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An informal road detection neural network for societal impact in developing countries / Inger Fabris-Rotelli in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2022 (2022 edition)
[article]
Titre : An informal road detection neural network for societal impact in developing countries Type de document : Article/Communication Auteurs : Inger Fabris-Rotelli, Auteur ; Abraham Wannenburg, Auteur ; Gao Maribe, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 267 - 274 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] Afrique du sud (état)
[Termes IGN] apprentissage profond
[Termes IGN] données étiquetées d'entrainement
[Termes IGN] extraction du réseau routier
[Termes IGN] image satellite
[Termes IGN] impact social
[Termes IGN] pays en développement
[Termes IGN] réseau neuronal artificielRésumé : (auteur) Roads found in informal settlements arise out of convenience, and are often not recorded or maintained by authorities. This complicates service delivery, sustainable development and crisis mitigation, including management and tracking of COVID-19. We, therefore, aim to extract informal roads in remote sensing images. Existing techniques aiming at the extraction of formal roads are not suitable for the problem due to the complex physical and spectral properties of informal roads. The only existing approaches for informal roads, namely (Nobrega et al., 2006, Thiede et al., 2020), do not consider neural networks as a solution. Neural networks show promise in overcoming these complexities. However, they require a large amount of data to learn, which is currently not available due to the expensive and time-consuming nature of collecting such data. This paper implements a neural network to extract informal roads from a data set digitised by this research group. Data quality is assessed by calculating validity completeness, homogeneity and the V-measure, a measure of consistency, in order to evaluate the overall usability of the dataset for neural network informal road detection. We implement the GANs-UNet model that obtained the highest F1-score in a 2020 review paper (Abdollahi et al., 2020) on the state-of-the-art deep learning models used to extract formal roads. The results indicate that the model is able to extract informal roads successfully in the presence of appropriate training data. Numéro de notice : A2022-424 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.5194/isprs-annals-V-4-2022-267-2022 Date de publication en ligne : 18/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-4-2022-267-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100729
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-4-2022 (2022 edition) . - pp 267 - 274[article]Classification of vegetation classes by using time series of Sentinel-2 images for large scale mapping in Cameroon / Hermann Tagne in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)
[article]
Titre : Classification of vegetation classes by using time series of Sentinel-2 images for large scale mapping in Cameroon Type de document : Article/Communication Auteurs : Hermann Tagne, Auteur ; Arnaud Le Bris , Auteur ; David Monkam, Auteur ; Clément Mallet , Auteur Année de publication : 2022 Projets : TOSCA Parcelle / Le Bris, Arnaud Article en page(s) : pp 673 - 680 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Cameroun
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] occupation du sol
[Termes IGN] série temporelleRésumé : (auteur) Sentinel-2 satellites provide dense image time series exhibiting high spectral, spatial and temporal resolutions. These images are in particular of utter interest for Land-Cover (LC) mapping at large scales. LC maps can now be computed on a yearly basis at the scale of a country with efficient supervised classifiers, assuming suitable training data are available. However, the efficient exploitation of large amount of Sentinel-2 imagery still remain challenging on unexplored areas where state-of-the-art classifiers are prone to fail. This paper focuses on Land-Cover mapping over Cameroon for the purpose of updating the Very High Resolution national topographic geodatabase. The ι2 framework is adopted and tested for the specificity of the country. Here, experiments focus on generic vegetation classes (five) which enables providing robust focusing masks for higher resolution classifications. Two strategies are compared: (i) a LC map is calculated out of a year long time series and (ii) monthly LC maps are generated and merged into a single yearly map. Satisfactory accuracy scores are obtained (>94% in Overall Accuracy), allowing to provide a first step towards finer-grained map retrieval. Numéro de notice : A2022-426 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-3-2022-673-2022 Date de publication en ligne : 18/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-3-2022-673-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100731
