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Emergency management perspectives on volunteered geographic information: Opportunities, challenges and change / Billy Haworth in Computers, Environment and Urban Systems, vol 57 (May 2016)
[article]
Titre : Emergency management perspectives on volunteered geographic information: Opportunities, challenges and change Type de document : Article/Communication Auteurs : Billy Haworth, Auteur Année de publication : 2016 Article en page(s) : pp 189 - 198 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] Australie
[Termes IGN] citoyen
[Termes IGN] données localisées des bénévoles
[Termes IGN] données localisées numériques
[Termes IGN] gestion de crise
[Termes IGN] participation du public
[Termes IGN] risque naturelRésumé : (auteur) Volunteered geographic information (VGI) refers to the widespread creation and sharing of geographic information by private citizens, often through platforms such as online mapping tools, social media, and smartphone applications. VGI has shifted the ways information is created, shared, used and experienced, with important implications for applications of geospatial data, including emergency management. Detailed interviews with 13 emergency management professionals from eight organisations across five Australian states provided insights into the impacts of VGI on official emergency management. Perceived opportunities presented by VGI included improved communication, acquisition of diverse local information, and increased community engagement in disaster management. Identified challenges included the digital divide, data management, misinformation, and liability concerns. Significantly, VGI disrupts the traditional top-down structure of emergency management and reflects a culture shift away from authoritative control of information. To capitalise on the opportunities of VGI, agencies need to share responsibility and be willing to remain flexible in supporting positive community practises, including VGI. Given the high accountability and inherently responsive nature of decision making in disaster management, it provides a useful lens through which to examine the impacts of VGI on official authoritative systems more broadly. This analysis of the perceptions of emergency management professionals suggests changes to traditional systems that involve decentralisation of power and increased empowerment of citizens, where value is increasingly recognised in both expert and citizen-produced information, initiatives and practises. Numéro de notice : A2016-396 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2016.02.009 Date de publication en ligne : 07/03/2016 En ligne : https://doi.org/10.1016/j.compenvurbsys.2016.02.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81216
in Computers, Environment and Urban Systems > vol 57 (May 2016) . - pp 189 - 198[article]Surveying graffiti, an emerging culture / Anonyme in Position, n° 81 (February - March 2016)
[article]
Titre : Surveying graffiti, an emerging culture Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2016 Article en page(s) : pp 40 - 42 Langues : Anglais (eng) Descripteur : [Termes IGN] dessin
[Termes IGN] droit
[Termes IGN] espace public
[Termes IGN] Nouvelle-Galles du SudNuméro de notice : A2016-237 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80713
in Position > n° 81 (February - March 2016) . - pp 40 - 42[article]Assessment of forest canopy vertical structure with multi - scale remote sensing : from the plot to the large area / Phil Wilkes (2016)
Titre : Assessment of forest canopy vertical structure with multi - scale remote sensing : from the plot to the large area Type de document : Thèse/HDR Auteurs : Phil Wilkes, Auteur Editeur : Enschede [Pays Bas] : University of Twente Année de publication : 2016 Collection : ITC Dissertation num. 280 Importance : 180 p. ISBN/ISSN/EAN : 978-90-365-4038-4 Note générale : bibliographie
Dissertation to obtain the Double-Badged Degree of Doctor at the University of Twente, Enschede, The Netherlands; and RMIT University, Melbourne, AustraliaLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] ombre
[Termes IGN] placette d'échantillonnage
[Termes IGN] régression
[Termes IGN] semis de points
[Termes IGN] strate végétale
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] Victoria (Australie)Index. décimale : 33.80 Lasergrammétrie Résumé : (auteur) The attribution of forest structure forms an integral part of international monitoring and reporting obligations with regard to sustainable forest management. Furthermore, detailed information about forest structure allows land managers and forest scientists to determine a forests ability to provide ecosystems services. Currently, forest attribution is achieved using a network of forest inventory plots that are revisited periodically. This approach comprises a sparse sample, both temporally and spatially, that may not capture variance in forest structure. This is particularly true in dynamic native forests where variability in forest structure can be high. In recent years the capability of remote sensing techniques has been realised for sustainable forest management applications. Advantages of a remote sensing approach include synoptic and high temporal coverage as well as reduced costs to the end - user. Furthermore, recent advancement in active sensors, such as Light Detection and Ranging Instruments (LiDAR) have allowed for detailed three - dimensional forest measurement of structure across large areas.
