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Building a small fire database for Sub-Saharan Africa from Sentinel-2 high-resolution images / Emilio Chuvieco in Science of the total environment, vol 845 (November 1 2022)
[article]
Titre : Building a small fire database for Sub-Saharan Africa from Sentinel-2 high-resolution images Type de document : Article/Communication Auteurs : Emilio Chuvieco, Auteur ; Ekhi Roteta, Auteur ; Matteo Sali, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 157139 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Afrique subsaharienne
[Termes IGN] base de données localisées
[Termes IGN] image Sentinel-MSI
[Termes IGN] zone sinistréeRésumé : (auteur) Coarse resolution sensors are not very sensitive at detecting small fire patches, making current estimations of global burned areas (BA) very conservative. Using medium or high-resolution sensors to generate BA products becomes then a priority, particularly in areas where fires tend to be small and frequent. Building on previous work that developed a small fire dataset (SFD) for Sub-Saharan Africa for 2016, this paper presents a new version of the dataset for 2019 using the two Sentinel-2 satellites (A and B) and VIIRS active fires. Total estimated BA was 4.8 Mkm2. This value was much higher than estimations from two global, coarser-spatial resolution BA products based on MODIS data for the same area and period: 80 % greater than estimates from FireCCI51 (based on MODIS 250 m bands) and 120 % larger than MCD64A1 (based on MODIS 500 m bands). The main differences were observed in those months with higher fire occurrence (November to January for the Northern Hemisphere regions and June to September for the Southern Hemisphere ones). Accuracy assessment of the SFD product was based on a novel sampling strategy designed to obtain independent fire reference perimeters. Validation results showed remarkable high accuracy values comparing to existing global BA products. Overall omission errors (OE) were estimated as 8.5 %, commission errors (CE) as 15.0 %, with a Dice Coefficient of 87.7 %. All of these estimations implied significant improvements over the global, coarser spatial resolution BA products (OE > 50 % and CE > 20 % for the same area and period), as well as over the previous SFD product for 2016 of the same area, generated from a single Sentinel-2 satellite and MODIS active fires (OE = 26.5 % and CE = 19.3 %). Temporal accuracies greatly increased as well with the new product, with 92.5 % of fires detected within the first 10 days of occurrence. Numéro de notice : A2022-570 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scitotenv.2022.157139 Date de publication en ligne : 13/07/2022 En ligne : https://doi.org/10.1016/j.scitotenv.2022.157139 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101279
in Science of the total environment > vol 845 (November 1 2022) . - n° 157139[article]Evaluation of automatic prediction of small horizontal curve attributes of mountain roads in GIS environments / Sercan Gülci in ISPRS International journal of geo-information, vol 11 n° 11 (November 2022)
[article]
Titre : Evaluation of automatic prediction of small horizontal curve attributes of mountain roads in GIS environments Type de document : Article/Communication Auteurs : Sercan Gülci, Auteur ; Afiz Hulusi Acar, Auteur ; Abdullah E. Akay, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 560 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de Douglas-Peucker
[Termes IGN] attribut géomètrique
[Termes IGN] coefficient de corrélation
[Termes IGN] courbe
[Termes IGN] matrice de confusion
[Termes IGN] montagne
[Termes IGN] réseau routier
[Termes IGN] système d'information géographique
[Termes IGN] tracé routier
[Termes IGN] Turquie
[Vedettes matières IGN] GénéralisationRésumé : (auteur) Road curve attributes can be determined by using Geographic Information System (GIS) to be used in road vehicle traffic safety and planning studies. This study involves analyzing the GIS-based estimation accuracy in the length, radius and the number of small horizontal road curves on a two-lane rural road and a forest road. The prediction success of horizontal curve attributes was investigated using digitized raw and generalized/simplified road segments. Two different roads were examined, involving 20 test groups and two control groups, using 22 datasets obtained from digitized and surveyed roads based on satellite imagery, GIS estimates, and field measurements. Confusion matrix tables were also used to evaluate the prediction accuracy of horizontal curve geometry. F-score, Mathews Correlation Coefficient, Bookmaker Informedness and Balanced Accuracy were used to investigate the performance of test groups. The Kruskal–Wallis test was used to analyze the statistical relationships between the data. Compared to the Bezier generalization algorithm, the Douglas–Peucker algorithm showed the most accurate horizontal curve predictions at generalization tolerances of 0.8 m and 1 m. The results show that the generalization tolerance level contributes to the prediction accuracy of the number, curve radius, and length of the horizontal curves, which vary with the tolerance value. Thus, this study underlined the importance of calculating generalizations and tolerances following a manual road digitization. Numéro de notice : A2022-847 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11110560 Date de publication en ligne : 09/11/2022 En ligne : https://doi.org/10.3390/ijgi11110560 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102083
