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Incorporating Sentinel-1 SAR imagery with the MODIS MCD64A1 burned area product to improve burn date estimates and reduce burn date uncertainty in wildland fire mapping / Kristofer Lasko in Geocarto international, vol 35 n° 6 ([01/05/2020])
[article]
Titre : Incorporating Sentinel-1 SAR imagery with the MODIS MCD64A1 burned area product to improve burn date estimates and reduce burn date uncertainty in wildland fire mapping Type de document : Article/Communication Auteurs : Kristofer Lasko, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Asie du sud-est
[Termes IGN] bande C
[Termes IGN] carte de la végétation
[Termes IGN] cartographie des risques
[Termes IGN] dynamique de la végétation
[Termes IGN] image Aqua-MODIS
[Termes IGN] image multibande
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] image Terra-MODIS
[Termes IGN] incendie de forêt
[Termes IGN] incertitude temporelle
[Termes IGN] Laos
[Termes IGN] qualité de l'air
[Termes IGN] Thaïlande
[Termes IGN] zone sinistréeRésumé : (auteur) Wildland fires result in a unique signal detectable by multispectral remote sensing and synthetic aperture radar (SAR). However, in many regions, such as Southeast Asia, persistent cloud cover and aerosols temporarily obstruct multispectral satellite observations of burned area, including the MODIS MCD64A1 Burned Area Product (BAP). Multiple days between cloud free pre- and post-burn MODIS observations result in burn date uncertainty. We incorporate cloud-penetrating, C-band SAR-with the MODIS MCD64A1 BAP in Southeast Asia, to exploit the strengths of each dataset to better estimate the burn date and reduce the potential burn date uncertainty range. We incorporate built-in quality control using MCD64A1 to reduce erroneous pixel updating. We test the method over part of Laos and Thailand during April 2016 and found average uncertainty reduction of 4.5 d, improving 15% of MCD64A1 pixels. A new BAP could improve monitoring temporal trends of wildland fires, air quality studies and monitoring post-fire vegetation dynamics. Numéro de notice : A2020-226 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1608592 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/https://doi.org/10.1080/10106049.2019.1608592 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94948
in Geocarto international > vol 35 n° 6 [01/05/2020][article]Assessment of malaria hazard, vulnerability, and risks in Dire Dawa City Administration of eastern Ethiopia using GIS and remote sensing / Abdinasir Moha in Applied geomatics, vol 12 n° 1 (April 2020)
[article]
Titre : Assessment of malaria hazard, vulnerability, and risks in Dire Dawa City Administration of eastern Ethiopia using GIS and remote sensing Type de document : Article/Communication Auteurs : Abdinasir Moha, Auteur ; Molla Maru, Auteur ; Tebarek Lika, Auteur Année de publication : 2020 Article en page(s) : pp 15 - 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] ArcGIS
[Termes IGN] cartographie des risques
[Termes IGN] changement climatique
[Termes IGN] Ethiopie
[Termes IGN] image infrarouge
[Termes IGN] image Landsat-OLI
[Termes IGN] maladie parasitaire
[Termes IGN] risque sanitaire
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (auteur) Malaria is a serious vector-borne disease affecting a greater proportion of the world’s population. Sub-Saharan Africa carries a disproportionately high share of the global malaria burden. Ethiopia is generally considered a low-to-moderate malaria transmission intensity country. However, the health sector in Ethiopia is greatly affected by climate change, which has profound consequences on the transmission cycles of vector-borne infectious diseases like malaria. The main objective of the study was to assess the spatial distribution of malaria hazard, vulnerability, and risk areas in Dire Dawa City Administration. GIS and remote-sensing in general and multi-criteria evaluation (MCE) in particular was used for assessing and mapping malaria hazard, risk, and vulnerable areas in Dire Dawa City Administration based on the data collected from various sources. The malaria hazard map of the study area labeled 0.6% of the region as low-hazard level, 79.7% moderate, 19.7% high, and 0.1% very low. Results of malaria vulnerability analysis reveal that about 23%, 73%, and 4% of the region was found to be vulnerable to malaria risk at very high, high, and low levels, respectively. The malaria risk map classifies 80% of the region as a moderate malaria-risk area and 20% as high malaria-risk area. This assessment advocates that the GIS and remote-sensing technology as tools can be used to provide timely information on malaria hazard, vulnerability, and risk areas for planning and taking measures at various levels ranging from early warning, monitoring, and control to prevention against malaria epidemics in a resource-efficient and cost-effective way. Numéro de notice : A2020-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-019-00276-5 Date de publication en ligne : 17/07/2019 En ligne : https://doi.org/10.1007/s12518-019-00276-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95862