This thesis presents new metrics, techniques and acquisition specifications for the attribution of forest canopy over large areas (e.g. comprising two or more forest types where forest structure maybe unknown a priori) using active and passive remote sensing. In particular, the focus is on attributes that quantify the vertical structure of forests; canopy height and canopy vertical structure. Canopy height is a commonly measured multipurpose attribute that is utilised, for example, to estimate biomass. Attribution of the canopy height profile, although less common, is important for mapping habitat suitability, biomass and fire susceptibility. Current techniques to attribute forests tend to be tailored to a particular forest type or location and therefore application of these models across large areas is unreliable. Here the aim is to develop metrics and techniques that are transferable between different forest types and applicable to forests where there is no prior knowledge of forest structure.
Here a multi - scale remote sensing approach was taken, where plot scale measurements were upscaled to attribute large areas. Initially, existing LiDAR derived metrics applicable at the plot scale were tested at three 5 km x 5 km study areas in Victoria, Australia where forests cover a broad range of structural types. Results indicate existing metrics of canopy height were applicable across the range of forest types, for example the 95 th percentile of LiDAR derived height estimated inventory measured canopy height with a RMSE of 12% (~5 m). An existing mixture modelling technique to attribute the canopy height profile was found unsuitable when applied across heterogeneously forested landscape. This was due to the inability to parameterise the model correctly without a priori knowledge of forest structure e.g. presence or absence of shade tolerant layers. For this reason a new technique was developed utilising a nonparametric regression of LiDAR derived gap probability that generalised the canopy profile. Taking the second derivative of the regression curve identified locations within the canopy that correspond with canopy strata, this therefore allowed a dynamic attribution of canopy vertical structure. Model output was validated with a crown volume modelling approach at 24 plots, where crown models were parameterised with inventory data and allometry. Results indicate this technique can estimate the number of canopy strata with a RMSE of 0. 41 strata. Furthermore, the new technique met the transferability criteria , as a universal regression coefficient was transferable between forest types with different structural attributes.
As LiDAR acquisition that cover large areas will inevitably encounter a range of forest types, parameters for attributing canopy structure that were transferable between forest types were investigated; in particular sampling frequency. To effectively assess a range of pulse densities would require repeat capture over a study area at a range of flying heights , which would be prohibitively expensive. For this reason a new technique was developed that systematically thinned point clouds. This technique differs from previous approaches by allowing simulation of multi - return instruments as well as repeat capture of the same plot. Six sites from around Australia were utilised which covered a broad range of forest types, from open savanna to tropical rainforest. For a suite of metrics, the ability of progressively less dense point clouds ( 4 – 0. 05 pl m - 2 ) to estimate canopy structure was estimated by comparison with higher density data (10 pl m - 2 ). Results indicate that canopy structure can be adequately attributed with data captured at 0.5 pl m - 2 . When pulse densities are Techniques derived at the plot scale were then applied to estimate canopy height across 2.9 million hectares of heterogeneous forest. Canopy height in the study area ranged from 0 – 70 m and comprised forest types from open woodland to tall closed canopy rainforest. LiDAR derived canopy height was used to t rain ensemble regression tree s (random forest) , where predictor datasets included synoptic passive optical imagery and other ancillary spatial datasets , such as Landsat TM and MODIS. Results suggest canopy height can be estimated with a RMSE of 30% (5.5 m) when validated with an independent inventory dataset. This is a similar error to that reported in previous studies for less complex forests and is within the European Space Agency target for canopy height estimation. However, model output did show a systematic error, where the height of short and tall forests were over and underestimated respectively. This was corrected by subtracting a model led estimate of error from the random forest output. Production of a canopy height map over a large area allowed for a consistent product that covered a broad range of forest types, derivation at a 30 m resolution allowed the identification of landscape features such as logging coupes. The presented technique utilised an open source computing framework as well as freely available predictor datasets to facilitate uptake of by land management agencies and forest scientists.Note de contenu : Chapter 1 : Introduction
1.1. General introduction
1.2. Problem statement
1.3. Research questions
1.4. Thesis structure
Chapter 2 : Metrics of canopy vertical structure suitable for large area forest attribution
2.1. Introduction
2.1.1. Canopy height
2.1.2. Canopy vertical structure
2.1.3. Aims and objectives
2.2. Materials and methods
