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Fully convolutional neural network for impervious surface segmentation in mixed urban environment / Joseph McGlinchy in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (February 2021)
[article]
Titre : Fully convolutional neural network for impervious surface segmentation in mixed urban environment Type de document : Article/Communication Auteurs : Joseph McGlinchy, Auteur ; Brian Muller, Auteur ; Brian Johnson, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 117 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] croissance urbaine
[Termes IGN] Denver
[Termes IGN] exactitude des données
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] milieu urbain
[Termes IGN] segmentation
[Termes IGN] surface imperméableRésumé : (Auteur) The urgency of creating appropriate, high-resolution data products such as impervious cover information has increased as cities face rapid growth as well as climate change and other environmental challenges. This work explores the use of fully convolutional neural networks (FCNNs )—specifically UNet with a ResNet-152 encoder—in mapping impervious surfaces at the pixel level from WorldView-2 in a mixed urban/residential environment. We investigate three-, four-, and eight-band multispectral inputs to the FCNN. Resulting maps are promising in both qualitative and quantitative assessment when compared to automated land use/land cover products. Accuracy was assessed by F1 and average precision (AP) scores, as well as receiver operating characteristic curves, with area under the curve (AUC ) used as an additional accuracy metric. The four-band model shows the highest average test-set accuracies (F1, AP, and AUC of 0.709, 0.82, and 0.807, respectively), with higher AP and AUC than the automated land use/land cover products, indicating the utility of the blue-green-red-infrared channels for the FCNN. Improved performance was seen in residential areas, with worse performance in more densely developed areas. Numéro de notice : A2021-099 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.2.117 Date de publication en ligne : 01/02/2021 En ligne : https://doi.org/10.14358/PERS.87.2.117 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97045
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 2 (February 2021) . - pp 117 - 123[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021021 SL Revue Centre de documentation Revues en salle Disponible Joint promotion partner recommendation systems using data from location-based social networks / Yi-Chung Chen in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)
[article]
Titre : Joint promotion partner recommendation systems using data from location-based social networks Type de document : Article/Communication Auteurs : Yi-Chung Chen, Auteur ; Hsi-Ho Huang, Auteur ; Sheng-Min Chiu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 57 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] Facebook
[Termes IGN] Foursquare
[Termes IGN] géomercatique
[Termes IGN] New York (Etats-Unis ; ville)
[Termes IGN] point d'intérêt
[Termes IGN] politique commerciale
[Termes IGN] réseau social géodépendantRésumé : (auteur) Joint promotion is a valuable business strategy that enables companies to attract more customers at lower operational cost. However, finding a suitable partner can be extremely difficult. Conventionally, one of the most common approaches is to conduct survey-based analysis; however, this method can be unreliable as well as time-consuming, considering that there are likely to be thousands of potential partners in a city. This article proposes a framework to recommend Joint Promotion Partners using location-based social networks (LBSN) data. We considered six factors in determining the suitability of a partner (customer base, association, rating and awareness, prices and star ratings, distance, and promotional strategy) and developed efficient algorithms to perform the required calculations. The effectiveness and efficiency of our algorithms were verified using the Foursquare dataset and real-life case studies. Numéro de notice : A2021-152 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10020057 Date de publication en ligne : 30/01/2021 En ligne : https://doi.org/10.3390/ijgi10020057 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97063
in ISPRS International journal of geo-information > vol 10 n° 2 (February 2021) . - n° 57[article]Modeling land use change and forest carbon stock changes in temperate forests in the United States / Lucia Fitts in Carbon Balance and Management, vol 16 ([01/02/2021])
[article]
Titre : Modeling land use change and forest carbon stock changes in temperate forests in the United States Type de document : Article/Communication Auteurs : Lucia Fitts, Auteur ; Matthew B. Russell, Auteur ; Grant M. Domke, Auteur ; Joseph F. Knight, Auteur Année de publication : 2021 Article en page(s) : n° 20 (2021) Langues : Anglais (eng) Descripteur : [Termes IGN] changement d'occupation du sol
