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Classification of hyperspectral and LiDAR data using coupled CNNs / Renlong Hang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)
[article]
Titre : Classification of hyperspectral and LiDAR data using coupled CNNs Type de document : Article/Communication Auteurs : Renlong Hang, Auteur ; Zhu Li, Auteur ; Pedram Ghamisi, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 4939 - 4950 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données hétérogènes
[Termes IGN] données lidar
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion de données
[Termes IGN] Houston (Texas)
[Termes IGN] image hyperspectrale
[Termes IGN] occupation du sol
[Termes IGN] Perceptron multicouche
[Termes IGN] précision de la classification
[Termes IGN] semis de points
[Termes IGN] Trente
[Termes IGN] utilisation du solRésumé : (auteur) In this article, we propose an efficient and effective framework to fuse hyperspectral and light detection and ranging (LiDAR) data using two coupled convolutional neural networks (CNNs). One CNN is designed to learn spectral–spatial features from hyperspectral data, and the other one is used to capture the elevation information from LiDAR data. Both of them consist of three convolutional layers, and the last two convolutional layers are coupled together via a parameter-sharing strategy. In the fusion phase, feature-level and decision-level fusion methods are simultaneously used to integrate these heterogeneous features sufficiently. For the feature-level fusion, three different fusion strategies are evaluated, including the concatenation strategy, the maximization strategy, and the summation strategy. For the decision-level fusion, a weighted summation strategy is adopted, where the weights are determined by the classification accuracy of each output. The proposed model is evaluated on an urban data set acquired over Houston, USA, and a rural one captured over Trento, Italy. On the Houston data, our model can achieve a new record overall accuracy (OA) of 96.03%. On the Trento data, it achieves an OA of 99.12%. These results sufficiently certify the effectiveness of our proposed model. Numéro de notice : A2020-391 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2969024 Date de publication en ligne : 06/02/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2969024 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95374
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 7 (July 2020) . - pp 4939 - 4950[article]Regionalization of flood magnitudes using the ecological attributes of watersheds / Bahman Jabbarian Amiri in Geocarto international, vol 35 n° 9 ([01/07/2020])
[article]
Titre : Regionalization of flood magnitudes using the ecological attributes of watersheds Type de document : Article/Communication Auteurs : Bahman Jabbarian Amiri, Auteur ; Bahareh Baheri, Auteur ; Nicola Fohrer, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 917 - 933 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] bassin hydrographique
[Termes IGN] Caspienne, mer
[Termes IGN] crue
[Termes IGN] débit
[Termes IGN] estimation quantitative
[Termes IGN] humidité du sol
[Termes IGN] inondation
[Termes IGN] modèle de simulation
[Termes IGN] occupation du sol
[Termes IGN] prévention des risques
[Termes IGN] régionalisation (segmentation)
[Termes IGN] ressources en eau
[Termes IGN] utilisation du sol
[Termes IGN] zone inondableRésumé : (auteur) Estimating flood discharge at ungauged sites is a significant challenge facing water resources planners and engineers during the planning and design of hydraulic structures, managing flood prone zones, and operating artificial waterbodies. Developing more robust models to improve the reliability of flood discharge estimations is thus very useful. The role of ecological attributes including land use/land cover (LULC), hydrologic soil groups (HSG), and watershed physical characteristics (area, main stream length, average slope), and watershed shape coefficients (form, compactness, circularity, and elongation) in explaining the overall variation in flood magnitude in 39 watersheds, located in the southern basin of the Caspian Sea, was investigated. As the LULC and HSG were found to play a significant role in explaining total variation (40–89%) in flood magnitudes, their inclusion in the estimation of flood magnitudes can provide more reliable estimates of flood risk and magnitude. Numéro de notice : A2020-428 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1552321 Date de publication en ligne : 07/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1552321 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95494
in Geocarto international > vol 35 n° 9 [01/07/2020] . - pp 917 - 933[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020091 RAB Revue Centre de documentation En réserve L003 Disponible A simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques / Olutoyin Adeola Fashae in Geocarto international, vol 35 n° 9 ([01/07/2020])
[article]
Titre : A simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques Type de document : Article/Communication Auteurs : Olutoyin Adeola Fashae, Auteur ; Rotimi Oluseyi Obateru, Auteur ; Adeyemi Oludap Olusola, Auteur Année de publication : 2020 Article en page(s) : pp 954 - 975 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique subsaharienne
[Termes IGN] ArcGIS
[Termes IGN] bassin hydrographique
[Termes IGN] bilan hydrique
[Termes IGN] classification dirigée
[Termes IGN] image Landsat
[Termes IGN] modèle numérique de surface
[Termes IGN] planification urbaine
[Termes IGN] série temporelle