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-3-2022 (2022 edition) . - pp 673 - 680[article]Comparison between Gaussian and decorrelation filters of GRACE-based RL05 temporal gravity solutions over Egypt / Basem Elsaka in Survey review, vol 54 n° 384 (May 2022)
[article]
Titre : Comparison between Gaussian and decorrelation filters of GRACE-based RL05 temporal gravity solutions over Egypt Type de document : Article/Communication Auteurs : Basem Elsaka, Auteur ; Mohamed El-Ashquer, Auteur Année de publication : 2022 Article en page(s) : pp 233 - 242 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] analyse comparative
[Termes IGN] champ de pesanteur local
[Termes IGN] décorrélation
[Termes IGN] données GRACE
[Termes IGN] Egypte
[Termes IGN] filtre de GaussRésumé : (auteur) This contribution provides a comparison between the Gaussian and decorrelation filters as derived from GRACE products (RL05) estimated by the official GRACE Science Data System centres (GFZ, CSR and JPL) as well as the ITSG-GRACE2016 solutions over Egypt. The outcome of this study will help in finding out which of these centres provides improved temporal gravity solutions as well as the most promising GRACE time series over Egypt. The obtained results regarding Gaussian filters show that the GFZ centre provides the most promising solutions w.r.t. CSR and JPL. Whereas the ITSG-GRACE2016 products provide improvements, especially at Gaussian radius 200 km, of about 56%, 68% and 60% w.r.t. CSR, JPL and GFZ solutions, respectively. Regarding the decorrelation filtering, the ITSG-GRACE2016 provides the least Std. w.r.t. CSR, JPL and GFZ solutions showing for the DDK8 improvement of about 48%, 64% and 68% w.r.t. the three centres GFZ, JPL and CSR, respectively. Numéro de notice : A2022-355 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2021.1919841 Date de publication en ligne : 04/05/2021 En ligne : https://doi.org/10.1080/00396265.2021.1919841 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100553
in Survey review > vol 54 n° 384 (May 2022) . - pp 233 - 242[article]Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns / Damilola Eyelade in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)
[article]
Titre : Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns Type de document : Article/Communication Auteurs : Damilola Eyelade, Auteur ; Keith C. Clarke, Auteur ; Ighodalo Ijagbone, Auteur Année de publication : 2022 Article en page(s) : pp 1037 - 1058 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] changement d'utilisation du sol
[Termes IGN] croissance urbaine
[Termes IGN] dalle
[Termes IGN] données spatiotemporelles
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle de simulation
[Termes IGN] modélisation spatiale
[Termes IGN] Nigéria
[Termes IGN] OpenStreetMapRésumé : (auteur) The SLEUTH model provides a framework for understanding land use evolution around urban areas. Calibration of SLEUTH’s behavioral coefficients can be impacted by scale and nonlinear transitions due to the SLEUTH land use deltatron module’s assumption of linear Markov change probabilities. This study attempted to establish what spatial resolution and temporal scale produces the most accurate forecasts given the linear change assumption. The impact of tiling the input data was also examined. To determine these, SLEUTH was calibrated at four spatial and three temporal scales for Ibadan, Nigeria using both untiled and tiled data. Calibration results were evaluated using accuracy metrics including Figure of Merit (FOM) and mean uncertainty. The best mix of calibration metrics (FOM 0.26) and mean uncertainty (11.64) was achieved at 30 m resolution and an intermediate temporal interval. Tiling input data led to overfitting, allowing good model fit within individual tiles but a reduction in trend recognition across land use types. Subsequently, a 2040 projection that is as accurate as possible, and scientifically justifiable given the available data, was produced. The findings provide a framework for understanding the effect of spatiotemporal scale on SLEUTH inputs that require tiling particularly for urban areas in the global south. Numéro de notice : A2022-347 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2011292 Date de publication en ligne : 16/12/2021 En ligne : https://doi.org/10.1080/13658816.2021.2011292 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100531
