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Task selection in spatial crowdsourcing from worker’s perspective / Dingxiong Deng in Geoinformatica, vol 20 n° 3 (July - September 2016)
[article]
Titre : Task selection in spatial crowdsourcing from worker’s perspective Type de document : Article/Communication Auteurs : Dingxiong Deng, Auteur ; Cyrus Shahabi, Auteur ; Ugur Demiryurek, Auteur ; Linhong Zhu, Auteur Année de publication : 2016 Article en page(s) : pp 529 – 568 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] appareil portable
[Termes IGN] approximation
[Termes IGN] données localisées des bénévoles
[Termes IGN] données spatiotemporelles
[Termes IGN] géopositionnement
[Termes IGN] ordonnancement de tâches
[Termes IGN] programmation dynamique
[Termes IGN] prospective
[Termes IGN] téléphonie mobile
[Termes IGN] travail coopératifRésumé : (auteur) With the progress of mobile devices and wireless broadband, a new eMarket platform, termed spatial crowdsourcing is emerging, which enables workers (aka crowd) to perform a set of spatial tasks (i.e., tasks related to a geographical location and time) posted by a requester. In this paper, we study a version of the spatial crowdsourcing problem in which the workers autonomously select their tasks, called the worker selected tasks (WST) mode. Towards this end, given a worker, and a set of tasks each of which is associated with a location and an expiration time, we aim to find a schedule for the worker that maximizes the number of performed tasks. We first prove that this problem is NP-hard. Subsequently, for small number of tasks, we propose two exact algorithms based on dynamic programming and branch-and-bound strategies. Since the exact algorithms cannot scale for large number of tasks and/or limited amount of resources on mobile platforms, we propose different approximation algorithms. Finally, to strike a compromise between efficiency and accuracy, we present a progressive algorithms. We conducted a thorough experimental evaluation with both real-world and synthetic data on desktop and mobile platforms to compare the performance and accuracy of our proposed approaches. Numéro de notice : A2016-380 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0251-4 En ligne : http://dx.doi.org/10.1007/s10707-016-0251-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81147
in Geoinformatica > vol 20 n° 3 (July - September 2016) . - pp 529 – 568[article]Spectral band selection for urban material classification using hyperspectral libraries / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-7 (July 2016)
[article]
Titre : Spectral band selection for urban material classification using hyperspectral libraries Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur ; Xavier Briottet , Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2016 Article en page(s) : pp 33 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] bande spectrale
[Termes IGN] base de données d'images
[Termes IGN] capteur superspectral
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] milieu urbain
[Termes IGN] optimisation (mathématiques)
[Termes IGN] rayonnement infrarouge
[Termes IGN] signature spectraleRésumé : (auteur) In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000–2400 nm) to material classification was also shown. Numéro de notice : A2016-825 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-III-7-33-2016 Date de publication en ligne : 07/06/2016 En ligne : http://dx.doi.org/10.5194/isprs-annals-III-7-33-2016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82695
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol III-7 (July 2016) . - pp 33 - 40[article]Fusion of hyperspectral and VHR multispectral image classifications in urban α–areas / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-3 (July 2016)
[article]
Titre : Fusion of hyperspectral and VHR multispectral image classifications in urban α–areas Type de document : Article/Communication Auteurs : Alexandre Hervieu , Auteur ; Arnaud Le Bris , Auteur ; Clément Mallet , Auteur Année de publication : 2016 Projets : HYEP / Weber, Christiane Article en page(s) : pp 457 - 464 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] méthode de réduction d'énergie
[Termes IGN] occupation du sol
[Termes IGN] optimisation (mathématiques)
[Termes IGN] zone urbaineRésumé : (auteur) An energetical approach is proposed for classification decision fusion in urban areas using multispectral and hyperspectral imagery at distinct spatial resolutions. Hyperspectral data provides a great ability to discriminate land-cover classes while multispectral data,usually at higher spatial resolution, makes possible a more accurate spatial delineation of the classes. Hence, the aim here is to achieve the most accurate classification maps by taking advantage of both data sources at the decision level: spectral properties of the hyperspectral data and the geometrical resolution of multispectral images. More specifically, the proposed method takes into account probability class membership maps in order to improve the classification fusion process. Such probability maps are available using standard classification techniques such as Random Forests or Support Vector Machines. Classification probability maps are integrated into an energy framework where minimization of a given energy leads to better classification maps. The energy is minimized using a graph-cut method called quadratic pseudo-boolean optimization (QPBO) with α-expansion. A first model is proposed that gives satisfactory results in terms of classification results and visual interpretation. This model is compared to a standard Potts models adapted to the considered problem. Finally, the model is enhanced by integrating the spatial contrast observed in the data source of higher spatial resolution (i.e., the multispectral image). Obtained results using the proposed energetical decision fusion process are shown on two urban multispectral/hyperspectral datasets. 2-3% improvement is noticed with respect to a Potts formulation and 3-8% compared to a single hyperspectral-based classification. Numéro de notice : A2016-826 Affiliation des auteurs : LASTIG MATIS (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-III-3-457-2016 Date de publication en ligne : 06/06/2016 En ligne : http://dx.doi.org/10.5194/isprs-annals-III-3-457-2016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82697
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol III-3 (July 2016) . - pp 457 - 464[article]Documents numériques
en open access
Fusion of hyperspectral and VHR ... - pdf éditeurAdobe Acrobat PDF Integrating risk preferences in forest harvest scheduling / Kyle J. Eyvindson in Annals of Forest Science, vol 73 n° 2 (June 2016)
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Titre : Integrating risk preferences in forest harvest scheduling Type de document : Article/Communication Auteurs : Kyle J. Eyvindson, Auteur ; Annika S. Kangas, Auteur Année de publication : 2016 Article en page(s) : pp 321 - 330 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] gestion
[Termes IGN] gestion prévisionnelle
[Termes IGN] planification
[Termes IGN] production agricole végétale
[Termes IGN] programmation stochastique
[Termes IGN] risque environnemental
[Termes IGN] sylvicultureRésumé : (auteur) Key message: Through a stochastic programming framework, risk preferences can be included in forest planning. The value of utilizing stochastic programming is always positive; however, the value depends on the information quality and risk preferences of the decision maker.
