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GIS 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)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 9 (September 2021) . - n° 598 Titre : GIS models for vulnerability of coastal erosion assessment in a tropical protected area Type de document : Article/Communication Auteurs : Luís Russo Vieira, Auteur ; José Guilherme Vieira, Auteur ; Isabel Marques da silva, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] Brésil [Termes IGN] érosion côtière [Termes IGN] géoréférencement [Termes IGN] mangrove [Termes IGN] modèle de simulation [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité [Termes IGN] zone intertropicale Résumé : (auteur) Coastal erosion is considered a major worldwide challenge. The vulnerability assessment of coastal areas, in relation to climate change, is a key topic of worldwide increasing interest. The integration of methodologies supported by Remote Sensing, Geographical Information Systems (GIS) and in situ monitoring has allowed a viable identification of vulnerable areas to erosion. In the present study, a model was proposed to the assessment of the estuarine system of Cananéia-Iguape (Brazil), by applying the evaluation and prediction of vulnerability models for the conservation and preservation of mangroves. Approximately 1221 Km2 were classified, with 16% of the total presenting high and very high vulnerability to erosion. Other relevant aspects, were the identification and georeferencing sites that showed strong evidence of erosion and, thus, having a huge influence on the final vulnerability scores. The obtained results led to the development of a multidisciplinary approach through the application of a prediction and description model that resulted from the adaptation of the study system from a set of implemented models for coastal regions, in order to contribute to the erosion vulnerability assessment in the mangroves ecosystems (and associated localities, municipalities and communities). Numéro de notice : A2021-685 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10090598 date de publication en ligne : 10/09/2021 En ligne : https://doi.org/10.3390/ijgi10090598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98411 [article]

Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data / Laura Elena Cué La Rosa in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 179 (September 2021) . - pp 35 - 49 Titre : Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data Type de document : Article/Communication Auteurs : Laura Elena Cué La Rosa, Auteur ; Camile Sothe, Auteur ; Raul Queiroz Feitosa, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 35 - 49 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Brésil [Termes IGN] carte de la végétation [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] densité de la végétation [Termes IGN] données d'apprentissage [Termes IGN] espèce végétale [Termes IGN] étiquetage sémantique [Termes IGN] forêt tropicale [Termes IGN] image captée par drone [Termes IGN] image hyperspectrale Résumé : (Auteur) This work proposes a multi-task fully convolutional architecture for tree species mapping in dense forests from sparse and scarce polygon-level annotations using hyperspectral UAV-borne data. Our model implements a partial loss function that enables dense tree semantic labeling outcomes from non-dense training samples, and a distance regression complementary task that enforces tree crown boundary constraints and substantially improves the model performance. Our multi-task architecture uses a shared backbone network that learns common representations for both tasks and two task-specific decoders, one for the semantic segmentation output and one for the distance map regression. We report that introducing the complementary task boosts the semantic segmentation performance compared to the single-task counterpart in up to 11% reaching an average user’s accuracy of 88.63% and an average producer’s accuracy of 88.59%, achieving state-of-art performance for tree species classification in tropical forests. Numéro de notice : A2021-575 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.07.001 date de publication en ligne : 28/07/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.07.001 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98175 [article]

Fast unsupervised multi-scale characterization of urban landscapes based on Earth observation data / Claire Teillet in Remote sensing, vol 13 n° 12 (June-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 12 (June-2 2021) . - n° 2398 Titre : Fast unsupervised multi-scale characterization of urban landscapes based on Earth observation data Type de document : Article/Communication Auteurs : Claire Teillet, Auteur ; Benjamin Pillot, Auteur ; Thibault Catry, Auteur ; Laurent Demagistri, Auteur ; Dominique Lyszczarz, Auteur ; Marc Lang, Auteur ; Pierre Couteron, Auteur ; Nicolas Barbier, Auteur ; Arsène Adou Kouassi, Auteur ; Quentin Gunther, Auteur ; Nadine Dessay, Auteur Année de publication : 2021 Projets : GeoSud / , TOSCA / Article en page(s) : n° 2398 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Bouaké [Termes IGN] Brasilia [Termes IGN] caractérisation [Termes IGN] empreinte [Termes IGN] image Pléiades-HR [Termes IGN] image Sentinel-MSI [Termes IGN] paysage urbain [Termes IGN] texture d'image [Termes IGN] zone urbaine Résumé : (auteur) Most remote sensing studies of urban areas focus on a single scale, using supervised methodologies and very few analyses focus on the “neighborhood” scale. The lack of multi-scale analysis, together with the scarcity of training and validation datasets in many countries lead us to propose a single fast unsupervised method for the characterization of urban areas. With the FOTOTEX algorithm, this paper introduces a texture-based method to characterize urban areas at three nested scales: macro-scale (urban footprint), meso-scale (“neighbourhoods”) and micro-scale (objects). FOTOTEX combines a Fast Fourier Transform and a Principal Component Analysis to convert texture into frequency signal. Several parameters were tested over Sentinel-2 and Pleiades imagery on Bouake and Brasilia. Results showed that a single Sentinel-2 image better assesses the urban footprint than the global products. Pleiades images allowed discriminating neighbourhoods and urban objects using texture, which is correlated with metrics such as building density, built-up and vegetation proportions. The best configurations for each scale of analysis were determined and recommendations provided to users. The open FOTOTEX algorithm demonstrated a strong potential to characterize the three nested scales of urban areas, especially when training and validation data are scarce, and computing resources limited. Numéro de notice : A2021-505 Affiliation des auteurs : ENSG+Ext (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13122398 date de publication en ligne : 19/06/2021 En ligne : https://doi.org/10.3390/rs13122398 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98125 [article]

Multicriterial method of AHP analysis for the identification of coastal vulnerability regarding the rise of sea level: case study in Ilha Grande Bay, Rio de Janeiro, Brazil / Julia Caon Araujo in Natural Hazards, vol 107 n° 1 (May 2021)  

Public [article]  inNatural Hazards > vol 107 n° 1 (May 2021) . - pp 53 - 72 Titre : Multicriterial method of AHP analysis for the identification of coastal vulnerability regarding the rise of sea level: case study in Ilha Grande Bay, Rio de Janeiro, Brazil Type de document : Article/Communication Auteurs : Julia Caon Araujo, Auteur ; Fabio Ferreira Dias, Auteur Année de publication : 2021 Article en page(s) : pp 53 - 72 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse multicritère [Termes IGN] changement climatique [Termes IGN] érosion côtière [Termes IGN] modèle numérique de terrain [Termes IGN] montée du niveau de la mer [Termes IGN] processus d'analyse hiérarchique [Termes IGN] Rio de Janeiro [Termes IGN] surveillance du littoral [Termes IGN] système d'information géographique Résumé : (auteur) Current climate changes have several consequences, such as rising sea levels. Today, the identification of coastal vulnerabilities worldwide is necessary to prevent impacts and drive action. The aim of the work was to estimate the vulnerable areas from a total rate of increase in sea level of 2.8 m and to identify the impacts of greater magnitude through the use of hierarchical analysis. The analytic hierarchy process method was used to list the most serious impacts. In addition, the simulation of the most vulnerable sites was carried out in a GIS environment using geoprocessing and a digital terrain model for the area of study. The Ilha Grande Bay region (southeastern Brazil) was chosen as a test area due to its economic, tourist and environmental importance. The main impacts are floods, coastal erosion and loss of coastal ecosystems. The most vulnerable areas are characterized as flat with low slopes, usually coastal plains occupied by environmental protection areas, urban centers and historical centers. The methodology proved to be effective in assessing and forecasting vulnerable areas and can be applied to several types of coastal areas. Numéro de notice : A2021-537 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s11069-021-04573-4 date de publication en ligne : 05/02/2021 En ligne : https://doi.org/10.1007/s11069-021-04573-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98007 [article]

An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards / Geraldo Moura Ramos Filho in Natural Hazards, Vol 105 n° 3 (February 2021)  

Public [article]  inNatural Hazards > Vol 105 n° 3 (February 2021) . - pp 2409 - 2429 Titre : An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards Type de document : Article/Communication Auteurs : Geraldo Moura Ramos Filho, Auteur ; Victor Hugo Rabelo Coelho, Auteur ; Emerson da Silva Freitas, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2409 - 2429 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Antecedent precipitation index [Termes IGN] crue [Termes IGN] indice de risque [Termes IGN] inondation [Termes IGN] méthode robuste [Termes IGN] prévention des risques [Termes IGN] risque naturel [Termes IGN] Sao Paulo [Termes IGN] seuillage [Termes IGN] surveillance hydrologique Résumé : (auteur) This paper presents an improved method of using threshold of peak rainfall intensity for robust flood/flash flood evaluation and warnings in the state of São Paulo, Brazil. The improvements involve the use of two tolerance levels and the delineating of an intermediate threshold by incorporating an exponential curve that relates rainfall intensity and Antecedent Precipitation Index (API). The application of the tolerance levels presents an average increase of 14% in the Probability of Detection (POD) of flood and flash flood occurrences above the upper threshold. Moreover, a considerable exclusion (63%) of non-occurrences of floods and flash floods in between the two thresholds significantly reduce the number of false alarms. The intermediate threshold using the exponential curves also exhibits improvements for almost all time steps of both hydrological hazards, with the best results found for floods correlating 8-h peak intensity and 8 days API, with POD and Positive Predictive Value (PPV) values equal to 81% and 82%, respectively. This study provides strong indications that the new proposed rainfall threshold-based approach can help reduce the uncertainties in predicting the occurrences of floods and flash floods. Numéro de notice : A2020-204 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-020-04405-x date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.1007/s11069-020-04405-x Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97167 [article]

Influence of flight altitude and control points in the georeferencing of images obtained by unmanned aerial vehicle / Lucas Santos Santana in European journal of remote sensing, vol 54 n° 1 (2021)  

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Performance of 6 different global navigation satellite system receivers at low latitude under moderate and strong scintillation / E.R. de Paula in Earth and space science, vol 8 n° 2 (February 2021)  

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Quantification of cotton water consumption by remote sensing / Jefferson Vieira José in Geocarto international, vol 35 n° 16 ([01/12/2020])  

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School cartography in Brazil and its inclusive perspective / Imre Josef Demhardt in International journal of cartography, vol 6 n° 3 (October 2020)  

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Carbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing / Felipe Schwerz in Annals of Forest Science [en ligne], vol 77 n° 3 (September 2020)  

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What Is threatening forests in protected areas? A global assessment of deforestation in protected areas, 2001–2018 / Christopher M. Wade in Forests, vol 11 n° 5 (May 2020)  

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A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery / Lucas Prado Osco in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

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Statistical assessment of cartographic product from photogrammetry and fixed-wing UAV acquisition / Ademir Marques Junior in European journal of remote sensing, vol 53 n° 1 (2020)  

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Flowering acceleration in native Brazilian tree species for genetic conservation and breeding / Gleidson Guilherme Caldas Mende in Annals of forest research, Vol 63 n° 1 (January - June 2020)  

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Estimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry / Juliana Batistoti in Remote sensing, Vol 11 n° 20 (October 2019)  

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