2.2.1. Study area
2.2.2. Forest inventory data
2.2.3. Airborne laser scanning data
2.3. Data processing
2.3.1. Canopy height
2.3.2. Canopy vertical structure
2.4. Results
2.4.1. Canopy height
2.4.2. Canopy height profiles
2.5. Discussion
2.6. Conclusion
Chapter 3 : Using discrete-return ALS to quantify number of canopy strata across diverse forest types
3.1. Introduction
3.2. Attributing canopy vertical structure
3.3. Application across a diverse forested landscape
3.3.1. ALS acquisition and preprocessing
3.3.2. Pgap from ALS
3.3.3. Derivation of smoothing coefficient (α)
3.3.4. Bootstrapping simulated point clouds
3.3.5. Validation with field inventory
3.4. Results and Discussion
3.4.1. Methodology evaluation
3.4.2. Validation results
3.4.3. Canopy vertical structure as an independent metric
3.5. Conclusion
Chapter 4 : Understanding the effects of ALS pulse density for metric retrieval across diverse forest types
4.1. Introduction
4.2. Method
4.2.1. Study area and data capture
4.2.2. Data processing
4.2.3. Metrics
4.3. Results
4.3.1. Canopy height
4.3.2. Canopy cover
4.3.3. Canopy vertical structure
4.3.4. Characteristics of thinned point clouds
4.4. Discussion
4.5. Conclusion
Chapter 5 : Mapping forest canopy height across large areas by upscaling ALS estimates with freely available satellite data
5.1. Introduction
5.2. Materials and methods
5.3. Results
5.3.1. Canopy height estimation
5.3.2. Validation with inventory data
5.3.3. Training and validation of random forest using smaller geographic areas
5.3.4. Simulating disparate ALS capture for training a random forest
5.4. Discussion
5.5. Conclusions
Chapter 6 : Summary and synthesis
6.1. Summary of results
6.2. Identifying trends in large area forest structure
6.3. Remote sensing in sustainable forest management: a future perspectiveNuméro de notice : 17249 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : PhD thesis : Remote sensing : Twente : 2016 Organisme de stage : RMIT DOI : sans En ligne : http://www.itc.nl/library/papers_2016/phd/wilkes.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81928
[article]
Titre : Land [information system] Tasmania Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2015 Article en page(s) : pp 30 - 31 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] données ouvertes
[Termes IGN] TasmanieRésumé : (éditeur) The land Tasmania open data project is helping to spatially enable the Tasmanian community (cf www.thelist.tas.gov.au) Numéro de notice : A2015-951 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79828
in Position > n° 80 (December 2015 - January 2016) . - pp 30 - 31[article]Documents numériques
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Land [information system] TasmaniaAdobe Acrobat PDF Ocular robotics : The world's most dynamic eye / Ocular robotics in GIM international [en ligne], vol 29 n° 12 (December 2015)
[article]
Titre : Ocular robotics : The world's most dynamic eye Type de document : Article/Communication Auteurs : Ocular robotics, Auteur Année de publication : 2015 Article en page(s) : pp 30 - 31 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] Australie
[Termes IGN] capteur optique
[Termes IGN] instrument d'optique
[Termes IGN] robot mobile
[Termes IGN] télémètre laser terrestreRésumé : (auteur) Ocular Robotics is an Australia robotics company based in Sydney which designs, develops, manufactures and markets the world's most dynamic sensor platform: RobotEye. The simultaneous speed and precision delivered by the patented RobotEye platform enable the Ocular Robotics family of sensors to capture precisely registered data with unmatched speed. RobotEye drastically increases the operational performance, safety and efficiency of systems that rely on sensors in markets as diverse as robotics and automation, security and surveillance, aerospace and defence, mining and resources and precision agriculture. Numéro de notice : A2015-831 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79130
in GIM international [en ligne] > vol 29 n° 12 (December 2015) . - pp 30 - 31[article]Socio-economic benefits from protected areas in southeastern Australia / E.C. Heagney in Conservation biology, vol 29 n° 6 (December 2015)PermalinkDriving intelligent transport / Danielle Mulligan in Position, n° 79 (October - November 2015)PermalinkUpdated best practice for EDM calibrations in New South Wales / Volker Janssen in Position, n° 78 (August - September 2015)PermalinkHow good is AUSGeoid09 in the Blue Mountains ? / Joseph Allerton in Position, n° 77 (June - July 2015)PermalinkValidation of canopy height profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment / Karolina D. Fieber in ISPRS Journal of photogrammetry and remote sensing, vol 104 (June 2015)PermalinkMulti-GNSS enabling Australia's positioning infrastructure / Matt Higgins in Position, n° 76 (April - May 2015)PermalinkPredicting floods with GPS / Paul Grad in Position, n° 76 (April - May 2015)PermalinkExhibiting the exhibitors: spatial visualization for heterogeneous cinema venue data / Colin Arrowsmth in Cartographic journal (the), vol 51 n° 4 (November 2014)PermalinkNon-linear motions of Australian geodetic stations induced by non-tidal ocean loading and the passage of tropical cyclones / A. Mémin in Journal of geodesy, vol 88 n° 10 (October 2014)PermalinkEvaluation of the third- and fourth-generation GOCE Earth gravity field models with Australian terrestrial gravity data in spherical harmonics / Moritz Rexer in Journal of geodesy, vol 88 n° 4 (April 2014)Permalink