Centre de documentation
scientifique

Dépouillements

Use of LiDAR for calculating solar irradiance on roofs and façades of buildings at city scale: Methodology, validation, and analysis / Liang Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 12 - 29 Titre : Use of LiDAR for calculating solar irradiance on roofs and façades of buildings at city scale: Methodology, validation, and analysis Type de document : Article/Communication Auteurs : Liang Cheng, Auteur ; Hao Xu, Auteur ; Shuyi Li, Auteur ; Yanming Chen, Auteur ; Fangli Zhang, Auteur ; Manchun Li, Auteur Année de publication : 2018 Article en page(s) : pp 12 - 29 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] éclairement lumineux [Termes IGN] façade [Termes IGN] milieu urbain [Termes IGN] rayonnement solaire [Termes IGN] toit Résumé : (Auteur) As the rate of urbanization continues to accelerate, the utilization of solar energy in buildings plays an increasingly important role in sustainable urban development. For this purpose, we propose a LiDAR-based joint approach for calculating the solar irradiance incident on roofs and façades of buildings at city scale, which includes a methodology for calculating solar irradiance, the validation of the proposed method, and analysis of its application. The calculation of surface irradiance on buildings may then inform photovoltaic power generation simulations, architectural design, and urban energy planning. Application analyses of the proposed method in the experiment area found that: (1) Global and direct irradiations vary significantly by hour, day, month and season, both following the same trends; however, diffuse irradiance essentially remains unchanged over time. (2) Roof irradiation, but not façade irradiation, displays distinct time-dependent patterns. (3) Global and direct irradiations on roofs are highly correlated with roof aspect and slope, with high global and direct irradiations observed on roofs of aspect 100–250° and slopes of 0–60°, whereas diffuse irradiation on roofs is only affected by roof slope. (4) The façade of a building receives higher levels of global and direct irradiations if facing southeast, south, and southwest; however, diffuse irradiation remains constant regardless of façade orientation. Numéro de notice : A2018-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.024 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89568 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018043	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018042	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform / Mohd Shahrimie Mohd Asaari in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 121 - 138 Titre : Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform Type de document : Article/Communication Auteurs : Mohd Shahrimie Mohd Asaari, Auteur ; Puneet Mishra ; Stien Mertens, Auteur ; Stijn Dhondt, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 121 - 138 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse spectrale [Termes IGN] image hyperspectrale [Termes IGN] maïs (céréale) [Termes IGN] mesure de similitude [Termes IGN] réflectance végétale [Termes IGN] signature spectrale [Termes IGN] similitude spectrale [Termes IGN] stress hydrique Résumé : (Auteur) The potential of close-range hyperspectral imaging (HSI) as a tool for detecting early drought stress responses in plants grown in a high-throughput plant phenotyping platform (HTPPP) was explored. Reflectance spectra from leaves in close-range imaging are highly influenced by plant geometry and its specific alignment towards the imaging system. This induces high uninformative variability in the recorded signals, whereas the spectral signature informing on plant biological traits remains undisclosed. A linear reflectance model that describes the effect of the distance and orientation of each pixel of a plant with respect to the imaging system was applied. By solving this model for the linear coefficients, the spectra were corrected for the uninformative illumination effects. This approach, however, was constrained by the requirement of a reference spectrum, which was difficult to obtain. As an alternative, the standard normal variate (SNV) normalisation method was applied to reduce this uninformative variability. Once the envisioned illumination effects were eliminated, the remaining differences in plant spectra were assumed to be related to changes in plant traits. To distinguish the stress-related phenomena from regular growth dynamics, a spectral analysis procedure was developed based on clustering, a supervised band selection, and a direct calculation of a spectral similarity measure against a reference. To test the significance of the discrimination between healthy and stressed plants, a statistical test was conducted using a one-way analysis of variance (ANOVA) technique. The proposed analysis techniques was validated with HSI data of maize plants (Zea mays L.) acquired in a HTPPP for early detection of drought stress in maize plant. Results showed that the pre-processing of reflectance spectra with the SNV effectively reduces the variability due to the expected illumination effects. The proposed spectral analysis method on the normalized spectra successfully detected drought stress from the third day of drought induction, confirming the potential of HSI for drought stress detection studies and further supporting its adoption in HTPPP. Numéro de notice : A2018-122 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.02.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.02.