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Decolonizing world heritage maps using indigenous toponyms, stories, and interpretive attributes / Mark Palmer in Cartographica, vol 55 n° 3 (Fall 2020)
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Titre : Decolonizing world heritage maps using indigenous toponyms, stories, and interpretive attributes Type de document : Article/Communication Auteurs : Mark Palmer, Auteur ; Cadey Korson, Auteur Année de publication : 2020 Article en page(s) : pp 183 - 192 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie
[Termes IGN] Australie
[Termes IGN] Canada
[Termes IGN] carte administrative
[Termes IGN] Etats-Unis
[Termes IGN] ethnologie
[Termes IGN] histoire
[Termes IGN] Nouvelle-Zélande
[Termes IGN] patrimoine culturel
[Termes IGN] représentation géographique
[Termes IGN] système d'information géographique
[Termes IGN] toponymie localeRésumé : (auteur) Maps and GIS used for the nomination and subsequent management of UNESCO World Heritage sites have primarily served bureaucratic resource management purposes. However, bureaucratic maps offer an opportunity to represent associative cultural landscapes, intangible cultural elements, and the geographies of Indigenous peoples. Indigenous toponyms can be found on many World Heritage maps for sites located within settler societies such as New Zealand, Australia, the United States, and Canada. Currently, bureaucratic heritage maps do not emphasize or even have a method for presenting the meaning and significance of Indigenous toponyms. Instead, the names are represented as static, inanimate objects void of meaning. This article presents archival evidence that bureaucratic state maps found within some UNESCO World Heritage nomination dossiers and resource management plans contain Indigenous cartographic elements that Indigenous communities could use as the basis for creating Indigital story maps. Numéro de notice : A2020-604 Affiliation des auteurs : non IGN Thématique : TOPONYMIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2019-0014 Date de publication en ligne : 30/09/2020 En ligne : https://doi.org/10.3138/cart-2019-0014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95961
in Cartographica > vol 55 n° 3 (Fall 2020) . - pp 183 - 192[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 031-2020031 SL Revue Centre de documentation Revues en salle Disponible Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches / S.M. Hamylton in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)
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Titre : Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches Type de document : Article/Communication Auteurs : S.M. Hamylton, Auteur ; R.H. Morris, Auteur ; R.C. Carvalho, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102085 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] données de terrain
[Termes IGN] image captée par drone
[Termes IGN] Nouvelle-Galles du Sud
[Termes IGN] pesticide
[Termes IGN] réserve naturelle
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétationRésumé : (auteur) We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected. Numéro de notice : A2020-716 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102085 Date de publication en ligne : 03/03/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102085 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96287
in International journal of applied Earth observation and geoinformation > vol 89 (July 2020) . - n° 102085[article]Mapping the condition of macadamia tree crops using multi-spectral UAV and WorldView-3 imagery / Kasper Johansen in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)
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Titre : Mapping the condition of macadamia tree crops using multi-spectral UAV and WorldView-3 imagery Type de document : Article/Communication Auteurs : Kasper Johansen, Auteur ; Qibin Duan, Auteur ; Yu-Hsuan Tu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 28 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Australie
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données multitemporelles
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] production agricole végétale
