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Enhancing building footprints with squaring operations / Imran Lokhat in Journal of Spatial Information Science, JoSIS, n° 13 (September 2016)
[article]
Titre : Enhancing building footprints with squaring operations Type de document : Article/Communication Auteurs : Imran Lokhat , Auteur ; Guillaume Touya , Auteur Année de publication : 2016 Article en page(s) : pp 33 - 60 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] base de données localisées
[Termes IGN] bati
[Termes IGN] empreinte
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] méthode des moindres carrés
[Termes IGN] OpenStreetMap
[Termes IGN] quadrillage
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Whatever the data source, or the capture process, the creation of a building footprint in a geographical dataset is error prone. Building footprints are designed with square angles, but once in a geographical dataset, the angles may not be exactly square. The almost-square angles blur the legibility of the footprints when displayed on maps, but might also be propagated in further applications based on the footprints, e.g., 3D city model construction. This paper proposes two new methods to square such buildings: a simple one, and a more complex one based on nonlinear least squares. The latter squares right and flat angles by iteratively moving vertices, while preserving the initial shape and position of the buildings. The methods are tested on real datasets and assessed against existing methods, proving the usefulness of the contribution. Direct applications of the squaring transformation, such as OpenStreetMap enhancement, or map generalization are presented. Numéro de notice : A2016--117 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5311/JOSIS.2016.13.276 En ligne : http://josis.org/index.php/josis/article/view/276 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84777
in Journal of Spatial Information Science, JoSIS > n° 13 (September 2016) . - pp 33 - 60[article]Documents numériques
en open access
Enhancing building footprints ... - pdf éditeurAdobe Acrobat PDF Regression wavelet analysis for lossless coding of remote-sensing data / Naoufal Amrani in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
[article]
Titre : Regression wavelet analysis for lossless coding of remote-sensing data Type de document : Article/Communication Auteurs : Naoufal Amrani, Auteur ; Joan Serra-Sagristà, Auteur ; Valero Laparra, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 5616 - 5627 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] décomposition d'image
[Termes IGN] image hyperspectrale
[Termes IGN] ondelette
[Termes IGN] régression
[Termes IGN] transformation en ondelettesRésumé : (Auteur) A novel wavelet-based scheme to increase coefficient independence in hyperspectral images is introduced for lossless coding. The proposed regression wavelet analysis (RWA) uses multivariate regression to exploit the relationships among wavelet-transformed components. It builds on our previous nonlinear schemes that estimate each coefficient from neighbor coefficients. Specifically, RWA performs a pyramidal estimation in the wavelet domain, thus reducing the statistical relations in the residuals and the energy of the representation compared to existing wavelet-based schemes. We propose three regression models to address the issues concerning estimation accuracy, component scalability, and computational complexity. Other suitable regression models could be devised for other goals. RWA is invertible, it allows a reversible integer implementation, and it does not expand the dynamic range. Experimental results over a wide range of sensors, such as AVIRIS, Hyperion, and Infrared Atmospheric Sounding Interferometer, suggest that RWA outperforms not only principal component analysis and wavelets but also the best and most recent coding standard in remote sensing, CCSDS-123. Numéro de notice : A2016-905 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2569485 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2569485 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83100
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 9 (September 2016) . - pp 5616 - 5627[article]Retrieval of leaf area index in different plant species using thermal hyperspectral data / Elnaz Neinavaz in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
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Titre : Retrieval of leaf area index in different plant species using thermal hyperspectral data Type de document : Article/Communication Auteurs : Elnaz Neinavaz, Auteur ; Andrew K. Skidmore, Auteur ; Roshanak Darvishzadeh, Auteur ; Thomas A. Groen, Auteur Année de publication : 2016 Article en page(s) : pp 390 - 401 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Buxus sempervirens
[Termes IGN] classification par réseau neuronal
[Termes IGN] espèce végétale
[Termes IGN] Euonymus japonicus
[Termes IGN] image hyperspectrale
[Termes IGN] indice foliaire
[Termes IGN] Leaf Area Index
[Termes IGN] méthode des moindres carrés
[Termes IGN] photo-interprétation
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] régression
[Termes IGN] Rhododendron (genre)Résumé : (Auteur) Leaf area index (LAI) is an important variable of terrestrial ecosystems because it is strongly correlated with many ecosystem processes (e.g., water balance and evapotranspiration) and directly related to the plant energy balance and gas exchanges. Although LAI has been accurately predicted using visible and short-wave infrared hyperspectral data (0.3–2.5 μm), LAI estimation using thermal infrared (TIR, 8–14 μm) measurements has not yet been addressed. The novel approach of this study is to evaluate the retrieval of LAI using TIR hyperspectral data. The leaf area indices were destructively acquired for four plant species: Azalea japonica, Buxus sempervirens, Euonymus japonicus, and Ficus benjamina. Canopy emissivity spectral measurements were obtained under controlled laboratory conditions using a MIDAC (M4401-F) spectrometer. The LAI retrieval was assessed using a partial least squares regression (PLSR), artificial neural networks (ANNs), and narrow band indices calculated from all possible combinations of waveband pairs for three vegetation indices including simple difference, simple ratio, and normalized difference. ANNs retrieved LAI more accurately than PLSR and vegetation indices (0.67 Numéro de notice : A2016-789 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.07.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.07.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82505
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 390 - 401[article]Semiblind hyperspectral unmixing in the presence of spectral library mismatches / Xiao Fu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
[article]
