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An exploratory assessment of the effectiveness of geomasking methods on privacy protection and analytical accuracy for individual-level geospatial data / Jue Wang in Cartography and Geographic Information Science, Vol 49 n° 5 (September 2022)
[article]
Titre : An exploratory assessment of the effectiveness of geomasking methods on privacy protection and analytical accuracy for individual-level geospatial data Type de document : Article/Communication Auteurs : Jue Wang, Auteur ; Junghwan Kim, Auteur ; Mei-Po Kwan, Auteur Année de publication : 2022 Article en page(s) : pp 385 - 406 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse spatiale
[Termes IGN] confidentialité
[Termes IGN] données localisées
[Termes IGN] géomasquage
[Termes IGN] masque géographique
[Termes IGN] partage de données localisées
[Termes IGN] protection de la vie privéeRésumé : (auteur) The widespread use of personal geospatial data raises serious geoprivacy concerns for sharing these data, which may limit the reproducibility of research findings. One widely used method for securely sharing confidential geospatial information is applying geomasking techniques before sharing. Geomasking may reduce the usability of the data. Thus, researchers need to strike a balance between privacy protection and analytical accuracy. Although many geomasking methods have been proposed, there is no systematic evaluation of these methods or guidance on which method to use and how to apply it properly. To address this gap, we evaluate eight geomasking methods with simulated geospatial data with various spatial patterns and investigate their performance on privacy protection and analytical accuracy. We propose not only a set of preliminary guidelines for applying the proper geomasking methods when using different spatial analysis methods but also an evaluation framework for assessing geomasking methods for other spatial analysis methods. The findings will help researchers to properly apply geomasking for sensitive geospatial data and thus promote data sharing and interdisciplinary collaboration while protecting personal geoprivacy. Numéro de notice : A2022-632 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2022.2056510 En ligne : https://doi.org/10.1080/15230406.2022.2056510 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101397
in Cartography and Geographic Information Science > Vol 49 n° 5 (September 2022) . - pp 385 - 406[article]Benchmarking laser scanning and terrestrial photogrammetry to extract forest inventory parameters in a complex temperate forest / Daniel Kükenbrink in International journal of applied Earth observation and geoinformation, vol 113 (September 2022)
[article]
Titre : Benchmarking laser scanning and terrestrial photogrammetry to extract forest inventory parameters in a complex temperate forest Type de document : Article/Communication Auteurs : Daniel Kükenbrink, Auteur ; Mauro Marty, Auteur ; Ruedi Bösch, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102999 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] caméra à bas coût
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] détection d'arbres
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tempérée
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lidar mobile
[Termes IGN] lidar topographique
[Termes IGN] photogrammétrie terrestre
[Termes IGN] semis de points
[Termes IGN] série temporelle
[Termes IGN] structure-from-motion
[Termes IGN] Zurich (Suisse)Résumé : (auteur) National forest inventories (NFI) are important for the assessment of the state and development of forests. Traditional NFIs often rely on statistical sampling approaches as well as expert assessment which may suffer from observer bias and may lack robustness for time series analysis. Over the course of the last decade, close-range remote sensing techniques such as terrestrial and mobile laser scanning became ever more established for the assessment of three-dimensional (3D) forest structure. With the ongoing trend to make the systems smaller, easier to use and more efficient, the pathway is being opened for an operational inclusion of such devices within the framework of an NFI to support the traditional field assessment. Close-range remote sensing could potentially speed up field inventory work as well as increase the area in which certain parameters are assessed. Benchmarks are needed to evaluate the performance of different close-range remote sensing devices and approaches, both in terms of efficiency as well as accuracy. In this study we evaluate the performance of two terrestrial (TLS), one handheld mobile (PLS) and two drone based (UAVLS) laser scanning systems to detect trees and extract the diameter at breast height (DBH) in three plots with a steep gradient in tree and understorey vegetation density. As a novelty, we also tested the acquisition of 3D point-clouds using a low-cost action camera (GoPro) in conjunction with the Structure from Motion (SfM) technique and compared its performance with those of the more costly LiDAR devices. Among the many parameters evaluated in traditional NFIs, the focus of the performance evaluation of this study is set on the automatic tree detection and DBH extraction. The results showed that TLS delivers the highest tree detection rate (TDR) of up to 94.6% under leaf-off and up to 82% under leaf-on conditions and a relative RMSE (rRMSE) for the DBH extraction between 2.5 and 9%, depending on the undergrowth complexity. The tested PLS system (leaf-on) achieved a TDR of up to 80% with an rRMSE between 3.7 and 5.8%. The tested UAVLS systems showed lowest TDR of less than 77% under leaf-off and less than 37% under leaf-on conditions. The novel GoPro approach achieved a TDR of up to 53% under leaf-on conditions. The reduced TDR can be explained by the reduced area coverage due to the chosen circular acquisition path taken with the GoPro approach. The DBH extraction performance on the other hand is comparable to those of the LiDAR devices with an rRMSE between 2 and 9%. Further benchmarks are needed in order to fully assess the applicability of these systems in the framework of an NFI. Especially the robustness under varying forest conditions (seasonality) and over a broader range of forest types and canopy structure has to be evaluated. Numéro de notice : A2022-787 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102999 Date de publication en ligne : 05/09/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102999 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101893
in International journal of applied Earth observation and geoinformation > vol 113 (September 2022) . - n° 102999[article]Estimating carbon stocks and biomass expansion factors of urban greening trees using terrestrial laser scanning / Linlin Wu in Forests, vol 13 n° 9 (september 2022)
[article]