in International journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 1037 - 1058[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022051 SL Revue Centre de documentation Revues en salle Disponible Plastic waste cleanup priorities to reduce marine pollution: A spatiotemporal analysis for Accra and Lagos with satellite data / Susmita Dasgupta in Science of the total environment, vol 839 (May 2022)
[article]
Titre : Plastic waste cleanup priorities to reduce marine pollution: A spatiotemporal analysis for Accra and Lagos with satellite data Type de document : Article/Communication Auteurs : Susmita Dasgupta, Auteur ; Maria Sarraf, Auteur ; David M. Wheeler, Auteur Année de publication : 2022 Article en page(s) : n° 156319 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] déchet
[Termes IGN] distribution spatiale
[Termes IGN] enquête
[Termes IGN] géoréférencement
[Termes IGN] Ghana
[Termes IGN] image à haute résolution
[Termes IGN] Lagos
[Termes IGN] littoral
[Termes IGN] matière plastique
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] pollution des mers
[Termes IGN] variation saisonnièreRésumé : (auteur) Plastic waste, with an estimated lifetime of centuries, accounts for the major share of marine litter. Each year, thousands of fish, sea birds, sea turtles, and other marine species are killed by ingesting or becoming entangled with plastic debris. Reducing marine plastic pollution is particularly challenging for developing countries owing to the wide dispersal of plastic waste disposal and scarce public cleanup resources. To costeffectively reduce marine pollution, resources should target “hotspot” areas, where large volumes of plastic litter have a high likelihood of ending up in the ocean. Using new public information, this study develops a hotspot targeting strategy for Accra and Lagos, which are major sources of marine plastic pollution in West Africa. The same global information sources can support hotspot analyses for many other coastal cities that generate marine plastic waste. The methodology combines georeferenced household survey data on plastic use, measures of seasonal variation in marine plastic pollution from satellite imagery, and a model of plastic waste transport to the ocean that uses information on topography, seasonal rainfall, drainage to rivers, and river transport to the ocean. For cleanup, the results for West Africa assign the highest locational priority to areas with heavy plastic-waste disposal along river channels or in steeply sloped locations with high rainfall runoff potential near rivers. They assign the highest temporal priority to just before the onset of the first-semester rainy season, when runoff from the first rains transports large volumes of plastic waste that have accumulated during the dry season. Numéro de notice : A2022-471 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scitotenv.2022.156319 Date de publication en ligne : 28/05/2022 En ligne : https://doi.org/10.1016/j.scitotenv.2022.156319 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100816
in Science of the total environment > vol 839 (May 2022) . - n° 156319[article]The role of blue green infrastructure in the urban thermal environment across seasons and local climate zones in East Africa / Xueqin Li in Sustainable Cities and Society, vol 80 (May 2022)PermalinkDetecting and mapping drought severity using multi-temporal Landsat data in the uMsinga region of KwaZulu-Natal, South Africa / Shenelle Lottering in Geocarto international, vol 37 n° 6 ([01/04/2022])PermalinkFlood mapping using multi-temporal Sentinel-1 SAR images: A case study—Inaouene watershed from Northeast of Morocco / Brahim Benzougagh in Iranian Journal of Science and Technology - Transactions of Civil Engineering, vol 46 n° 2 (April 2022)PermalinkFeasibility of mapping radioactive minerals in high background radiation areas using remote sensing techniques / J.O. Ondieki in International journal of applied Earth observation and geoinformation, vol 107 (March 2022)PermalinkInfluence of determinant factors towards soil erosion using ordinary least squared regression in GIS domain / Imran Ahmad in Applied geomatics, vol 14 n° 1 (March 2022)PermalinkAssessment and mapping soil water erosion using RUSLE approach and GIS tools: Case of Oued el-Hai watershed, Aurès West, Northeastern of Algeria / Aida Bensekhria in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)PermalinkMulti-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana / Ram Avtar in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkUse of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa / Mangana Rampheri in Geocarto international, vol 37 n° 2 ([15/01/2022])Permalink3D stem modelling in tropical forest: towards improved biomass and biomass change estimates / Sébastien Bauwens (2022)PermalinkAn assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 / Darius Phiri in Geomatics, Natural Hazards and Risk, vol 13 (2022)Permalink