Titre : Semiblind hyperspectral unmixing in the presence of spectral library mismatches Type de document : Article/Communication Auteurs : Xiao Fu, Auteur ; Wing-Kin Ma, Auteur ; José M. Bioucas-Dias, Auteur ; Tsung-Han Chan, Auteur Année de publication : 2016 Article en page(s) : pp 5171 - 5184 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] données clairsemées
[Termes IGN] image hyperspectrale
[Termes IGN] itération
[Termes IGN] régressionRésumé : (Auteur) The dictionary-aided sparse regression (SR) approach has recently emerged as a promising alternative to hyperspectral unmixing in remote sensing. By using an available spectral library as a dictionary, the SR approach identifies the underlying materials in a given hyperspectral image by selecting a small subset of spectral samples in the dictionary to represent the whole image. A drawback with the current SR developments is that an actual spectral signature in the scene is often assumed to have zero mismatch with its corresponding dictionary sample, and such an assumption is considered too ideal in practice. In this paper, we tackle the spectral signature mismatch problem by proposing a dictionary-adjusted nonconvex sparsity-encouraging regression (DANSER) framework. The main idea is to incorporate dictionary-correcting variables in an SR formulation. A simple and low per-iteration complexity algorithm is tailor-designed for practical realization of DANSER. Using the same dictionary-correcting idea, we also propose a robust subspace solution for dictionary pruning. Extensive simulations and real-data experiments show that the proposed method is effective in mitigating the undesirable spectral signature mismatch effects. Numéro de notice : A2016-896 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2557340 En ligne : https://doi.org/10.1109/TGRS.2016.2557340 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83087
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 9 (September 2016) . - pp 5171 - 5184[article]Taking correlations in GPS least squares adjustments into account with a diagonal covariance matrix / Gaël Kermarrec in Journal of geodesy, vol 90 n° 9 (September 2016)
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Titre : Taking correlations in GPS least squares adjustments into account with a diagonal covariance matrix Type de document : Article/Communication Auteurs : Gaël Kermarrec, Auteur ; Steffen Schön, Auteur Année de publication : 2016 Article en page(s) : pp 793 – 805 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] compensation par moindres carrés
[Termes IGN] corrélation
[Termes IGN] données GPS
[Termes IGN] estimateur
[Termes IGN] matrice de covariance
[Termes IGN] matrice diagonale
[Termes IGN] pondération
[Termes IGN] positionnement différentiel
[Termes IGN] positionnement par GPS
[Termes IGN] régression
[Termes IGN] série temporelle
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) Based on the results of Luati and Proietti (Ann Inst Stat Math 63:673–686, 2011) on an equivalence for a certain class of polynomial regressions between the diagonally weighted least squares (DWLS) and the generalized least squares (GLS) estimator, an alternative way to take correlations into account thanks to a diagonal covariance matrix is presented. The equivalent covariance matrix is much easier to compute than a diagonalization of the covariance matrix via eigenvalue decomposition which also implies a change of the least squares equations. This condensed matrix, for use in the least squares adjustment, can be seen as a diagonal or reduced version of the original matrix, its elements being simply the sums of the rows elements of the weighting matrix. The least squares results obtained with the equivalent diagonal matrices and those given by the fully populated covariance matrix are mathematically strictly equivalent for the mean estimator in terms of estimate and its a priori cofactor matrix. It is shown that this equivalence can be empirically extended to further classes of design matrices such as those used in GPS positioning (single point positioning, precise point positioning or relative positioning with double differences). Applying this new model to simulated time series of correlated observations, a significant reduction of the coordinate differences compared with the solutions computed with the commonly used diagonal elevation-dependent model was reached for the GPS relative positioning with double differences, single point positioning as well as precise point positioning cases. The estimate differences between the equivalent and classical model with fully populated covariance matrix were below the mm for all simulated GPS cases and below the sub-mm for the relative positioning with double differences. These results were confirmed by analyzing real data. Consequently, the equivalent diagonal covariance matrices, compared with the often used elevation-dependent diagonal covariance matrix is appropriate to take correlations in GPS least squares adjustment into account, yielding more accurate cofactor matrices of the unknown. Numéro de notice : A2016-654 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0911-z En ligne : http://dx.doi.org/10.1007/s00190-016-0911-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81856
in Journal of geodesy > vol 90 n° 9 (September 2016) . - pp 793 – 805[article]Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland / Eetu Kotivuori in Silva fennica, vol 50 n° 4 (2016)PermalinkSpace-time multiple regression model for grid-based population estimation in urban areas / Ko Ko Lwin in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)PermalinkAn interactive tool for semi-automatic feature extraction of hyperspectral data / Zoltan Kovacs in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkComparison of robust estimators for leveling networks in Monte Carlo simulations / Maria Pokarowska in Reports on geodesy and geoinformatics, vol 101 (June 2016)PermalinkEvaluating the productivity of four main tree species in Germany under climate change with static reduced models / Martin Gutsch in Annals of Forest Science, vol 73 n° 2 (June 2016)PermalinkRelationship between landform classification and vegetation (case study: southwest of Fars province, Iran) / Marzieh Mokarram in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkA spatial analysis of GEOID03 and GEOID09 in Connecticut / Kazi Arifuzzaman in Journal of applied geodesy, vol 10 n° 2 (June 2016)PermalinkBarycentre method for solving distance equations / X. Shuqiang in Survey review, vol 48 n° 348 (May 2016)PermalinkForest above ground biomass inversion by fusing GLAS with optical remote sensing data / Xiaohuan Xi in ISPRS International journal of geo-information, vol 5 n° 4 (April 2016)PermalinkRobust locally weighted regression techniques for ground surface points filtering in mobile laser scanning three dimensional point cloud data / Abdul Nurunnabi in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)Permalink