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The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)
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Titre : The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas Type de document : Article/Communication Auteurs : Emanuele Santi, Auteur ; Simonetta Paloscia, Auteur ; Simone Pettinato, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 63 - 73 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] biomasse forestière
[Termes IGN] capacité de stockage
[Termes IGN] classification par réseau neuronal
[Termes IGN] forêt méditerranéenne
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Envisat-ASAR
[Termes IGN] image radar moirée
[Termes IGN] modèle de transfert radiatif
[Termes IGN] production primaire brute
[Termes IGN] Toscane (Italie)Résumé : (auteur) The extraction of forest information from SAR images is particularly complex in Mediterranean areas, since they are characterized by high spatial fragmentation and heterogeneity. We have investigated the use of multi-frequency SAR data from different sensors (ALOS/PALSAR and ENVISAT/ASAR) for estimating forest biomass in two test areas in Central Italy (San Rossore and Molise), where detailed in-situ measurements and Airborne Laser Scanning (ALS) data were available. The study focused on the estimation of growing stock volume (GS, in m3/ha) by using an inversion algorithm based on artificial neural networks (ANN). The ANN algorithm was first appropriately trained using the available GS estimates obtained from ALS data. The potential of this algorithm was then improved through the innovative use of a simulated dataset, generated by a forward electromagnetic model based on the Radiative Transfer Theory (RTT). The algorithm is able to merge SAR data at L and C bands for predicting GS in diversified Mediterranean environments. The performed analyses indicated that GS was correctly estimated by integrating information from L and C bands on both test areas, with the following statistics: R > 0.97 and RMSE = 28.5 m3/ha for the independent test, and R = 0.86 and RMSE ≈ 77 m3/ha for the final independent validation, the latter performed on the forest stands of both areas not included in the ALS acquisitions and where conventional measurements were available. The research then illustrates the potential of using the obtained GS estimates from SAR data to drive the simulations of forest net primary production (NPP). This experiment produced spatially explicit estimates of GS current annual increments that are slightly less accurate than those obtained from ground observations (R = 0.75 and RMSE ≈ 1.5 m3/ha/year). Numéro de notice : A2017-415 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.07.038 En ligne : https://doi.org/10.1016/j.rse.2017.07.038 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86307
in Remote sensing of environment > vol 200 (October 2017) . - pp 63 - 73[article]Wind loads and competition for light sculpt trees into self-similar structures / Christophe Eloy in Nature communications, vol 8 (2017)
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Titre : Wind loads and competition for light sculpt trees into self-similar structures Type de document : Article/Communication Auteurs : Christophe Eloy, Auteur ; Meriem Fournier, Auteur ; André Lacointe, Auteur ; Bruno Moulia, Auteur Année de publication : 2017 Langues : Anglais (eng) Descripteur : [Termes IGN] arbre (flore)
[Termes IGN] croissance des arbres
[Termes IGN] données allométriques
[Termes IGN] modèle numérique
[Termes IGN] rayonnement lumineux
[Termes IGN] structure de la végétation
[Termes IGN] vent
[Vedettes matières IGN] BotaniqueRésumé : (auteur) Trees are self-similar structures: their branch lengths and diameters vary allometrically within the tree architecture, with longer and thicker branches near the ground. These tree allometries are often attributed to optimisation of hydraulic sap transport and safety against elastic buckling. Here, we show that these allometries also emerge from a model that includes competition for light, wind biomechanics and no hydraulics. We have developed MECHATREE, a numerical model of trees growing and evolving on a virtual island. With this model, we identify the fittest growth strategy when trees compete for light and allocate their photosynthates to grow seeds, create new branches or reinforce existing ones in response to wind-induced loads. Strikingly, we find that selected trees species are self-similar and follow allometric scalings similar to those observed on dicots and conifers. This result suggests that resistance to wind and competition for light play an essential role in determining tree allometries. Numéro de notice : A2017-780 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1038/s41467-017-00995-6 En ligne : https://doi.org/10.1038/s41467-017-00995-6 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88980