in Applied geomatics > vol 12 n° 1 (April 2020) . - pp 15 - 22[article]A novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety / Mayra Salcedo-Gonzalez in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : A novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety Type de document : Article/Communication Auteurs : Mayra Salcedo-Gonzalez, Auteur ; Julio Suarez-Paez, Auteur ; Manuel Esteve, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] cartographie des risques
[Termes IGN] Colombie
[Termes IGN] criminalité
[Termes IGN] données spatiotemporelles
[Termes IGN] géoréférencement
[Termes IGN] géovisualisation
[Termes IGN] gestion des ressources humaines
[Termes IGN] gestion urbaine
[Termes IGN] logiciel libre
[Termes IGN] protection civile
[Termes IGN] risque social
[Termes IGN] système d'information urbain
[Termes IGN] système de contrôle
[Termes IGN] ville intelligenteRésumé : (auteur) This article shows a novel geo-visualization method of dynamic spatiotemporal data that allows mobility and concentration of criminal activity to be study. The method was developed using, only and significantly, real data of Santiago de Cali (Colombia), collected by the Colombian National Police (PONAL). This method constitutes a tool that allows criminal influx to be analyzed by concentration, zone, time slot and date. In addition to the field experience of police commanders, it allows patterns of criminal activity to be detected, thereby enabling a better distribution and management of police resources allocated to crime deterrence, prevention and control. Additionally, it may be applied to the concepts of safe city and smart city of the PONAL within the architecture of Command and Control System (C2S) of Command and Control Centers for Public Safety. Furthermore, it contributes to a better situational awareness and improves the future projection, agility, efficiency and decision-making processes of police officers, which are all essential for fulfillment of police missions against crime. Finally, this was developed using an open source software, it can be adapted to any other city, be used with real-time data and be implemented, if necessary, with the geographic software of any other C2S. Numéro de notice : A2020-259 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi9030160 Date de publication en ligne : 10/03/2020 En ligne : https://doi.org/10.3390/ijgi9030160 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95016
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 17 p.[article]
Titre : Deep learning for semantic feature extraction in aerial imagery Type de document : Thèse/HDR Auteurs : Ananya Gupta, Auteur ; Hujun Yin, Directeur de thèse ; Simon Watson, Directeur de thèse Editeur : Manchester [Royaume-Uni] : University of Manchester Année de publication : 2020 Importance : 151 p. Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the faculty of Science and engineeringLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage profond
[Termes IGN] cartographie d'urgence
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Dublin (Irlande ; ville)
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] image multitemporelle
[Termes IGN] OpenStreetMap
[Termes IGN] réseau routier
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] voxelIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Remote sensing provides image and LiDAR data that can be useful for a number of tasks such as disaster mapping and surveying. Deep learning (DL) has been shown to provide good results in extracting knowledge from input data sources by the means of learning intermediate representation features. However, popular DL methods require large scaled datasets for training which are costly and time-consuming to obtain. This thesis investigates semantic knowledge extraction from remote sensing data using DL methods in regimes with limited labelled data. Firstly, semantic segmentation methods are compared and analysed on the task of aerial image segmentation. It is shown that pretraining on ImageNet improves the segmentation results despite the domain shift between ImageNet images and aerial images. A framework for mapping road networks in disaster struck areas is proposed. It uses pre and post disaster imagery and labels from OpenStreetMaps (OSM), forgoing the need for costly manually labelled data. Graph-based methods are used to update the pre-existing road maps from OSM. Experiments on a disaster dataset from Palu, Indonesia show the efficacy of the proposed method. A method for semantic feature extraction from aerial imagery is proposed which is shown to work well for multitemporal high resolution image registration. These feature are able to deal with temporal variations caused by seasonal changes. Methods for tree identification in LiDAR data have been proposed to overcome the need for manually labelled data. The first method works on high density point clouds and uses certain LiDAR data attributes for tree identification, achieving almost 90% accuracy. The second uses a voxel based 3D Convolutional Neural Network on low density LiDAR datasets and is able to identify most large trees. The third method is a scaled version of PointNet++ and achieves an F_score of 82.1 on the ISPRS benchmark, comparable to the state of the art methods but with increased efficiency. Finally, saliency methods used for explainability in image analysis are extended to work on 3D point clouds and voxel-based networks to help aid explainability in this area. It is shown that edge and corner features are deemed important by these networks for classification. These features are also demonstrated to be inherently sparse and pruned easily. Note de contenu : 1- Introduction
