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Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest / Laura Alonso-Martinez in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)
[article]
Titre : Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest Type de document : Article/Communication Auteurs : Laura Alonso-Martinez, Auteur ; J. Picos, Auteur ; Julia Armesto, Auteur Année de publication : 2021 Article en page(s) : pp 203 - 210 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] couvert forestier
[Termes IGN] Espagne
[Termes IGN] Eucalyptus (genre)
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Pinus pinaster
[Termes IGN] Pinus radiata
[Termes IGN] Pinus sylvestris
[Termes IGN] ressources forestières
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Advances in remote sensing technologies are generating new perspectives concerning the role of and methods used for National Forestry Inventories (NFIs). The increase in computation capabilities over the last several decades and the development of new statistical techniques have allowed for the automation of forest resource map generation through image analysis techniques and machine learning algorithms. The availability of large-scale data and the high temporal resolution that satellite platforms provide mean that it is possible to obtain updated information about forest resources at the stand level, thus increasing the quality of the spatial information. However, photointerpretation of satellite and aerial images is still the most common way that remote sensing information is used for NFIs or forest management purposes. This study describes a methodology that automatically maps the main forest covers in Galicia (Eucalyptus spp., conifers and broadleaves) using Worldview-2 and the random forest classifier. Furthermore, the method also evaluates the separate mapping of the three most abundant Pinus tree species in Galicia (Pinus pinaster, Pinus radiata and Pinus sylvestris). According to the results, Worldview-2 multispectral images allow for the efficient differentiation between the main forest classes that are present in Galicia with a very high degree of accuracy (91%) and ample spatial detail. Pinus species can also be efficiently differentiated (83%). Numéro de notice : A2021-493 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-3-2021-203-2021 Date de publication en ligne : 17/06/2021 En ligne : http://dx.doi.org/10.5194/isprs-annals-V-3-2021-203-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97958
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2021 (July 2021) . - pp 203 - 210[article]Coral habitat mapping: a comparison between maximum likelihood, Bayesian and Dempster–Shafer classifiers / Mohammad Shawkat Hossain in Geocarto international, vol 36 n° 11 ([15/06/2021])
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Titre : Coral habitat mapping: a comparison between maximum likelihood, Bayesian and Dempster–Shafer classifiers Type de document : Article/Communication Auteurs : Mohammad Shawkat Hossain, Auteur ; Aidy M. Muslim, Auteur ; Muhammad Izuan Nadzri, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1217 - 1235 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte thématique
[Termes IGN] classification bayesienne
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification pixellaire
[Termes IGN] fond marin
[Termes IGN] Google Earth
[Termes IGN] habitat d'espèce
[Termes IGN] image Quickbird
[Termes IGN] Malaisie
[Termes IGN] précision infrapixellaire
[Termes IGN] récif corallienRésumé : (auteur) This study deals with the mixed-pixel problem of detecting benthic habitat class membership and evaluates two soft classifiers for coral habitat mapping on Lang Tengah island (Malaysia). A comparison was made between the Bayesian and Dempster–Shafer (D–S) with a traditional maximum likelihood (ML). The heterogeneous pattern of reef environment, established by field observation, four classes of coral habitats containing various combinations of live coral, dead coral with algae, rubble coral and sand. Posterior probability and belief maps, generated by Bayesian and D–S, respectively, were evaluated by visual inspection and final coral habitat distribution maps were validated via accuracy assessment estimates. The accuracy validation tests agreed with the visual inspection of the probability, uncertainty and coral distribution maps. The Bayesian algorithm performed better, with a 34.7–68.5% improvement in accuracy compared to D–S and ML, respectively. Probability maps demonstrate the advantages of the soft classifier over the hard classifier for coral mapping. Numéro de notice : A2021-435 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1637466 Date de publication en ligne : 10/07/2019 En ligne : https://doi.org/10.1080/10106049.2019.1637466 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97803
in Geocarto international > vol 36 n° 11 [15/06/2021] . - pp 1217 - 1235[article]Groundwater vulnerability assessment of the chalk aquifer in the northern part of France / Lahcen Zouhri in Geocarto international, vol 36 n° 11 ([15/06/2021])
[article]