Titre : Estimating carbon stocks and biomass expansion factors of urban greening trees using terrestrial laser scanning Type de document : Article/Communication Auteurs : Linlin Wu, Auteur ; Yongjun Shi, Auteur ; Fanyi Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1389 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse forestière
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt urbaine
[Termes IGN] houppier
[Termes IGN] puits de carbone
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestre
[Termes IGN] volume en boisRésumé : (auteur) Urban forest carbon sequestration represents an important component of the global forest carbon pool; however, accurate measurements are limited by the inability of existing field stand models to match the specificity of urban greening species. Herein, canopy volume, carbon stock, and the biomass expansion factor (BEF) of 30 Koelreuteria paniculate trees were measured based on terrestrial laser scanning (TLS) and compared to the results of existing wood volume and carbon stock model measurements. The findings revealed that (1) TLS point cloud data were highly reproducible and accurate (root mean square error of tree height and diameter at breast height were ±0.35 m and ±0.33 cm, respectively). (2) Owing to human interference and cluttered urban environments, the BEF of urban greening tree species fluctuated irregularly, considerably different from that of natural forest stands. (3) Leaf carbon stocks were influenced by the size of the voxel. (4) Different tree measurement factors maintained variable degrees of influence on BEF (height under branch, volume of thick branch, crown width, and projected areas of tree-crown produced correlation coefficients of −0.64, 0.54, 0.45, and 0.43, respectively). Accordingly, the carbon stock and BEF of urban greening tree species can be accurately calculated via TLS without damage. Numéro de notice : A2022-755 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13091389 Date de publication en ligne : 31/08/2022 En ligne : https://doi.org/10.3390/f13091389 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101758
in Forests > vol 13 n° 9 (september 2022) . - n° 1389[article]Geoscience Knowledge Graph (GeoKG): Development, construction and challenges / Xueying Zhang in Transactions in GIS, vol 26 n° 6 (September 2022)
[article]
Titre : Geoscience Knowledge Graph (GeoKG): Development, construction and challenges Type de document : Article/Communication Auteurs : Xueying Zhang, Auteur ; Yi Huang, Auteur ; Chunju Zhang, Auteur ; Peng Ye, Auteur Année de publication : 2022 Article en page(s) : pp 2480 - 2494 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] corrélation
[Termes IGN] données localisées numériques
[Termes IGN] représentation des connaissances
[Termes IGN] réseau sémantiqueRésumé : (auteur) Big earth data is a cross-domain of geoscience and information science, which provides a novel perspective for solving geoscience problems. Most contemporary research is driven by data but neglect the potential value of knowledge. As a new scientific language in Geoscience, GeoKG is essential for understanding, representing, and mining geoscience knowledge, and can contribute to the integration of big earth data, geoscience knowledge, and geoscience models. However, research on GeoKG lack spatiotemporal perspectives in knowledge cognition, representation, acquisition and management. To this end, this article first outlines a cognitive mechanism from the human–machine double perspective and categorizes the characteristics and content of geoscience knowledge. To express evolution and complex natural rules, a knowledge representation framework is proposed through ‘state-process’ and ‘condition-result’ models. Aiming at multimodal data, a workflow is put forward to acquire knowledge from a small sample, a knowledge graph, a map, and a schematic diagram. Furthermore, we discuss the organization of GeoKG by improving existing data models, developing spatiotemporal correlation indexing and advancing knowledge graph completion. The concrete construction process of GeoKG is analyzed thoroughly in this study, which can support the synthetic analysis of big earth data, promote the development of knowledge engineering and provide a foundation for improving intelligent geoscience. Numéro de notice : A2022-949 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1111/tgis.12985 En ligne : https://doi.org/10.1111/tgis.12985 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102142
in Transactions in GIS > vol 26 n° 6 (September 2022) . - pp 2480 - 2494[article]A multi-source spatio-temporal data cube for large-scale geospatial analysis / Fan Gao in International journal of geographical information science IJGIS, vol 36 n° 9 (September 2022)
[article]
Titre : A multi-source spatio-temporal data cube for large-scale geospatial analysis Type de document : Article/Communication Auteurs : Fan Gao, Auteur ; Peng Yue, Auteur ; Zhipeng Cao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1853 - 1884 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] cube espace-temps
[Termes IGN] cyberinfrastructure
[Termes IGN] données spatiotemporelles
[Termes IGN] Géocube
[Termes IGN] hypercube
[Termes IGN] informatique en nuage
[Termes IGN] intelligence artificielle
[Termes IGN] observation de la TerreRésumé : (auteur) Data management and analysis are challenging with big Earth observation (EO) data. Expanding upon the rising promises of data cubes for analysis-ready big EO data, we propose a new geospatial infrastructure layered over a data cube to facilitate big EO data management and analysis. Compared to previous work on data cubes, the proposed infrastructure, GeoCube, extends the capacity of data cubes to multi-source big vector and raster data. GeoCube is developed in terms of three major efforts: formalize cube dimensions for multi-source geospatial data, process geospatial data query along these dimensions, and organize cube data for high-performance geoprocessing. This strategy improves EO data cube management and keeps connections with the business intelligence cube, which provides supplementary information for EO data cube processing. The paper highlights the major efforts and key research contributions to online analytical processing for dimension formalization, distributed cube objects for tiles, and artificial intelligence enabled prediction of computational intensity for data cube processing. Case studies with data from Landsat, Gaofen, and OpenStreetMap demonstrate the capabilities and applicability of the proposed infrastructure. Numéro de notice : A2022-643 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2087222 Date de publication en ligne : 14/06/2022 En ligne : https://doi.org/10.1080/13658816.2022.2087222 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101458
in International journal of geographical information science IJGIS > vol 36 n° 9 (September 2022) . - pp 1853 - 1884[article]Réservation
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