in ISPRS International journal of geo-information > vol 11 n° 11 (November 2022) . - n° 560[article]A machine learning approach for detecting rescue requests from social media / Zheye Wang in ISPRS International journal of geo-information, vol 11 n° 11 (November 2022)
[article]
Titre : A machine learning approach for detecting rescue requests from social media Type de document : Article/Communication Auteurs : Zheye Wang, Auteur ; Nina S.N. Lam, Auteur ; Mingxuan Sun, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 570 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] apprentissage automatique
[Termes IGN] code postal
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] Etats-Unis
[Termes IGN] filtrage d'information
[Termes IGN] secours d'urgence
[Termes IGN] tempête
[Termes IGN] terminologie
[Termes IGN] TwitterRésumé : (auteur) Hurricane Harvey in 2017 marked an important transition where many disaster victims used social media rather than the overloaded 911 system to seek rescue. This article presents a machine-learning-based detector of rescue requests from Harvey-related Twitter messages, which differentiates itself from existing ones by accounting for the potential impacts of ZIP codes on both the preparation of training samples and the performance of different machine learning models. We investigate how the outcomes of our ZIP code filtering differ from those of a recent, comparable study in terms of generating training data for machine learning models. Following this, experiments are conducted to test how the existence of ZIP codes would affect the performance of machine learning models by simulating different percentages of ZIP-code-tagged positive samples. The findings show that (1) all machine learning classifiers except K-nearest neighbors and Naïve Bayes achieve state-of-the-art performance in detecting rescue requests from social media; (2) using ZIP code filtering could increase the effectiveness of gathering rescue requests for training machine learning models; (3) machine learning models are better able to identify rescue requests that are associated with ZIP codes. We thereby encourage every rescue-seeking victim to include ZIP codes when posting messages on social media. This study is a useful addition to the literature and can be helpful for first responders to rescue disaster victims more efficiently. Numéro de notice : A2022-846 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11110570 Date de publication en ligne : 16/11/2022 En ligne : https://doi.org/10.3390/ijgi11110570 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102081
in ISPRS International journal of geo-information > vol 11 n° 11 (November 2022) . - n° 570[article]A new spatial database framework for pedestrian indoor navigation based on the OpenStreetMap tag information / Gift Dumedah in Transactions in GIS, vol 26 n° 7 (November 2022)
[article]
Titre : A new spatial database framework for pedestrian indoor navigation based on the OpenStreetMap tag information Type de document : Article/Communication Auteurs : Gift Dumedah, Auteur ; Abdul-Karim Wumpini Fuseini, Auteur ; Isaac Marfo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 3090 - 3108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] approche hiérarchique
[Termes IGN] données localisées des bénévoles
[Termes IGN] Ghana
[Termes IGN] navigation pédestre
[Termes IGN] OpenStreetMap
[Termes IGN] positionnement en intérieur
[Termes IGN] universitéRésumé : (auteur) It is widely acknowledged that the tools for pedestrian navigation in indoor environments have been increasing while the internal spaces of buildings continue to grow in complexity. The majority of mobile applications for indoor navigation are mostly dependent on access to radio-frequency identification (RFID) and WiFi, which are particularly limited and expensive in most of Sub-Saharan Africa. In addition, data from Volunteered Geographic Information such as OpenStreetMap (OSM) lacked clear framework and specification for database design for indoor navigation. Accordingly, this study proposed and illustrated a new database framework for indoor navigation by taking advantage of the popular OSM tag information structure. The proposed framework characterized the indoor environment based on horizontal and vertical partitions, together with description of indoor features by using cardinal directions and qualitative descriptions. The framework was demonstrated by creating sample database records, and retrieval of step-by-step travel information for different internal configurations of the indoor environment. A key contribution of this framework is its simplistic and low-cost nature, where user travel information is retrieved from the database with no need for communication signals from Global Positioning Systems, RFID, or WiFi, making it advantageous for low-cost applications where access to these communication infrastructure are limited. Numéro de notice : A2022-889 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12998 Date de publication en ligne : 25/10/2022 En ligne : https://doi.org/10.1111/tgis.12998 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102234