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89570 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018043	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018042	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery / Chunping Qiu in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 218 - 231 Titre : Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery Type de document : Article/Communication Auteurs : Chunping Qiu, Auteur ; Michael Schmitt, Auteur ; Xiao Xiang Zhu, Auteur Année de publication : 2018 Article en page(s) : pp 218 - 231 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] couple stéréoscopique [Termes IGN] géométrie épipolaire [Termes IGN] image optique [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] image Worldview [Termes IGN] mesure de similitude [Termes IGN] points homologues [Termes IGN] précision de localisation [Termes IGN] reconstruction 3D [Termes IGN] zone urbaine Résumé : (Auteur) In this paper, we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do this mainly from a geometrical point of view, we first analyze the height reconstruction accuracy to be expected for different stereogrammetric configurations. Then, we propose a strategy for simultaneous tie point matching and 3D reconstruction, which exploits an epipolar-like search window constraint. To drive the matching and ensure some robustness, we combine different established hand-crafted similarity measures. For the experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR imagery is generally feasible with 3D positioning accuracies in the meter-domain, although the matching of these strongly hetereogeneous multi-sensor data remains very challenging. Numéro de notice : A2018-124 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.12.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.12.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89586 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018043	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018042	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

A spatio-temporal index for aerial full waveform laser scanning data / Debra F. Laefer in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 232 - 251 Titre : A spatio-temporal index for aerial full waveform laser scanning data Type de document : Article/Communication Auteurs : Debra F. Laefer, Auteur ; Anh-Vu Vo, Auteur ; Michela Bertolotto, Auteur Année de publication : 2018 Article en page(s) : pp 232 - 251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre-R [Termes IGN] base de données localisées [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forme d'onde pleine [Termes IGN] index spatiotemporel [Termes IGN] indexation spatiale [Termes IGN] octree Résumé : (Auteur) Aerial laser scanning is increasingly available in the full waveform version of the raw signal, which can provide greater insight into and control over the data and, thus, richer information about the scanned scenes. However, when compared to conventional discrete point storage, preserving raw waveforms leads to vastly larger and more complex data volumes. To begin addressing these challenges, this paper introduces a novel bi-level approach for storing and indexing full waveform (FWF) laser scanning data in a relational database environment, while considering both the spatial and the temporal dimensions of that data. In the storage scheme's upper level, the full waveform datasets are partitioned into spatial and temporal coherent groups that are indexed by a two-dimensional R∗-tree. To further accelerate intra-block data retrieval, at the lower level a three-dimensional local octree is created for each pulse block. The local octrees are implemented in-memory and can be efficiently written to a database for reuse. The indexing solution enables scalable and efficient three-dimensional (3D) spatial and spatio-temporal queries on the actual pulse data - functionalities not available in other systems. The proposed FWF laser scanning data solution is capable of managing multiple FWF datasets derived from large flight missions. The flight structure is embedded into the data storage model and can be used for querying predicates. Such functionality is important to FWF data exploration since aircraft locations and orientations are frequently required for FWF data analyses. Empirical tests on real datasets of up to 1 billion pulses from Dublin, Ireland prove the almost perfect scalability of the system. The use of the local 3D octree in the indexing structure accelerated pulse clipping by 1.2–3.5 times for non-axis-aligned (NAA) polyhedron shaped clipping windows, while axis-aligned (AA) polyhedron clipping was better served using only the top indexing layer. The distinct behaviours of the hybrid indexing for AA and NAA clipping windows are attributable to the different proportion of the local-index-related overheads with respect to the total querying costs. When temporal constraints were added, generally the number of costly spatial checks were reduced, thereby shortening the querying times. Numéro de notice : A2018-125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89587 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018043	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018042	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