2- Background and Literature Review
3- Aerial Image Segmentation with Open Data
4- Aerial Image Registration
5- Tree Annotations in LiDAR Data
6- 3D Point Cloud Feature Explanations
7- Conclusions and Future WorkNuméro de notice : 28302 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Science and Engineering : University of Manchester : 2020 DOI : sans En ligne : https://www.research.manchester.ac.uk/portal/files/184627877/FULL_TEXT.PDF Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98051 Optimizing arbovirus surveillance using risk mapping and coverage modelling / Joni A. Downs in Annals of GIS, Vol 26 n° 1 (January 2020)
[article]
Titre : Optimizing arbovirus surveillance using risk mapping and coverage modelling Type de document : Article/Communication Auteurs : Joni A. Downs, Auteur ; Mehrdad Vaziri, Auteur ; George Deskins, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 13 - 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] cartographie des risques
[Termes IGN] données environnementales
[Termes IGN] échantillonnage de données
[Termes IGN] épizootie
[Termes IGN] Floride (Etats-Unis)
[Termes IGN] maladie infectieuse
[Termes IGN] modélisation spatiale
[Termes IGN] optimisation spatiale
[Termes IGN] surveillance sanitaire
[Termes IGN] système d'information géographiqueRésumé : (auteur) Diseases carried by mosquitoes and other arthropods endanger human health globally. Though costly, surveillance efforts are vital for disease control and prevention This paper describes an approach for strategically configuring targeted disease surveillance sites across a study area. The methodology combines risk index mapping and spatial optimization modelling. The risk index is used to identify demand for surveillance, and the maximum covering location problem is used to select a specified number of candidate surveillance sites that covers the maximum amount of risk. The approach is demonstrated using a case study where optimal locations for sentinel surveillance sites are selected for the purposes of detecting eastern equine encephalitis virus in a county in the state of Florida. Optimal sentinel sites were selected under a number of scenarios that modelled different target populations (horses or humans), coverage distances (0.5, 1.0, and 1.5 km), and numbers of sites to select (1–12). Sentinel site selections for the horse and human models displayed different spatial patterns, with horse sites located largely in the west-central region and human ones in the north-central. Minor amounts of spatial overlap between the horse and human sites were observed, especially as coverage distances and numbers of sites were increased. Additionally, a near linear increase in risk coverage was observed as sites were incrementally added to the scenarios. This finding suggests that the number of sentinel sites within the ranges explored should be based on the maximum that can be funded, since they provide similar levels of benefit. Numéro de notice : A2020-117 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2019.1688391 Date de publication en ligne : 18/11/2019 En ligne : https://doi.org/10.1080/19475683.2019.1688391 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94736
in Annals of GIS > Vol 26 n° 1 (January 2020) . - pp 13 - 23[article]PermalinkA thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding / Mohammad Khalid Hossain in Computers, Environment and Urban Systems, vol 79 (January 2020)PermalinkNew method for environmental monitoring in armed conflict zones: a case study of Syria / Samira Mobaied in Environmental Monitoring and Assessment, vol 191 n° 11 (November 2019)PermalinkUtilisation des SIG et de la télédétection pour la cartographie de la susceptibilité aux mouvements d'instabilité de versant dans l'Ouest montagneux de la Côte d'Ivoire / Boyossoro Hélène Kouadio in Revue Française de Photogrammétrie et de Télédétection, n° 221 (novembre 2019)PermalinkAdvanced Remote Sensing Technology for Synthetic Aperture Radar Applications, Tsunami Disasters, and Infrastructure / Maged Marghany (2019)PermalinkRéorganisation du SIG et valorisation des données du Parc Naturel Régional du Gâtinais français / Paul Roux (2019)PermalinkSpatial discontinuities, health and mobility - What do the Google's POIs and tweets tell us about Bangkok's (Thailand) structures and spatial dynamics? / Alexandre Cebeillac in Revue internationale de géomatique, vol 28 n° 4 (octobre - décembre 2018)PermalinkAlgorithm of land cover spatial data processing for the local flood risk mapping / Monika Siejka in Survey review, vol 50 n° 362 (August 2018)PermalinkModeling of inland flood vulnerability zones through remote sensing and GIS techniques in the highland region of Papua New Guinea / Porejane Harley in Applied geomatics, vol 10 n° 2 (June 2018)PermalinkAn open source framework for publishing flood inundation extent libraries in a Web GIS environment using open source technologies / Vinod Kumar Sharma in International journal of cartography, vol 4 n° 1 (March 2018)Permalink