[Termes IGN] surveillance de la végétationRésumé : (auteur) Australia is one of the world’s largest producers of macadamia nuts. As macadamia trees can take up to 15 years to mature and produce maximum yield, it is important to optimize tree condition. Field based assessment of macadamia tree condition is time-consuming and often inconsistent. Using remotely sensed imagery may allow for faster, more extensive, and more consistent assessment of macadamia tree condition. To identify individual macadamia tree crowns, high spatial resolution imagery is required. Hence, the objective of this work was to develop and test an approach to map the condition of individual macadamia tree crowns using both multi-spectral Unmanned Aerial Vehicle (UAV) and WorldView-3 imagery for different macadamia varieties and three different sites located near Bundaberg, Australia. A random forest classifier, based on all available spectral bands and selected vegetation indices was used to predict five condition categories, ranging from excellent (category 1) to poor (category 5). Various combinations of the developed models were tested between the three sites and over time. The results showed that the multi-spectral WorldView-3 imagery produced the lowest out of bag (OOB) classification errors in most cases. However, for both the UAV and the WorldView-3 imagery, more than 98.5% of predicted macadamia condition categories were either correctly mapped or offset by a single category out of the five condition categories (excellent, good, moderate, fair and poor) for trees of the same variety and at one point in time. Multi-temporally, the WorldView-3 imagery performed better than the UAV data for predicting the condition of the same macadamia tree variety. Applying a model from one site to another site with the same macadamia tree variety produced OOB classification between 31.20 and 42.74%, but with >98.63% of trees predicted within a single condition category. Importantly, models trained based on one type of macadamia tree variety could not be successfully applied to a site with another variety. The developed classification models may be used as a decision and management support tool for the macadamia industry to inform management practices and improve on-demand irrigation, fertilization, and pest inspection at the individual tree level. Numéro de notice : A2020-277 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.01 Date de publication en ligne : 20/05/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.017 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95093
in ISPRS Journal of photogrammetry and remote sensing > vol 165 (July 2020) . - pp 28 - 40[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020071 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020073 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020072 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Assessing environmental impacts of urban growth using remote sensing / John C. Trinder in Geo-spatial Information Science, vol 23 n° 1 (March 2020)
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Titre : Assessing environmental impacts of urban growth using remote sensing Type de document : Article/Communication Auteurs : John C. Trinder, Auteur ; Qingxiang Liu, Auteur Année de publication : 2020 Article en page(s) : pp 20 - 39 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] changement d'utilisation du sol
[Termes IGN] croissance urbaine
[Termes IGN] développement durable
[Termes IGN] image Landsat
[Termes IGN] impact sur l'environnement
[Termes IGN] réseau neuronal artificiel
[Termes IGN] service écosystémique
[Termes IGN] Sydney (Nouvelle-Galles du Sud)
[Termes IGN] Wuhan (Chine)Résumé : (auteur) This paper provides a study of the changes in land use in urban environments in two cities, Wuhan, China and western Sydney in Australia. Since mixed pixels are a characteristic of medium resolution images such as Landsat, when used for the classification of urban areas, due to changes in urban ground cover within a pixel, Multiple Endmember Spectral Mixture Analysis (MESMA) together with Super-Resolution Mapping (SRM) are employed to derive class fractions to generate classification maps at a higher spatial resolution using an Artificial Neural Network (ANN) predicted Wavelet method. Landsat images over the two cities for a 30-year period, are classified in terms of vegetation, buildings, soil and water. The classifications are then processed using Indifrag software to assess the levels of fragmentation caused by changes in the areas of buildings, vegetation, water and soil over the 30 years. The extents of fragmentation of vegetation, buildings, water and soil for the two cities are compared, while the percentages of vegetation are compared with recommended percentages of green space for urban areas for the benefit of health and well-being of inhabitants. Changes in Ecosystem Service Values (ESVs) resulting from the urbanization have been assessed for Wuhan and Sydney. The UN Sustainable Development Goals (SDG) for urban areas are being assessed by researchers to better understand how to achieve the sustainability of cities. Numéro de notice : A2020-162 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10095020.2019.1710438 Date de publication en ligne : 21/01/2020 En ligne : https://doi.org/10.1080/10095020.2019.1710438 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94822