A novel orthoimage mosaic method using a weighted A∗ algorithm : Implementation and evaluation / Maoteng Zheng in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 30 - 46 Titre : A novel orthoimage mosaic method using a weighted A∗ algorithm : Implementation and evaluation Type de document : Article/Communication Auteurs : Maoteng Zheng, Auteur ; Xiong Xiaodong, Auteur ; Junfeng Zhu, Auteur Année de publication : 2018 Article en page(s) : pp 30 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Orthophotographie, orthoimage [Termes IGN] diagramme de Voronoï [Termes IGN] drone [Termes IGN] jeu de données localisées [Termes IGN] modèle numérique de surface [Termes IGN] noeud [Termes IGN] orthophotoplan numérique [Termes IGN] pondération Résumé : (Auteur) The implementation and evaluation of a weighted A∗ algorithm for orthoimage mosaic with UAV (Unmanned Aircraft Vehicle) imagery is proposed. The initial seam-line network is firstly generated by standard Voronoi Diagram algorithm; an edge diagram is generated based on DSM (Digital Surface Model) data; the vertices (conjunction nodes of seam-lines) of the initial network are relocated if they are on high objects (buildings, trees and other artificial structures); and the initial seam-lines are refined using the weighted A∗ algorithm based on the edge diagram and the relocated vertices. Our method was tested with three real UAV datasets. Two quantitative terms are introduced to evaluate the results of the proposed method. Preliminary results show that the method is suitable for regular and irregular aligned UAV images for most terrain types (flat or mountainous areas), and is better than the state-of-the-art method in both quality and efficiency based on the test datasets. Numéro de notice : A2018-119 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.02.007 Date de publication en ligne : 09/03/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89588 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018043	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018042	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification / Rama Rao Nidamanuri in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 74 - 85 Titre : Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification Type de document : Article/Communication Auteurs : Rama Rao Nidamanuri, Auteur ; Fahad Shahbaz Khan, Auteur ; Joost van de Weijer, Auteur ; Matthieu Molinier, Auteur ; Jorma Laaksonen, Auteur Année de publication : 2018 Article en page(s) : pp 74 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse texturale [Termes IGN] apprentissage profond [Termes IGN] classification [Termes IGN] image RVB [Termes IGN] motif binaire local [Termes IGN] réseau neuronal convolutif [Termes IGN] texture d'image Résumé : (Auteur) Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification. Numéro de notice : A2018-121 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.023 Date de publication en ligne : 15/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89590 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018043	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018042	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Mapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data / Abel Chemura in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 1 - 11 Titre : Mapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data Type de document : Article/Communication Auteurs : Abel Chemura, Auteur ; Onisimo Mutanga, Auteur ; John Odindi, Auteur ; Dumisani Kutywayo, Auteur Année de publication : 2018 Article en page(s) : pp 1 - 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] agriculture de précision [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] Coffea arabica [Termes IGN] feuille (végétation) [Termes IGN] image Sentinel-MSI [Termes IGN] nutriment végétal [Termes IGN] teneur en azote Résumé : (auteur) Nitrogen (N) is the most limiting factor to coffee development and productivity. Therefore, development of rapid, spatially explicit and temporal remote sensing-based approaches to determine spatial variability of coffee foliar N are imperative for increasing yields, reducing production costs and mitigating environmental impacts associated with excessive N applications. This study sought to assess the value of Sentinel-2 MSI spectral bands and vegetation indices in empirical estimation of coffee foliar N content at landscape level. Results showed that coffee foliar N is related to Sentinel-2 MSI B4 (R2 = 0.32), B6 (R2 = 0.49), B7 (R2 = 0.42), B8 (R2 = 0.57) and B12 (R2 = 0.24) bands. Vegetation indices were more related to coffee foliar N as shown by the Inverted Red-Edge Chlorophyll Index – IRECI (R2 = 0.66), Relative Normalized Difference Index – RNDVI (R2 = 0.48), CIRE1 (R2 = 0.28), and Normalized Difference Infrared Index – NDII (R2 = 0.37). These variables were also identified by the random forest variable optimisation as the most valuable in coffee foliar N prediction. Modelling coffee foliar N using vegetation indices produced better accuracy (R2 = 0.71 with RMSE = 0.27 for all and R2 = 0.73 with RMSE = 0.25 for optimized variables), compared to using spectral bands (R2 = 0.57 with RMSE = 0.32 for all and R2 = 0.58 with RMSE = 0.32 for optimized variables). Combining optimized bands and vegetation indices produced the best results in coffee foliar N modelling (R2 = 0.78, RMSE = 0.23). All the three best performing models (all vegetation indices, optimized vegetation indices and combining optimal bands and optimal vegetation indices) established that 15.2 ha (4.7%) of the total area under investigation had low foliar N levels ( Numéro de notice : A2018-145 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.02.004 Date de publication en ligne : 10/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.02.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89753 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018043	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018042	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt