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Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices / L. Ji in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 20 - 47 Titre : Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices Type de document : Article/Communication Auteurs : L. Ji, Auteur ; Li Zhang, Auteur ; Jennifer Rover, Auteur Année de publication : 2014 Article en page(s) : pp 20 - 47 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] bruit (théorie du signal) [Termes IGN] estimation statistique [Termes IGN] géostatistique [Termes IGN] indice de végétation Résumé : (Auteur) In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices. Numéro de notice : A2014-382 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73809 [article]

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Automatic 3D modelling of metal frame connections from LiDAR data for structural engineering purposes / M. Cabaleiro in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 47 - 57 Titre : Automatic 3D modelling of metal frame connections from LiDAR data for structural engineering purposes Type de document : Article/Communication Auteurs : M. Cabaleiro, Auteur ; B. Riveiro, Auteur ; Pedro Arias, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 47 - 57 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] modélisation 3D [Termes IGN] reconstruction 3D du bâti [Termes IGN] semis de points [Termes IGN] surveillance d'ouvrage [Termes IGN] transformation de Hough Résumé : (Auteur) The automatic generation of 3D as-built models from LiDAR data is a topic where significant progress has been made in recent years. This paper describes a new method for the detection and automatic 3D modelling of frame connections and the formation of profiles comprising a metal frame from LiDAR data. The method has been developed using an approach to create 2.5D density images for subsequent processing using the Hough transform. The structure connections can be automatically identified after selecting areas in the point cloud. As a result, the coordinates of the connection centre, composition (profiles, size and shape of the haunch) and direction of their profiles are extracted. A standard file is generated with the data obtained from the geometric and semantic characterisation of the connections. The 3D model of connections and metal frames, which are suitable for processing software for structural engineering applications, are generated automatically based on this file. The algorithm presented in this paper has been tested under laboratory conditions and also with several industrial portal frames, achieving promising results. Finally, 3D models were generated, and structural calculations were performed. Numéro de notice : A2014-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73810 [article]

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Deriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies / Jari Vauhkonen in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 57 -66 Titre : Deriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies Type de document : Article/Communication Auteurs : Jari Vauhkonen, Auteur ; Erik Naesset, Auteur ; Terje Gobakken, Auteur Année de publication : 2014 Article en page(s) : pp 57 -66 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] biomasse [Termes IGN] canopée [Termes IGN] données lidar [Termes IGN] estimation statistique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] tronc Résumé : (Auteur)A computational canopy volume (CCV) based on airborne laser scanning (ALS) data is proposed to improve predictions of forest biomass and other related attributes like stem volume and basal area. An approach to derive the CCV based on computational geometry, topological connectivity and numerical optimization was tested with sparse-density, plot-level ALS data acquired from 40 field sample plots of 500–1000 m2 located in a boreal forest in Norway. The CCV had a high correspondence with the biomass attributes considered when derived from optimized filtrations, i.e. ordered sets of simplices belonging to the triangulations based on the point data. Coefficients of determination (R2) between the CCV and total above-ground biomass, canopy biomass, stem volume, and basal area were 0.88–0.89, 0.89, 0.83–0.97, and 0.88–0.92, respectively, depending on the applied filtration. The magnitude of the required filtration was found to increase according to an increasing basal area, which indicated a possibility to predict this magnitude by means of ALS-based height and density metrics. A simple prediction model provided CCVs which had R2 of 0.77–0.90 with the aforementioned forest attributes. The derived CCVs always produced complementary information and were mainly able to improve the predictions of forest biomass relative to models based on the height and density metrics, yet only by 0–1.9 percentage points in terms of relative root mean squared error. Possibilities to improve the CCVs by a further analysis of topological persistence are discussed. Numéro de notice : A2014-384 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73811 [article]

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Hyperspectral imagery for disaggregation of land surface temperature with selected regression algorithms over different land use land cover scenes / Aniruddha Ghosh in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 76 - 93 Titre : Hyperspectral imagery for disaggregation of land surface temperature with selected regression algorithms over different land use land cover scenes Type de document : Article/Communication Auteurs : Aniruddha Ghosh, Auteur ; P.K. Joshi, Auteur Année de publication : 2014 Article en page(s) : pp 76 - 93 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] image hyperspectrale [Termes IGN] occupation du sol [Termes IGN] régression [Termes IGN] température de surface Résumé : (Auteur)Land surface temperature (LST), a key parameter in understanding thermal behavior of various terrestrial processes, changes rapidly and hence mapping and modeling its spatio-temporal evolution requires measurements at frequent intervals and finer resolutions. We designed a series of experiments for disaggregation of LST (DLST) derived from the Landsat ETM + thermal band using narrowband reflectance information derived from the EO1-Hyperion hyperspectral sensor and selected regression algorithms over three geographic locations with different climate and land use land cover (LULC) characteristics. The regression algorithms applied to this end were: partial least square regression (PLS), gradient boosting machine (GBM) and support vector machine (SVM). To understand the scale dependence of regression algorithms for predicting LST, we developed individual models (local models) at four spatial resolutions (480 m, 240 m, 120 m and 60 m) and tested the differences between these using RMSE derived from cross-validated samples. The sharpening capabilities of the models were assessed by predicting LST at finer resolutions using models developed at coarser spatial resolution. The results were also compared with LST produced by DisTrad sharpening model. It was found that scale dependence of the models is a function of the study area characteristics and regression algorithms. Considering the sharpening experiments, both GBM and SVM performed better than PLS which produced noisy LST at finer spatial resolutions. Based on the results, it can be concluded that GBM and SVM are more suitable algorithms for operational implementation of this application. These algorithms outperformed DisTrad model for heterogeneous landscapes with high variation in soil moisture content and photosynthetic activities. The variable importance measure derived from PLS and GBM provided insights about the characteristics of the relevant bands. The results indicate that wavelengths centered around 457, 671, 1488 and 2013–2083 nm are the most important in predicting LST. Nevertheless, further research is needed to improve the performance of regression algorithms when there is a large variability in LST and to examine the utility of narrowband vegetation indices to predict the LST. The benefits of this research may extend to applications such as monitoring urban heat island effect, volcanic activity and wildfire, estimating evapotranspiration and assessing drought severity. Numéro de notice : A2014-385 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73812 [article]