in Transactions in GIS > vol 26 n° 7 (November 2022) . - pp 3090 - 3108[article]A robust edge detection algorithm based on feature-based image registration (FBIR) using improved canny with fuzzy logic (ICWFL) / Anchal Kumawat in The Visual Computer, vol 38 n° 11 (November 2022)
[article]
Titre : A robust edge detection algorithm based on feature-based image registration (FBIR) using improved canny with fuzzy logic (ICWFL) Type de document : Article/Communication Auteurs : Anchal Kumawat, Auteur ; Sucheta Panda, Auteur Année de publication : 2022 Article en page(s) : pp 3681 - 3702 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] accentuation d'image
[Termes IGN] base de données d'images
[Termes IGN] détection de contours
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] filtre de Wiener
[Termes IGN] Inférence floue
[Termes IGN] logique floue
[Termes IGN] méthode robuste
[Termes IGN] restauration d'image
[Termes IGN] seuillage
[Termes IGN] superposition d'imagesRésumé : (auteur) The problem of edge detection plays a crucial role in almost all research areas of image processing. If edges are detected accurately, one can detect the location of objects and the parameters such as shape and area can be measured more precisely. In order to overcome the above problem, a feature-based image registration (FBIR) method in combination with an improved version of canny with fuzzy logic is proposed for accurate detection of edges. The major contributions of the present work are summarized in three steps. In the first step, a restoration-based enhancement algorithm is proposed to get a fine image from a distorted noisy image. In the second step, two versions of input images are registered using a modified FBIR approach. In the third step, to overcome the drawback of canny edge detection algorithm, each step of the algorithm is modified. The output is then fed to a “fuzzy inference system”. The “fuzzy rule-based technique”, when applied to the problem of “edge detection”, is very “efficient” because the thickness of the edges can be controlled by simply changing “rules and output parameters”. The domain of the images under consideration is various well-known image databases such as Berkeley and USC-SIPI databases, whereas the proposed method is also suitable for other types of both indoor and outdoor images. The robustness of the proposed method is analysed, compared and evaluated with seven image assessment quality (IAQ) parameters. The performance of the proposed method is compared with some of the state-of-the-art edge detection methods in terms of the seven IAQ parameters. Numéro de notice : A2022-839 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-021-02196-1 Date de publication en ligne : 14/07/2021 En ligne : https://doi.org/10.1007/s00371-021-02196-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102041
in The Visual Computer > vol 38 n° 11 (November 2022) . - pp 3681 - 3702[article]Semi-automatic development of thematic tactile maps / Jakub Wabiński in Cartography and Geographic Information Science, vol 49 n° 6 (November 2022)PermalinkComparison of change and static state as the dependent variable for modeling urban growth / Yongjiu Feng in Geocarto international, vol 37 n° 23 ([15/10/2022])PermalinkRaster-based method for building selection in the multi-scale representation of two-dimensional maps / Yilang Shen in Geocarto international, vol 37 n° 22 ([10/10/2022])PermalinkApplication of a graph convolutional network with visual and semantic features to classify urban scenes / Yongyang Xu in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)PermalinkIdentifying the key resources and missing elements to build a knowledge graph dedicated to spatial dataset search / Mehdi Zrhal in Procedia Computer Science, vol 207 (2022)PermalinkIncremental road network update method with trajectory data and UAV remote sensing imagery / Jianxin Qin in ISPRS International journal of geo-information, vol 11 n° 10 (October 2022)PermalinkInvestigation of recognition and classification of forest fires based on fusion color and textural features of images / Cong Li in Forests, vol 13 n° 10 (October 2022)PermalinkPredicting the variability in pedestrian travel rates and times using crowdsourced GPS data / Michael J. Campbell in Computers, Environment and Urban Systems, vol 97 (October 2022)PermalinkThe fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas / Jun Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 10 (October 2022)PermalinkCrowdsourcing-based application to solve the problem of insufficient training data in deep learning-based classification of satellite images / Ekrem Saralioglu in Geocarto international, vol 37 n° 18 ([01/09/2022])Permalink