in Geo-spatial Information Science > vol 23 n° 1 (March 2020) . - pp 20 - 39[article]Can Carbon Sequestration in Tasmanian “Wet” Eucalypt Forests Be Used to Mitigate Climate Change? Forest Succession, the Buffering Effects of Soils, and Landscape Processes Must Be Taken into Account / Peter D. McIntosh in International journal of forestry research, vol 2020 ([01/02/2020])
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Titre : Can Carbon Sequestration in Tasmanian “Wet” Eucalypt Forests Be Used to Mitigate Climate Change? Forest Succession, the Buffering Effects of Soils, and Landscape Processes Must Be Taken into Account Type de document : Article/Communication Auteurs : Peter D. McIntosh, Auteur ; James L. Hardcastle, Auteur ; Tobias Klöffe, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière
[Termes IGN] changement climatique
[Termes IGN] écosystème forestier
[Termes IGN] Eucalyptus (genre)
[Termes IGN] forêt équatoriale
[Termes IGN] matière organique
[Termes IGN] peuplement mélangé
[Termes IGN] puits de carbone
[Termes IGN] Tasmanie
[Termes IGN] zone humide
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Small areas of the wetter parts of southeast Australia including Tasmania support high-biomass “wet” eucalypt forests, including “mixed” forests consisting of mature eucalypts up to 100 m high with a rainforest understorey. In Tasmania, mixed forests transition to lower biomass rainforests over time. In the scientific and public debate on ways to mitigate climate change, these forests have received attention for their ability to store large amounts of carbon (C), but the contribution of soil C stocks to the total C in these two ecosystems has not been systematically researched, and consequently, the potential of wet eucalypt forests to serve as long-term C sinks is uncertain. This study compared soil C stocks to 1 m depth at paired sites under rainforest and mixed forests and found that there was no detectable difference of mean total soil C between the two forest types, and on average, both contained about 200 Mg·ha−1 of C. Some C in subsoil under rainforests is 3000 years old and retains a chemical signature of pyrogenic C, detectable in NMR spectra, indicating that soil C stocks are buffered against the effects of forest succession. The mean loss of C in biomass as mixed forests transition to rainforests is estimated to be about 260 Mg·ha−1 over a c. 400-year period, so the mature mixed forest ecosystem emits about 0.65 Mg·ha−1·yr−1 of C during its transition to rainforest. For this reason and because of the risk of forest fires, setting aside large areas of wet eucalypt forests as reserves in order to increase landscape C storage is not a sound strategy for long-term climate change mitigation. Maintaining a mosaic of managed native forests, including regenerating eucalypts, mixed forests, rainforests, and reserves, is likely to be the best strategy for maintaining landscape C stocks. Numéro de notice : A2020-627 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1155/2020/6509659 Date de publication en ligne : 30/07/2020 En ligne : https://doi.org/10.1155/2020/6509659 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96030
in International journal of forestry research > vol 2020 [01/02/2020] . - 16 p.[article]Computer vision-based framework for extracting tectonic lineaments from optical remote sensing data / Ehsan Farahbakhsh in International Journal of Remote Sensing IJRS, vol 41 n°5 (01 - 08 février 2020)PermalinkEstimating wheat yields in Australia using climate records, satellite image time series and machine learning methods / Elisa Kamir in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)PermalinkOptimising drone flight planning for measuring horticultural tree crop structure / Yu-Hsuan Tu in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)PermalinkDeep learning for multi-modal classification of cloud, shadow and land cover scenes in PlanetScope and Sentinel-2 imagery / Yuri Shendryk in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)PermalinkThe influence of sampling design on spatial data quality in a geographic citizen science project / Greg Brown in Transactions in GIS, Vol 23 n° 6 (November 2019)PermalinkUsing a U-net convolutional neural network to map woody vegetation extent from high resolution satellite imagery across Queensland, Australia / Neil Flood in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)PermalinkModelling discontinuous terrain from DSMs using segment labelling, outlier removal and thin-plate splines / Kassel Hingee in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)PermalinkSea level variation around Australia and its relation to climate indices / Armin Agha Karimi in Marine geodesy, vol 42 n° 5 (September 2019)PermalinkError propagation for the Molodensky G1 term / Jack C. McCubbine in Journal of geodesy, vol 93 n°6 (June 2019)PermalinkModelling the effects of fundamental UAV flight parameters on LiDAR point clouds to facilitate objectives-based planning / Jeremy J. Sofonia in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)Permalink