Context: Harvest scheduling requires decisions be taken based on imperfect information and assumptions regarding the future state of the forest and markets.
Aims: The aim of this study is to incorporate elements of risk management into forest management, so that the decision maker can understand the risks associated with utilizing the imperfect data.
Methods: Incorporation of uncertainty is done through stochastic programming. This allows for the decision maker’s attitude towards risk to be incorporated into the development of a solution. By means of a simple even-flow problem formulation, a method of using stochastic programming to incorporate explicit trade-off between objective function value and risk of not meeting the constraints has been developed.
Results: The different models highlight the importance of including uncertainty in management of forest resources. In general, as the decision maker becomes more risk averse, the incorporation of uncertainty into the model becomes more important.
Conclusions: The use of stochastic programming allows for additional information to be included in the formulation, and this allows for the decision maker to account for downside risk.Numéro de notice : A2016-351 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-015-0517-2 Date de publication en ligne : 11/09/2015 En ligne : https://doi.org/10.1007/s13595-015-0517-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81061
in Annals of Forest Science > vol 73 n° 2 (June 2016) . - pp 321 - 330[article]Optimization of observation plan based on the stochastic characteristics of the geodetic network / Wojciech Pachelski in Reports on geodesy and geoinformatics, vol 101 (June 2016)
[article]
Titre : Optimization of observation plan based on the stochastic characteristics of the geodetic network Type de document : Article/Communication Auteurs : Wojciech Pachelski, Auteur ; Paweł Postek, Auteur Année de publication : 2016 Article en page(s) : pp 16 - 26 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] coût
[Termes IGN] matrice de covariance
[Termes IGN] optimisation (mathématiques)
[Termes IGN] réseau géodésique planimétriqueRésumé : (Auteur) Optimal design of geodetic network is a basic subject of many engineering projects. An observation plan is a concluding part of the process. Any particular observation within the network has through adjustment a different contribution and impact on values and accuracy characteristics of unknowns. The problem of optimal design can be solved by means of computer simulation. This paper presents a new method of simulation based on sequential estimation of individual observations in a step-by-step manner, by means of the so-called filtering equations. The algorithm aims at satisfying different criteria of accuracy according to various interpretations of the covariance matrix. Apart of them, the optimization criterion is also amount of effort, defined as the minimum number of observations required.