[Termes IGN] stress hydrique
[Termes IGN] système d'information géographique
[Termes IGN] télédétection
[Termes IGN] utilisation du sol
[Termes IGN] zone urbaineRésumé : (auteur) Across most urban centres, adequate supply of water becomes essential for the urban poor. Attempts at ensuring water availability has been formulated using standard water models. This study developed a water balance model using Remote Sensing and GIS techniques during periods of water surplus and deficit across pre-millennium (1996 – 2000) and the post-millennium (2010 – 2014) periods within an urbanized Sub-Saharan city. Digital Elevation Model of the basin was prepared to generate flow direction and to delimit the watershed using ArcHydro tools in ArcGIS 10.3. Supervised classification was used to delineate the landuse classes from Landsat imageries. The result revealed that 1996, 1997, 1998, 2000, 2010 and 2013 were periods of water deficit, while 1999, 2011, 2012 and 2014 were periods of water surplus. This study affirmed the need to reactivate institutional frameworks that are responsible for assessment, conservation, management and planning of water resources for sustainable utilization. Numéro de notice : A2020-399 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1557261 Date de publication en ligne : 21/03/2019 En ligne : https://doi.org/10.1080/10106049.2018.1557261 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95435
in Geocarto international > vol 35 n° 9 [01/07/2020] . - pp 954 - 975[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020091 RAB Revue Centre de documentation En réserve L003 Disponible 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]Combining radar and optical imagery to map oil palm plantations in Sumatra, Indonesia, using the Google Earth Engine / Thuan Sarzynski in Remote sensing, vol 12 n° 7 (April 2020)
[article]
Titre : Combining radar and optical imagery to map oil palm plantations in Sumatra, Indonesia, using the Google Earth Engine Type de document : Article/Communication Auteurs : Thuan Sarzynski, Auteur ; Xingli Giam, Auteur ; Luis Carrasco, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] Elaeis guineensis
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat
[Termes IGN] image radar moirée
[Termes IGN] occupation du sol
[Termes IGN] Sumatra
[Termes IGN] surveillance agricole
[Termes IGN] utilisation du solRésumé : (auteur) Monitoring the expansion of commodity crops in the tropics is crucial to safeguard forests for biodiversity and ecosystem services. Oil palm (Elaeis guineensis) is one such crop that is a major driver of deforestation in Southeast Asia. We evaluated the use of a semi-automated approach with random forest as a classifier and combined optical and radar datasets to classify oil palm land-cover in 2015 in Sumatra, Indonesia, using Google Earth Engine. We compared our map with two existing remotely-sensed oil palm land-cover products that utilized visual and semi-automated approaches for the same year. We evaluated the accuracy of oil palm land-cover classification from optical (Landsat), radar (synthetic aperture radar (SAR)), and combined optical and radar satellite imagery (Combined). Combining Landsat and SAR data resulted in the highest overall classification accuracy (84%) and highest producer’s and user’s accuracy for oil palm classification (84% and 90%, respectively). The amount of oil palm land-cover in our Combined map was closer to official government statistics than the two existing land-cover products that used visual interpretation techniques. Our analysis of the extents of disagreement in oil palm land-cover indicated that our map had comparable accuracy to one of them and higher accuracy than the other. Our results demonstrate that a combination of optical and radar data outperforms the use of optical-only or radar-only datasets for oil palm classification and that our technique of preprocessing and classifying combined optical and radar data in the Google Earth Engine can be applied to accurately monitor oil-palm land-cover in Southeast Asia. Numéro de notice : A2020-455 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12071220 Date de publication en ligne : 10/04/2020 En ligne : https://doi.org/10.3390/rs12071220 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95554
in Remote sensing > vol 12 n° 7 (April 2020)[article]Size-class structure of the forests of Finland during 1921–2013: a recovery from centuries of exploitation, guided by forest policies / Helena M. Henttonen in European Journal of Forest Research, vol 139 n° 2 (April 2020)PermalinkComparison of spatial modelling approaches to simulate urban growth: a case study on Udaipur city, India / Biswajit Mondal in Geocarto international, vol 35 n° 4 ([15/03/2020])PermalinkLand use and land cover change modeling and future potential landscape risk assessment using Markov-CA model and analytical hierarchy process / Biswajit Nath in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)PermalinkPermalinkPermalinkA new cellular automata framework of urban growth modeling by incorporating statistical and heuristic methods / Yongjiu Feng in International journal of geographical information science IJGIS, vol 34 n° 1 (January 2020)PermalinkPermalinkPermalinkRevealing the Correlation between Population Density and the Spatial Distribution of Urban Public Service Facilities with Mobile Phone Data / Yi Shi in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)PermalinkSatellite image time series classification with pixel-set encoders and temporal self-attention / Vivien Sainte Fare Garnot (2020)Permalink