Titre : Groundwater vulnerability assessment of the chalk aquifer in the northern part of France Type de document : Article/Communication Auteurs : Lahcen Zouhri, Auteur ; Romain Armand, Auteur Année de publication : 2021 Article en page(s) : pp 1193 - 1216 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de sensibilité
[Termes IGN] aquifère
[Termes IGN] ArcGIS
[Termes IGN] carte hydrogéologique
[Termes IGN] craie
[Termes IGN] eau souterraine
[Termes IGN] Hauts-de-France (région 2016)
[Termes IGN] Oise (60)
[Termes IGN] utilisation du sol
[Termes IGN] vulnérabilitéRésumé : (auteur) This study explores the groundwater vulnerability of the chalk aquifer (northern part of France) using a well-known overlay and index DRASTIC method for intrinsic scenario and using land use (LU) parameter as additional factor. Different sources have allowed to compile data necessary to map the vulnerability of the aquifer under study, which used to generate the seven parameters of DRASTIC, namely: groundwater Depth, groundwater Recharge, lithology, Soil media, Topography, Impact of the vadose zone and hydraulic Conductivity. Applying the model in ArcGIS 10.2 platform leads to identify three classes of vulnerability: low, medium and high vulnerability. The highest DRASTIC indexes appear in areas where the groundwater depth is low and in more permeable unsaturated zones. The LU has a little effect on the distribution of vulnerability classes: this distribution is marked by the low vulnerability 44% against 6.5 of high vulnerability. Numéro de notice : A2021-434 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1637465 Date de publication en ligne : 10/07/2019 En ligne : https://doi.org/10.1080/10106049.2019.1637465 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97801
in Geocarto international > vol 36 n° 11 [15/06/2021] . - pp 1193 - 1216[article]Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine / Tongxi Hu in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)
[article]
Titre : Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine Type de document : Article/Communication Auteurs : Tongxi Hu, Auteur ; Elizabeth Myers Toman, Auteur ; Gang Chen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 250 - 261 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bassin hydrographique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification bayesienne
[Termes IGN] détection de changement
[Termes IGN] estimation bayesienne
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat
[Termes IGN] méthode de Monte-Carlo par chaînes de Markov
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Ohio (Etats-Unis)
[Termes IGN] précision infrapixellaire
[Termes IGN] série temporelleRésumé : (auteur) Large fractions of human-altered lands are working landscapes where people and nature interact to balance social, economic, and ecological needs. Achieving these sustainability goals requires tracking human footprints and landscape disturbance at fine scales over time—an effort facilitated by remote sensing but still under development. Here, we report a satellite time-series analysis approach to detecting fine-scale human disturbances in an Ohio watershed dominated by forests and pastures but with diverse small-scale industrial activities such as hydraulic fracturing (HF) and surface mining. We leveraged Google Earth Engine to stack decades of Landsat images and explored the effectiveness of a fuzzy change detection algorithm called the Bayesian Estimator of Abrupt change, Seasonality, and Trend (BEAST) to capture fine-scale disturbances. BEAST is an ensemble method, capable of estimating changepoints probabilistically and identifying sub-pixel disturbances. We found the algorithm can successfully capture the patterns and timings of small-scale disturbances, such as grazing, agriculture management, coal mining, HF, and right-of-ways for gas and power lines, many of which were not captured in the annual land cover maps from Cropland Data Layers—one of the most widely used classification-based land dynamics products in the US. For example, BEAST could detect the initial HF wellpad construction within 60 days of the registered drilling dates on 88.2% of the sites. The wellpad footprints were small, disturbing only 0.24% of the watershed in area, which was dwarfed by other activities (e.g., right-of-ways of utility transmission lines). Together, these known activities have disturbed 9.7% of the watershed from the year 2000 to 2017 with evergeen forests being the most affected land cover. This study provides empirical evidence on the effectiveness and reliability of BEAST for changepoint detection as well as its capability to detect disturbances from satellite images at sub-pixel levels and also documents the value of Google Earth Engine and satellite time-series imaging for monitoring human activities in complex working landscapes. Numéro de notice : A2021-415 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.04.008 Date de publication en ligne : 17/05/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.04.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97746
in ISPRS Journal of photogrammetry and remote sensing > vol 176 (June 2021) . - pp 250 - 261[article]Provisioning forest and conservation science with high-resolution maps of potential distribution of major European tree species under climate change / Debojyoti Chakraborty in Annals of Forest Science, vol 78 n° 2 (June 2021)
[article]
Titre : Provisioning forest and conservation science with high-resolution maps of potential distribution of major European tree species under climate change Type de document : Article/Communication Auteurs : Debojyoti Chakraborty, Auteur ; Norbert Móricz, Auteur ; Ervin Rasztovits, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : Article 26 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de groupement
[Termes IGN] carte forestière
[Termes IGN] changement climatique
[Termes IGN] conservation des ressources forestières
[Termes IGN] espèce végétale
[Termes IGN] Europe (géographie politique)
[Termes IGN] Fagus sylvatica
[Termes IGN] Larix decidua
[Termes IGN] outil d'aide à la décision
[Termes IGN] peuplement forestier
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus sessiliflora
[Termes IGN] vulnérabilité
[Vedettes matières IGN] Ecologie forestièreRésumé : (Auteur) We developed a dataset of the potential distribution of seven ecologically and economically important tree species of Europe in terms of their climatic suitability with an ensemble approach while accounting for uncertainty due to model algorithms. The dataset was documented following the ODMAP protocol to ensure reproducibility. Our maps are input data in a decision support tool “SusSelect” which predicts the vulnerability of forest trees in climate change and recommends adapted planting material. Numéro de notice : A2021-329 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01029-4 Date de publication en ligne : 22/03/2021 En ligne : https://doi.org/10.1007/s13595-021-01029-4 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97490
in Annals of Forest Science > vol 78 n° 2 (June 2021) . - Article 26[article]Resolution enhancement for large-scale land cover mapping via weakly supervised deep learning / Qiutong Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 6 (June 2021)PermalinkWalking through the forests of the future: using data-driven virtual reality to visualize forests under climate change / Jiawei Huang in International journal of geographical information science IJGIS, vol 35 n° 6 (June 2021)PermalinkElectrical resistivity, remote sensing and geographic information system approach for mapping groundwater potential zones in coastal aquifers of Gurpur watershed / H.S. Virupaksha in Geocarto international, vol 36 n° 8 ([01/05/2021])PermalinkEvaluation of light pollution in global protected areas from 1992 to 2018 / Haowei Mu in Remote sensing, vol 13 n° 9 (May-1 2021)PermalinkWhat is the difference between augmented reality and 2D navigation electronic maps in pedestrian wayfinding? / Weihua Dong in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)PermalinkDecision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping / Jiadi Yin in Remote sensing, vol 13 n° 8 (April-2 2021)PermalinkDEM resolution influences on peak flow prediction: a comparison of two different based DEMs through various rescaling techniques / Ali H. Ahmed Suliman in Geocarto international, vol 36 n° 7 ([15/04/2021])PermalinkDetecting archaeological features with airborne laser scanning in the alpine tundra of Sápmi, Northern Finland / Oula Seitsonen in Remote sensing, vol 13 n° 8 (April-2 2021)PermalinkPotentialité des données satellitaires Sentinel-2 pour la cartographie de l’impact des feux de végétation en Afrique tropicale : application au Togo / Yawo Konko in Bois et forêts des tropiques, n° 347 ([02/04/2021])PermalinkA CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery / Lucas Prado Osco in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)PermalinkGeovisualization of COVID-19: State of the art and opportunities / Yu Lan in Cartographica, vol 56 n° 1 (Spring 2021)PermalinkTemporal mosaicking approaches of Sentinel-2 images for extending topsoil organic carbon content mapping in croplands / Emmanuelle Vaudour in International journal of applied Earth observation and geoinformation, vol 96 (April 2021)PermalinkA user-driven process for INSPIRE-compliant land use database: example from Wallonia, Belgium / Benjamin Beaumont in Annals of GIS, vol 27 n° 2 (April 2021)PermalinkApports de la télédétection des puits pastoraux à la cartographie des eaux souterraines du Sahel / Bernard Collignon in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkCartographie de l’occupation du sol du Gabon en 2015, changements entre 2010 et 2015 / Farrel Nzigou Boucka in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkComplémentarité des images optiques Sentinel-2 avec les images radar Sentinel-1 et ALOS-PALSAR-2 pour la cartographie de la couverture végétale : application à une aire protégée et ses environs au Nord-Ouest du Maroc via trois algorithmes d’apprentissage automatique / Siham Acharki in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkDétection des zones de dégradation et de régénération de la couverture végétale dans le sud du Sénégal à travers l'analyse des tendances de séries temporelles MODIS NDVI et des changements d'occupation des sols à partir d'images LANDSAT / Boubacar Solly in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkEvaluation du potentiel des series d’images multi-temporelles optique et radar des satellites Sentinel 1 & 2 pour le suivi d’une zone côtière en contexte tropical: cas de l’estuaire du Cameroun pour la période 2015-2020 / Nourdi Njutapvoui in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkSuivi de la dynamique de l’occupation du sol en République de Guinée par imagerie satellitaire Spot : transfert technologique pour le développement d’outils performants d’aide à la décision / Gabriel Jaffrain in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkApplication of fuzzy analytical hierarchy process for assessment of desertification sensitive areas in North West of Morocco / Hicham Ait Kacem in Geocarto international, vol 36 n° 5 ([15/03/2021])PermalinkApplication of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring / Gopal Krishna in Geocarto international, vol 36 n° 5 ([15/03/2021])PermalinkÀ la croisée de l’art et de la science : la cartographie sensible comme dispositif de recherche-création / Elise Olmedo in Mappemonde, n° 130 (mars 2021)PermalinkAn experiment using the graphic variable color and the see color code on isarithmic maps accessible to blind and normally sighted people / Niédja Sodré de Araújo in Boletim de Ciências Geodésicas, vol 27 n° 1 ([01/03/2021])PermalinkChina’s high-resolution optical remote sensing satellites and their mapping applications / Deren Li in Geo-spatial Information Science, vol 24 n° 1 (March 2021)PermalinkDevelopment and assessment of rainwater harvesting suitability map using analytical hierarchy process, GIS and RS techniques / Khaled S. Balkhair in Geocarto international, vol 36 n° 4 ([01/03/2021])PermalinkFamous charts and forgotten fragments: exploring correlations in early Portuguese nautical cartography / Bruno Almeida in International journal of cartography, vol 7 n° 1 (March 2021)PermalinkHorizontal calibration of vessels with UASs / Casey O'Heran in Marine geodesy, vol 44 n° 2 (March 2021)PermalinkImproving the unsupervised mapping of riparian bugweed in commercial forest plantations using hyperspectral data and LiDAR / Kabir Peerbhay in Geocarto international, vol 36 n° 4 ([01/03/2021])PermalinkIntegration of an InSAR and ANN for sinkhole susceptibility mapping: A case study from Kirikkale-Delice (Turkey) / Hakan Nefeslioglu in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)PermalinkSpace-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach / Bisong Hu in International journal of geographical information science IJGIS, vol 35 n° 3 (March 2021)PermalinkToward a yearly country-scale CORINE land-cover map without using images: A map translation approach / Luc Baudoux in Remote sensing, Vol 13 n° 6 (March 2021)PermalinkAssessing spatial-temporal evolution processes and driving forces of karst rocky desertification / Fei Chen in Geocarto international, vol 36 n° 3 ([15/02/2021])PermalinkIntegrating runoff map of a spatially distributed model and thematic layers for identifying potential rainwater harvesting suitability sites using GIS techniques / Hamid Karimi in Geocarto international, vol 36 n° 3 ([15/02/2021])PermalinkAgricultural land partitioning model based on irrigation efficiency using a multi‐objective artificial bee colony algorithm / Mehrdad Bijandi in Transactions in GIS, Vol 25 n° 1 (February 2021)PermalinkAn integrated method for DEM simplification with terrain structural features and smooth morphology preserved / Wenhao Yu in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)PermalinkCrop identification by massive processing of multiannual satellite imagery for EU common agriculture policy subsidy control / Adolfo Lozano-Tello in European journal of remote sensing, vol 54 n° 1 (2021)PermalinkCrowdsourcing without data bias: Building a quality assurance system for air pollution symptom mapping / Marta Samulowska in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)PermalinkDetection of pictorial map objects with convolutional neural networks / Raimund Schnürer in Cartographic journal (the), vol 58 n° 1 (February 2021)PermalinkExtracting knowledge from legacy maps to delineate eco-geographical regions / Lin Yang in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)PermalinkGeomorphology and (palaeo-)hydrography of the Southern Atbai plain and western Eritrean Highlands (Eastern Sudan/Western Eritrea) / Stefano Costanzo in Journal of maps, vol 17 n° 2 (February 2021)PermalinkIdentifying urban growth patterns through land-use/land-cover spatio-temporal metrics: Simulation and analysis / Marta Sapena Moll in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)PermalinkLand cover harmonization using Latent Dirichlet Allocation / Zhan Li in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)PermalinkSpruce budworm tree host species distribution and abundance mapping using multi-temporal Sentinel-1 and Sentinel-2 satellite imagery / Rajeev Bhattarai in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)PermalinkTopoclimatic zoning of continental Chile / Donna Cortez in Journal of maps, vol 17 n° 2 (February 2021)PermalinkUsing automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain / R. Niederheiser in GIScience and remote sensing, vol 58 n° 1 (February 2021)Permalink