A numerical example of a 2-D network is illustrated to view the effectiveness of presented method. The results show decrease of the number of observations by 66% with respect to the not optimized observation plan, which still satisfy the assumed accuracy.Numéro de notice : A2016-650 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/rgg-2016-0018 En ligne : http://dx.doi.org/10.1515/rgg-2016-0018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81868
in Reports on geodesy and geoinformatics > vol 101 (June 2016) . - pp 16 - 26[article]Reconstruction of the vertical electron density profile based on vertical TEC using the simulated annealing algorithm / Chunhua Jiang in Advances in space research, vol 57 n° 10 (May 2016)PermalinkSimulating urban growth processes by integrating cellular automata model and artificial optimization in Binhai New Area of Tianjin, China / Fengmei Yao in Geocarto international, vol 31 n° 5 - 6 (May - June 2016)PermalinkOptimisation d'un service d'autopartage de véhicules électriques / Amine Ait-Ouahmed in Revue internationale de géomatique, vol 26 n° 2 (avril - juin 2016)PermalinkA synchronization algorithm for spaceborne/stationary BiSAR imaging based on contrast optimization with direct signal from radar satellite / M. Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)PermalinkEffect of tree location on mitigating parking lot insolation / Ivana Bajsanski in Computers, Environment and Urban Systems, vol 56 (March 2016)PermalinkGeoconcept, le géoptimisateur / Françoise de Blomac in DécryptaGéo le mag, n° 175 (mars 2016)PermalinkA land use/land cover change geospatial cyberinfrastructure to integrate big data and temporal topology / Jin Xing in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)PermalinkMulti-agent based path planning for first responders among moving obstacles / Zhiyong Wang in Computers, Environment and Urban Systems, vol 56 (March 2016)PermalinkOptimising the spatial resolution of WorldView-2 pan-sharpened imagery for predicting levels of Gonipterus scutellatus defoliation in KwaZulu-Natal, South Africa / Romano Lottering in ISPRS Journal of photogrammetry and remote sensing, vol 112 (February 2016)PermalinkPermalinkUne application SIG pour l’optimisation de la collecte des déchets post-inondation / Serge Lhomme (2016)PermalinkConception d'algorithmes / Patrick Bosc (2016)PermalinkPermalinkFusion of hyperspectral images and digital surface models for urban object extraction / Janja Avbelj (2016)PermalinkGestion de collecte des déchets post-inondation / Oumayma Kaabi (2016)PermalinkPermalinkPermalinkA wildlife movement approach to optimally locate wildlife crossing structures / Rebecca W. Loraamm in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkOptimal spatial land-use allocation for limited development ecological zones based on the geographic information system and a genetic ant colony algorithm / Nan Mi in International journal of geographical information science IJGIS, vol 29 n° 12 (December 2015)PermalinkRoad vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation / Fateme Ameri in Photogrammetric record, vol 30 n° 152 (December 2015 - February 2016)PermalinkGlobal optimization of GNSS station reference networks / David Coulot in GPS solutions, vol 19 n° 4 (october 2015)PermalinkStochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data / Yue Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)PermalinkMinimum volume simplex analysis: A fast algorithm for linear hyperspectral unmixing / Jun Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)PermalinkRoutes visualization: Automated placement of multiple route symbols along a physical network infrastructure / Jules Teulade-Denantes in Journal of Spatial Information Science (JoSIS), n° 11 (September 2015)PermalinkShort-term surface deformation on the Northern Hayward Fault, CA, and nearby landslides using polarimetric SAR interferometry (PolInSAR) / Samira Alipour in Pure and applied geophysics, vol 172 n° 8 (August 2015)PermalinkHyperspectral and multispectral image fusion based on a sparse representation / Qi Wei in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkAdaptive relative motion representation of space–time trajectories / Antoni B. Moore in Cartographic journal (the), Vol 52 n° 2 (May 2015)PermalinkA technique for simultaneous visualization and segmentation of hyperspectral data / Abhimitra Meka in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)PermalinkCollaborative representation for hyperspectral anomaly detection / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkProgressive band processing of constrained energy minimization for subpixel detection / Chein-I Chang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkMultibaseline polarimetric synthetic aperture radar tomography of forested areas using wavelet-based distribution compressive sensing / Lei Liang in Journal of applied remote sensing, vol 9 (2015)PermalinkAlgorithms for vision-based path following along previously taught paths / Deon George Sabatta (2015)PermalinkAutomatic spatial–spectral feature selection for hyperspectral image via discriminative sparse multimodal learning / Qian Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkPermalinkOptimisation de la configuration d’un instrument superspectral aéroporté pour la classification : application au milieu urbain / Arnaud Le Bris (2015)PermalinkPositioning configurations with the lowest GDOP and their classification / Shuqiang Xue in Journal of geodesy, vol 89 n° 1 (January 2015)PermalinkIntegrating a raster geographical information system with multi-objective land allocation optimization for conservation reserve design / WeiWei Dai in Transactions in GIS, vol 18 n° 6 (December 2014)PermalinkHigh-resolution fully polarimetric ISAR imaging based on compressive sensing / Wei Qiu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)PermalinkOn the computation of reliable formal uncertainties in the densification of GPS-levelling networks by least-squares collocation / E. Mysen in Journal of geodesy, vol 88 n° 10 (October 2014)PermalinkCombinatorial clustering and its application to 3D polygonal traffic sign reconstruction from multiple images / Bruno Vallet in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)PermalinkRegional land-use allocation using a coupled MAS and GA model: from local simulation to global optimization, a case study in Caidian District, Wuhan, China / Man Yuan in Cartography and Geographic Information Science, vol 41 n° 4 (September 2014)PermalinkRegularized simultaneous forward–backward greedy algorithm for sparse unmixing of hyperspectral data / Wei Tang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkA structure-aware global optimization method for reconstructing 3-D tree models from terrestrial laser scanning data / Z. Wang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 2 (September 2014)PermalinkPermalinkPhase quality optimization in polarimetric differential SAR interferometry / Rubén Iglesias in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)Permalink