models are an essential part of change-over-time analyses for monitoring erosion processes. Streambank topography presents a unique challenge for surface mapping due to dense riparian vegetation, canopy cover, and rapidly changing elevation values. The spatial heterogeneity of stream corridors has made the calculation of streambank erosion across larger spatial extents difficult. Contemporary technologies such as terrestrial laser scanners (TLS) and unmanned aerial vehicles (UAVs) offer new approaches for streambank topography mapping at very high spatial resolutions across varying spatial extents. To evaluate the accuracy of different technologies for streambank topography mapping, we compared streambank surface models derived via a UAV using structure-from-motion and from traditional aerial photogrammetry (i.e. Southwestern Ontario Orthoimagery Project; SWOOP) to that of a TLS benchmark across seven streambank segments. Additional comparisons were made for 22 manually measured stream transects to that of a TLS benchmark. Compared to our benchmark, the UAV-derived streambank surface model was the most accurate with an average root-mean-square-error of 0.104 m. Errors in the UAV surface model were correlated with georeferencing error. The UAV had an average 52% success rate for reconstructing the streambank topography across all field campaigns and was able to map up to 2037 m of streambank in one hour. The streambank surface model derived from traditional aerial photogrammetry and manual transect measurements had average root-mean-square-errors of 0.238 m and 0.274 m respectively. Both aerially-derived surface models tended to over measure elevation values compared to the TLS, whereas manual transect measurements consistently under measured elevation. Numéro de notice : A2020-208 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2019.1597294 Date de publication en ligne : 26/03/2019 En ligne : https://doi.org/10.1080/01431161.2019.1597294 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94890
in International Journal of Remote Sensing IJRS > vol 41 n° 1 (01 - 08 janvier 2020) . - pp 1 - 18[article]
Titre : Sustainable land management in a European context : A co-design approach Type de document : Monographie Auteurs : Thomas Weith, Éditeur scientifique ; Tim Barkmann, Auteur ; Nadin Gaasch, Éditeur scientifique ; et al., Éditeur scientifique Editeur : Springer Nature Année de publication : 2020 Importance : 347 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-50841-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Ecologie
[Termes IGN] aménagement durable
[Termes IGN] aménagement rural
[Termes IGN] changement d'utilisation du sol
[Termes IGN] écosystème
[Termes IGN] Europe (géographie politique)
[Termes IGN] géosciences
[Termes IGN] gestion foncière
[Termes IGN] gestion forestière durable
[Termes IGN] paysage urbain
[Termes IGN] politique communautaire
[Termes IGN] recherche interdisciplinaire
[Termes IGN] sciences de l'environnement
[Termes IGN] surface cultivée
[Termes IGN] surveillance de l'urbanisationRésumé : (éditeur) This open access book presents and discusses current issues and innovative solution approaches for land management in a European context. Manifold sustainability issues are closely interconnected with land use practices. Throughout the world, we face increasing conflict over the use of land as well as competition for land. Drawing on experience in sustainable land management gained from seven years of the FONA programme (Research for Sustainable Development, conducted under the auspices of the German Federal Ministry of Education and Research), the book stresses and highlights co-design processes within the "co-creation of knowledge", involving collaboration in transdisciplinary research processes between academia and other stakeholders. The book begins with an overview of the current state of land use practices and the subsequent need to manage land resources more sustainably. New system solutions and governance approaches in sustainable land management are presented from a European perspective on land use. The volume also addresses how to use new modes of knowledge transfer between science and practice. New perspectives in sustainable land management and methods of combining knowledge and action are presented to a broad readership in land system sciences and environmental sciences, social sciences and geosciences. Note de contenu : 1- Land-use: State and drivers in Europe
2- Co-production of knowledge
3- Co-evolution: New system solutions and governance
4- OutlookNuméro de notice : 25987 Affiliation des auteurs : non IGN Thématique : FORET Nature : Recueil / ouvrage collectif DOI : 10.1007/978-3-030-50841-8 En ligne : https://doi.org/10.1007/978-3-030-50841-8 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96745 Test du potentiel de l’imagerie satellite haute résolution pour le suivi des mouvements gravitaires des falaises crayeuses de Seine-Maritime / Zoé Stroebele (2020)
PermalinkTrajectoires paysagères des cônes de déjection torrentiels des Alpes du nord (Maurienne et Tarentaise) / Thérèse Hugerot (2020)
PermalinkUso de QGIS en la teledetección, Vol. 4. QGIS y sus aplicaciones en agua y en gestion del riego / Nicolas Baghdadi (2020)
PermalinkVers une occupation du sol France entière par imagerie satellite à très haute résolution / Tristan Postadjian (2020)
PermalinkVery high resolution land cover mapping of urban areas at global scale with convolutional neural network / Thomas Tilak (2020)
PermalinkAn implicit radar convolutional burn index for burnt area mapping with Sentinel-1 C-band SAR data / Puzhao Zhang in ISPRS Journal of photogrammetry and remote sensing, Vol 158 (December 2019)
PermalinkCombining Sentinel-1 and Sentinel-2 Satellite image time series for land cover mapping via a multi-source deep learning architecture / Dino Lenco in ISPRS Journal of photogrammetry and remote sensing, Vol 158 (December 2019)
PermalinkDes empreintes cartographiques : restitution de données géohistoriques à partir de la Carte de France de Cassini, 1750-1789 / Bertrand Duménieu in Cartes & Géomatique, n° 241-242 (décembre 2019)
PermalinkFaut-il des relevés de flore exhaustifs pour caractériser et cartographier l'acidité et les propriétés nutritionnelles des sols ? / Paulina E. Pinto in Rendez-vous techniques, n° 61-62 (hiver - printemps 2019)
PermalinkAn approach for establishing correspondence between OpenStreetMap and reference datasets for land use and land cover mapping / Qi Zhou in Transactions in GIS, Vol 23 n° 6 (November 2019)
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