[Termes IGN] Colorado (Etats-Unis)
[Termes IGN] forêt tempérée
[Termes IGN] Géorgie (Etats-Unis)
[Termes IGN] impact sur l'environnement
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] New York (Etats-Unis ; état)
[Termes IGN] puits de carbone
[Termes IGN] Texas (Etats-Unis)
[Termes IGN] Wisconsin (Etats-Unis)
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Background : Forests provide the largest terrestrial sink of carbon (C). However, these C stocks are threatened by forest land conversion. Land use change has global impacts and is a critical component when studying C fluxes, but it is not always fully considered in C accounting despite being a major contributor to emissions. An urgent need exists among decision-makers to identify the likelihood of forest conversion to other land uses and factors affecting C loss. To help address this issue, we conducted our research in California, Colorado, Georgia, New York, Texas, and Wisconsin. The objectives were to (1) model the probability of forest conversion and C stocks dynamics using USDA Forest Service Forest Inventory and Analysis (FIA) data and (2) create wall-to-wall maps showing estimates of the risk of areas to convert from forest to non-forest. We used two modeling approaches: a machine learning algorithm (random forest) and generalized mixed-effects models. Explanatory variables for the models included ecological attributes, topography, census data, forest disturbances, and forest conditions. Model predictions and Landsat spectral information were used to produce wall-to-wall probability maps of forest change using Google Earth Engine.
Results : During the study period (2000–2017), 3.4% of the analyzed FIA plots transitioned from forest to mixed or non-forested conditions. Results indicate that the change in land use from forests is more likely with increasing human population and housing growth rates. Furthermore, non-public forests showed a higher probability of forest change compared to public forests. Areas closer to cities and coastal areas showed a higher risk of transition to non-forests. Out of the six states analyzed, Colorado had the highest risk of conversion and the largest amount of aboveground C lost. Natural forest disturbances were not a major predictor of land use change.
Conclusions : Land use change is accelerating globally, causing a large increase in C emissions. Our results will help policy-makers prioritize forest management activities and land use planning by providing a quantitative framework that can enhance forest health and productivity. This work will also inform climate change mitigation strategies by understanding the role that land use change plays in C emissions.Numéro de notice : A2021-501 Affiliation des auteurs : non IGN Thématique : FORET/INFORMATIQUE Nature : Article DOI : 10.1186/s13021-021-00183-6 Date de publication en ligne : 03/07/2021 En ligne : https://doi.org/10.1186/s13021-021-00183-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98099
in Carbon Balance and Management > vol 16 [01/02/2021] . - n° 20 (2021)[article]A regional spatiotemporal analysis of large magnitude snow avalanches using tree rings / Erich Peitzsch in Natural Hazards and Earth System Sciences, Vol 21 n° 2 (February 2021)
[article]
Titre : A regional spatiotemporal analysis of large magnitude snow avalanches using tree rings Type de document : Article/Communication Auteurs : Erich Peitzsch, Auteur ; Jordi Hendrikx, Auteur ; Daniel Stahle, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 533 - 557 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] avalanche
[Termes IGN] Canada
[Termes IGN] cerne
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] données topographiques
[Termes IGN] échantillonnage
[Termes IGN] Etats-Unis
[Termes IGN] géomorphologie locale
[Termes IGN] magnitude
[Termes IGN] montagneRésumé : (auteur) Snow avalanches affect transportation corridors and settlements worldwide. In many mountainous regions, robust records of avalanche frequency and magnitude are sparse or non-existent. However, dendrochronological methods can be used to fill this gap and infer historical avalanche patterns. In this study, we developed a tree-ring-based avalanche chronology for large magnitude avalanche events (size ≥∼D3) using dendrochronological techniques for a portion of the US northern Rocky Mountains. We used a strategic sampling design to examine avalanche activity through time and across nested spatial scales (i.e., from individual paths, four distinct subregions, and the region). We analyzed 673 samples in total from 647 suitable trees collected from 12 avalanche paths from which 2134 growth disturbances were identified over the years 1636 to 2017 CE. Using existing indexing approaches, we developed a regional avalanche activity index to discriminate avalanche events from noise in the tree-ring record. Large magnitude avalanches, common across the region, occurred in 30 individual years and exhibited a median return interval of approximately 3 years (mean = 5.21 years). The median large magnitude avalanche return interval (3–8 years) and the total number of avalanche years (12–18) varies throughout the four subregions, suggesting the important influence of local terrain and weather factors. We tested subsampling routines for regional representation, finding that sampling 8 random paths out of a total of 12 avalanche paths in the region captures up to 83 % of the regional chronology, whereas four paths capture only 43 % to 73 %. The greatest value probability of detection for any given path in our dataset is 40 %, suggesting that sampling a single path would capture no more than 40 % of the regional avalanche activity. Results emphasize the importance of sample size, scale, and spatial extent when attempting to derive a regional large magnitude avalanche event chronology from tree-ring records. Numéro de notice : A2021-169 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.5194/nhess-21-533-2021 Date de publication en ligne : 05/02/2021 En ligne : https://doi.org/10.5194/nhess-21-533-2021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97108
in Natural Hazards and Earth System Sciences > Vol 21 n° 2 (February 2021) . - pp 533 - 557[article]A spatiotemporal structural graph for characterizing land cover changes / Bin Wu in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)
[article]
Titre : A spatiotemporal structural graph for characterizing land cover changes Type de document : Article/Communication Auteurs : Bin Wu, Auteur ; Ballang Yu, Auteur ; Song Shu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 397 - 425 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] changement d'occupation du sol
[Termes IGN] changement temporel
[Termes IGN] graphe
[Termes IGN] New York (Etats-Unis ; état)
[Termes IGN] objet géographique
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) Characterizing landscape patterns and revealing their underlying processes are critical for studying climate change and environmental problems. Previous methods for mapping land cover changes largely focused on the classification of remote sensing images. Therefore, they could not provide information about the evolutionary process of land cover changes. In this paper, we developed a spatiotemporal structural graph (STSG) technique for a comprehensive analysis of land cover changes. First, a land cover neighborhood graph was generated for each snapshot to quantify the spatial relationship between adjacent land cover objects. Then, an object-based temporal tracking algorithm was designed to monitor the temporal changes between land cover objects over time. Finally, land cover evolutionary trajectories, pixel-level land cover change trajectories, and node-wise connectivity changes over time were characterized. We applied the proposed method to analyze land cover changes in Suffolk County, New York from 1996 to 2010. The results demonstrated that STSG can not only characterize and visualize detailed land cover changes spatially but also maintain the temporal sequence and relations of land cover objects in an integrated space-time environment. The proposed STSG provides a useful framework for analyzing land cover changes and can be adapted to characterize and quantify other spatiotemporal phenomena. Numéro de notice : A2021-041 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1778706 Date de publication en ligne : 16/06/2020 En ligne : https://doi.org/10.1080/13658816.2020.1778706 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96753
in International journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 397 - 425[article]Apport de la photogrammétrie satellite pour la modélisation du manteau neigeux / César Deschamps-Berger (2021)PermalinkAutomated detection of individual Juniper tree location and forest cover changes using Google Earth Engine / Sudeera Wickramarathna in Annals of forest research, vol 64 n° 1 (2021)PermalinkDeep learning for wildfire progression monitoring using SAR and optical satellite image time series / Puzhao Zhang (2021)PermalinkPermalinkInferencing hourly traffic volume using data-driven machine learning and graph theory / Zhiyan Yi in Computers, Environment and Urban Systems, vol 85 (January 2021)PermalinkLocal fuzzy geographically weighted clustering: a new method for geodemographic segmentation / George Grekousis in International journal of geographical information science IJGIS, vol 35 n° 1 (January 2021)PermalinkQuantification probabiliste des taux de déformation crustale par inversion bayésienne de données GPS / Colin Pagani (2021)PermalinkPermalinkSea level acceleration under the magnifier / Huseyin Baki Iz in Journal of geodetic science, vol 11 n° 1 (January 2021)PermalinkTopographic, edaphic and climate influences on aspen (Populus tremuloides) drought stress on an intermountain bunchgrass prairie / Andrew Neary in Forest ecology and management, vol 479 ([01/01/2021])Permalink