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Adaptive MAP sub-pixel mapping model based on regularization curve for multiple shifted hyperspectral imagery / Yanfei Zhong in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 134 - 148 Titre : Adaptive MAP sub-pixel mapping model based on regularization curve for multiple shifted hyperspectral imagery Type de document : Article/Communication Auteurs : Yanfei Zhong, Auteur ; Yunyun Wu, Auteur ; Liangpei Zhang, Auteur ; Xiong Xu, Auteur Année de publication : 2014 Article en page(s) : pp 134 - 148 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] décomposition du pixel [Termes IGN] image hyperspectrale Résumé : (Auteur) Sub-pixel mapping is a promising technique for producing a spatial distribution map of different categories at the sub-pixel scale by using the fractional abundance image as the input. The traditional sub-pixel mapping algorithms based on single images often have uncertainty due to insufficient contraint of the sub-pixel land-cover patterns within the low-resolution pixels. To improve the sub-pixel mapping accuracy, sub-pixel mapping algorithms based on auxiliary datasets, e.g., multiple shifted images, have been designed, and the maximum a posteriori (MAP) model has been successfully applied to solve the ill-posed sub-pixel mapping problem. However, the regularization parameter is difficult to set properly. In this paper, to avoid a manually defined regularization parameter, and to utilize the complementary information, a novel adaptive MAP sub-pixel mapping model based on regularization curve, namely AMMSSM, is proposed for hyperspectral remote sensing imagery. In AMMSSM, a regularization curve which includes an L-curve or U-curve method is utilized to adaptively select the regularization parameter. In addition, to take the influence of the sub-pixel spatial information into account, three class determination strategies based on a spatial attraction model, a class determination strategy, and a winner-takes-all method are utilized to obtain the final sub-pixel mapping result. The proposed method was applied to three synthetic images and one real hyperspectral image. The experimental results confirm that the AMMSSM algorithm is an effective option for sub-pixel mapping, compared with the traditional sub-pixel mapping method based on a single image and the latest sub-pixel mapping methods based on multiple shifted images. Numéro de notice : A2014-376 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.019 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73815 [article]

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Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery / Benoit Beguet in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 164 - 178 Titre : Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery Type de document : Article/Communication Auteurs : Benoit Beguet, Auteur ; Dominique Guyon, Auteur ; Samia Boukir, Auteur ; Nesrine Chehata , Auteur Année de publication : 2014 Article en page(s) : pp 164 - 178 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] forêt [Termes IGN] image à haute résolution [Termes IGN] image multibande Résumé : (Auteur) The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick’s texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ∼∼1.1 m is expected on crown diameter, ∼∼0.9 m on tree spacing, ∼∼3 m on height and ∼∼0.06 m on diameter at breast height. Numéro de notice : A2014-377 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73816 [article]

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Detecting blind building façades from highly overlapping wide angle aerial imagery / Jean-Pascal Burochin in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 193 - 209 Titre : Detecting blind building façades from highly overlapping wide angle aerial imagery Type de document : Article/Communication Auteurs : Jean-Pascal Burochin , Auteur ; Bruno Vallet , Auteur ; Mathieu Brédif , Auteur ; Clément Mallet , Auteur ; Thomas Brosset, Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2014 Article en page(s) : pp 193 - 209 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection [Termes IGN] façade [Termes IGN] modélisation 3D [Termes IGN] télédétection aérienne [Termes IGN] texturage Résumé : (Auteur) This paper deals with the identification of blind building façades, i.e. façades which have no openings, in wide angle aerial images with a decimeter pixel size, acquired by nadir looking cameras. This blindness characterization is in general crucial for real estate estimation and has, at least in France, a particular importance on the evaluation of legal permission of constructing on a parcel due to local urban planning schemes. We assume that we have at our disposal an aerial survey with a relatively high stereo overlap along-track and across-track and a 3D city model of LoD 1, that can have been generated with the input images. The 3D model is textured with the aerial imagery by taking into account the 3D occlusions and by selecting for each façade the best available resolution texture seeing the whole façade. We then parse all 3D façades textures by looking for evidence of openings (windows or doors). This evidence is characterized by a comprehensive set of basic radiometric and geometrical features. The blindness prognostic is then elaborated through an (SVM) supervised classification. Despite the relatively low resolution of the images, we reach a classification accuracy of around 85% on decimeter resolution imagery with 60×40%60×40% stereo overlap. On the one hand, we show that the results are very sensitive to the texturing resampling process and to vegetation presence on façade textures. On the other hand, the most relevant features for our classification framework are related to texture uniformity and horizontal aspect and to the maximal contrast of the opening detections. We conclude that standard aerial imagery used to build 3D city models can also be exploited to some extent and at no additional cost for facade blindness characterisation. Numéro de notice : A2014-378 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.011 Date de publication en ligne : 13/08/2014 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73817 [article]

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