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An exploratory analysis of usability of Flickr tags for land use/land cover attribution / Yingwei Yan in Geo-spatial Information Science, vol 22 n° 1 (March 2019)  

Public [article]  inGeo-spatial Information Science > vol 22 n° 1 (March 2019) . - pp 12 - 22 Titre : An exploratory analysis of usability of Flickr tags for land use/land cover attribution Type de document : Article/Communication Auteurs : Yingwei Yan, Auteur ; Michael Schultz, Auteur ; Alexander Zipf, Auteur Année de publication : 2019 Article en page(s) : pp 12 - 22 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] analyse sémantique [Termes descripteurs IGN] contenu généré par les utilisateurs [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] étiquetage sémantique [Termes descripteurs IGN] image Flickr [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] San Diego Résumé : (Auteur) This study explored the land use/land cover (LULC) separability by the machine-generated and user-generated Flickr photo tags (i.e. the auto-tags and the user-tags, respectively), based on an authoritative LULC dataset for San Diego County in the United States. Ten types of LULCs were derived from the authoritative dataset. It was observed that certain types of the reclassified LULCs had abundant tags (e.g. the parks) or a high tag density (e.g. the commercial lands), compared with the less populated ones (e.g. the agricultural lands). Certain highly weighted terms of the tags derived based on a term frequency–inverse document frequency weighting scheme were helpful for identifying specific types of the LULCs, especially for the commercial recreation lands (e.g. the zoos). However, given the 10 sets of tags retrieved from the corresponding 10 types of LULCs, one set of tags (all the tags located at one specific type of the LULCs) could not fully delineate the corresponding LULC due to semantic overlaps, according to a latent semantic analysis. Numéro de notice : A2019-241 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2018.1560044 date de publication en ligne : 08/01/2019 En ligne : https://doi.org/10.1080/10095020.2018.1560044 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92934 [article]

Using LiDAR to develop high-resolution reference models of forest structure and spatial pattern / Haley L. Wiggins in Forest ecology and management, vol 434 (28 February 2019)  

Public [article]  inForest ecology and management > vol 434 (28 February 2019) . - pp 318 - 330 Titre : Using LiDAR to develop high-resolution reference models of forest structure and spatial pattern Type de document : Article/Communication Auteurs : Haley L. Wiggins, Auteur ; Cara R. Nelson, Auteur ; Andrew J. Larson, Auteur ; Hugh D. Safford, Auteur Année de publication : 2019 Article en page(s) : pp 318 - 330 Note générale : bibliography Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] Californie (Etats-Unis) [Termes descripteurs IGN] caractérisation [Termes descripteurs IGN] coupe (sylviculture) [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] Mexique [Termes descripteurs IGN] parc naturel national [Termes descripteurs IGN] restauration écologique [Termes descripteurs IGN] structure d'un peuplement forestier [Termes descripteurs IGN] topographie locale Résumé : (auteur) Successful restoration of degraded forest landscapes requires reference models that adequately capture structural heterogeneity at multiple spatial scales and for specific landforms. Despite this need, managers often lack access to reliable reference information, in large part because field-based methods for assessing variation in forest structure are costly and inherently suffer from limited replication and spatial coverage and, therefore, yield limited insights about the ecological structure of reference forests at landscape scales. LiDAR is a cost-effective alternative that can provide high-resolution characterizations of variation in forest structure among landform types. However, managers and researchers have been reluctant to use LiDAR for characterizing structure because of low confidence in its capacity to approximate actual tree distributions. By calculating bias in LiDAR estimates for a range of tree-height cutoffs, we improved LiDAR’s ability to capture structural variability in terms of individual trees. We assessed bias in the processed LiDAR data by comparing datasets of field-measured and LiDAR-detected trees of various height classes in terms of overall number of trees and estimates of structure and spatial pattern in an important contemporary reference forest, the Sierra de San Pedro Martir National Park, Baja California, Mexico. Agreement between LiDAR- and field-based estimates of tree density, as well as estimates of forest structure and spatial pattern, was maximized by removing trees less than 12 m tall. We applied this height cutoff to LiDAR-detected trees of our study landscape, and asked if forest structure and spatial pattern varied across topographic settings. We found that canyons, shallow northerly, and shallow southerly slopes were structurally similar; each had a greater number of all trees, large trees, and large tree clumps than steep southerly slopes and ridges. Steep northerly slopes supported unique structures, with taller trees than ridges and shorter trees than canyons and shallow southerly slopes. Our results show that characterizations of forest structure based on LiDAR-detected trees are reasonably accurate when the focus is narrowed to the overstory. In addition, our finding of strong variation of forest structure and spatial pattern across topographic settings demonstrates the importance of developing reference models at the landscape scale, and highlights the need for replicated sampling among stands and landforms. Methods developed here should be useful to managers interested in using LiDAR to characterize distributions of medium and large overstory trees, particularly for the development of landscape-scale reference models. Numéro de notice : A2019-013 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.12.012 date de publication en ligne : 24/12/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.12.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91616 [article]

Exploring uncertainties in terrain feature extraction across multi-scale, multi-feature, and multi-method approaches for variable terrain / Boleslo E. Romero in Cartography and Geographic Information Science, Vol 45 n° 5 (August 2018)  

Public [article]  inCartography and Geographic Information Science > Vol 45 n° 5 (August 2018) . - pp 381 - 399 Titre : Exploring uncertainties in terrain feature extraction across multi-scale, multi-feature, and multi-method approaches for variable terrain Type de document : Article/Communication Auteurs : Boleslo E. Romero, Auteur ; Keith C. Clarke, Auteur Année de publication : 2018 Article en page(s) : pp 381 - 399 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] Californie (Etats-Unis) [Termes descripteurs IGN] crète (ligne) [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] géomorphométrie [Termes descripteurs IGN] incertitude géométrique [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] réseau hydrographique [Termes descripteurs IGN] talweg Résumé : (Auteur) Terrain analysis uses different workflows to extract features from terrain models for the purpose of understanding topographic patterns and processes. However, the results of different workflows often conflict, leading to uncertainties about feature locations. Instead of relying upon a single workflow, we suggest that a fusion of information from multiple workflows better informs terrain analysis. From terrain data with different degrees of variability, we extracted terrain features related to the set of topographic surface network feature classes {peaks, pits, saddles, ridges, courses} using workflows from free, open-source, and commercial software. A multi-scale analysis produced terrain features with fuzzy membership values for various feature classes and revealed that terrain locations can exhibit characteristics of all classes. Multi-feature maps were created by determining at each location the dominant and second-ranked features, and an uncertainty value. Our multi-method approach incorporated all of the workflows’ multi-scale results and again produced multi-feature maps that increased the confidence of some features and reduced the signal of dissimilar results. We also found that high variability terrain produced crisper features in both spatial extent and membership strength. Our overall conclusion is that multi-scale, multi-feature, and multi-method analyses clarify terrain feature uncertainty. Numéro de notice : A2018-259 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1335235 date de publication en ligne : 18/07/2017 En ligne : https://doi.org/10.1080/15230406.2017.1335235 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90332 [article]

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Exploring geo-tagged photos for land cover validation with deep learning / Hanfa Xing in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 141 (July 2018) . - pp 237 - 251 Titre : Exploring geo-tagged photos for land cover validation with deep learning Type de document : Article/Communication Auteurs : Hanfa Xing, Auteur ; Yuan Meng, Auteur ; Zixuan Wang, Auteur ; Kaixuan Fan, Auteur ; Dongyang Hou, Auteur Année de publication : 2018 Article en page(s) : pp 237 - 251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] base de données d'occupation du sol [Termes descripteurs IGN] Californie (Etats-Unis) [Termes descripteurs IGN] échantillon [Termes descripteurs IGN] estimation de précision [Termes descripteurs IGN] géoétiquetage [Termes descripteurs IGN] image numérique [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] production participative [Termes descripteurs IGN] réseau neuronal convolutif Résumé : (Auteur) Land cover validation plays an important role in the process of generating and distributing land cover thematic maps, which is usually implemented by high cost of sample interpretation with remotely sensed images or field survey. With an increasing availability of geo-tagged landscape photos, the automatic photo recognition methodologies, e.g., deep learning, can be effectively utilised for land cover applications. However, they have hardly been utilised in validation processes, as challenges remain in sample selection and classification for highly heterogeneous photos. This study proposed an approach to employ geo-tagged photos for land cover validation by using the deep learning technology. The approach first identified photos automatically based on the VGG-16 network. Then, samples for validation were selected and further classified by considering photos distribution and classification probabilities. The implementations were conducted for the validation of the GlobeLand30 land cover product in a heterogeneous area, western California. Experimental results represented promises in land cover validation, given that GlobeLand30 showed an overall accuracy of 83.80% with classified samples, which was close to the validation result of 80.45% based on visual interpretation. Additionally, the performances of deep learning based on ResNet-50 and AlexNet were also quantified, revealing no substantial differences in final validation results. The proposed approach ensures geo-tagged photo quality, and supports the sample classification strategy by considering photo distribution, with accuracy improvement from 72.07% to 79.33% compared with solely considering the single nearest photo. Consequently, the presented approach proves the feasibility of deep learning technology on land cover information identification of geo-tagged photos, and has a great potential to support and improve the efficiency of land cover validation. Numéro de notice : A2018-289 Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.025 date de publication en ligne : 16/05/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.025 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90404 [article]

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Manipulating tree crown structure to promote old-growth characteristics in second-growth redwood forest canopies / Stephen C. Sillett in Forest ecology and management, vol 417 (15 May 2018)  

Public [article]  inForest ecology and management > vol 417 (15 May 2018) . - pp 77 - 89 Titre : Manipulating tree crown structure to promote old-growth characteristics in second-growth redwood forest canopies Type de document : Article/Communication Auteurs : Stephen C. Sillett, Auteur ; Marie E. Antoine, Auteur ; Jim Campbell-Spickler, Auteur ; Allyson L. Carroll, Auteur ; Ethan J. Coonen, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 77 - 89 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes descripteurs IGN] Californie (Etats-Unis) [Termes descripteurs IGN] canopée [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] élagage (sylviculture) [Termes descripteurs IGN] houppier [Termes descripteurs IGN] Sequoia sempervirens Résumé : (Auteur) In old-growth Sequoia sempervirens forests, reiterated trunks and limbs provide required habitat elements for specialized arboreal species, including an endangered seabird, Brachyramphus marmoratus. The oldest second-growth redwood forests—established after 19th century logging—lack species dependent on complex structure, presumably because redwoods maintain simple, model-conforming crowns for centuries unless damaged by wind or fire. We imposed a factorial experiment on 24 redwoods 59–75 m tall in six second-growth forests to determine if trunk reiteration and limb formation can be induced by removing treetops (topping) and branch tips (tipping) to disrupt apical control. We also increased light availability in the upper crown by pruning branches. After intensively mapping trunks and branches and imposing treatments, we re-mapped trees three years later to quantify growth increments. Topping stimulated trunk reiteration from the cut, and reiterated tops gained height more rapidly than controls. Tipping also stimulated trunk reiteration from branches, especially when combined with topping, resulting in formation of limbs (i.e., branches giving rise to reiterated trunks). Pruning had consistently negative effects on trunk and branch growth increments even after accounting for post-treatment variation in leaf area and light availability, suggesting that photosynthate was diverted to compartmentalization of wounds. Strategic injury of trees may have long-term conservation value in second-growth redwood forests if limbs can be initiated high enough in the crown to persist as trees approach maximum height. Topping and tipping treatments should be combined with silvicultural thinning of neighboring trees to increase light availability far more than can be achieved by pruning. Numéro de notice : A2018-469 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.02.036 date de publication en ligne : 08/03/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.02.036 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91150 [article]

From Google Maps to a fine-grained catalog of street trees / Steve Branson in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)  

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HERA: A dynamic web application for visualizing community exposure to flood hazards based on storm and sea level rise scenarios / Jeanne M. Jones in Computers & geosciences, vol 109 (December 2017)  

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Safe separation distance score : a new metric for evaluating wildland firefighter safety zones using lidar / Michael J. Campbell in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)  

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An individual tree-based automated registration of aerial images to LiDAR Data in a forested area / Jun-Hak Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 9 (September 2016)  

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Mapping of land cover in northern California with simulated hyperspectral satellite imagery / Matthew L. Clark in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)  

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Use of a GPS-derived troposphere model to improve InSAR deformation estimates in the San Gabriel Valley, California / Nicolas Houlié in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)  

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Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery / Mary Pyott Freeman in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)  

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Automatic detection and reconstruction of 2-D/3-D building shapes from spaceborne TomoSAR point clouds / Muhammad Shahzad in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)  

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Estimating spatial efficiency using cyber search, GIS, and spatial optimization: a case study of fire service deployment in Los Angeles County / R.L. Church in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)  

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A parallel algorithm for coverage optimization on multi-core architectures / Ran Wei in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)  

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