in Nature communications > vol 8 (2017)[article]Atmospheric correction over coastal waters using multilayer neural networks / Yongzhen Fan in Remote sensing of environment, vol 199 (15 September 2017)
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Titre : Atmospheric correction over coastal waters using multilayer neural networks Type de document : Article/Communication Auteurs : Yongzhen Fan, Auteur ; Wei Li, Auteur ; Charles K. Gatebe, Auteur ; Cédric Jamet, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 218 - 240 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] correction atmosphérique
[Termes IGN] couleur de l'océan
[Termes IGN] eaux côtières
[Termes IGN] image Aqua-MODIS
[Termes IGN] Perceptron multicouche
[Termes IGN] transfert radiatifRésumé : (auteur) Standard atmospheric correction (AC) algorithms work well in open ocean areas where the water inherent optical properties (IOPs) are correlated with pigmented particles. However, the IOPs of turbid coastal waters may independently vary with pigmented particles, suspended inorganic particles, and colored dissolved organic matter (CDOM). In turbid coastal waters standard AC algorithms often exhibit large inaccuracies that may lead to negative water-leaving radiances (Lw) or remote sensing reflectance (Rrs). We introduce a new atmospheric correction algorithm for coastal waters based on a multilayer neural network (MLNN) method. We use a coupled atmosphere-ocean radiative transfer model to simulate the Rayleigh-corrected radiance (Lrc) at the top of the atmosphere (TOA) and the Rrs just above the surface simultaneously, and train a MLNN to derive the aerosol optical depth (AOD) and Rrs directly from the TOA Lrc. The method is validated using both a synthetic dataset and Aerosol Robotic Network – Ocean Color (AERONET–OC) measurements. The SeaDAS NIR algorithm, the SeaDAS NIR/SWIR algorithm, and the MODIS version of the Case 2 regional water - CoastColour (C2RCC) algorithm are also included in the comparison with AERONET–OC measurements. The performance of the AC algorithms is evaluated with four statistical metrics: the Pearson correlation coefficient (R), the average percentage difference (APD), the mean percentage bias, and the root mean square difference (RMSD). The comparison with AERONET–OC measurements shows that the MLNN algorithm significantly improves retrieval of normalized Lw in blue bands (412 nm and 443 nm) and yields minor improvements in green and red bands compared with the other three algorithms. On a global scale, the MLNN algorithm reduces APD in normalized Lw by up to 13% in blue bands and by 2–7% in green and red bands when compared with the standard SeaDAS NIR algorithm. In highly absorbing coastal waters, such as the Baltic Sea, the MLNN algorithm reduces APD in normalized Lw by more than 60% in blue bands compared to the standard SeaDAS NIR algorithm, while in highly scattering coastal waters, such as the Black Sea, the MLNN algorithm reduces APD by more than 25%. These results indicate that the MLNN algorithm is suitable for application in turbid coastal waters. Application of the MLNN algorithm to MODIS Aqua images in several coastal areas also shows that it is robust and resilient to contamination due to sunglint or adjacency effects of land and cloud edges. The MLNN algorithm is very fast once the neural network has been properly trained and is therefore suitable for operational use. A significant advantage of the MLNN algorithm is that it does not need SWIR bands. Numéro de notice : A2017-417 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.07.016 En ligne : https://doi.org/10.1016/j.rse.2017.07.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86310
in Remote sensing of environment > vol 199 (15 September 2017) . - pp 218 - 240[article]An information fusion approach for PALSAR data to retrieve soil moisture / Ankita Jain in Geocarto international, vol 32 n° 9 (September 2017)
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Titre : An information fusion approach for PALSAR data to retrieve soil moisture Type de document : Article/Communication Auteurs : Ankita Jain, Auteur ; Dharmendra Singh, Auteur Année de publication : 2017 Article en page(s) : pp 1017 - 1033 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande spectrale
[Termes IGN] couvert végétal
[Termes IGN] données polarimétriques
[Termes IGN] fusion de données
[Termes IGN] humidité du sol
[Termes IGN] image ALOS-PALSAR
[Termes IGN] polarimétrie radarRésumé : (Auteur) Estimation of vegetation covered soil moisture with satellite images is still a challenging task. Several models are available for soil moisture retrieval in which water cloud model (WCM) is most common. But, it requires an estimation of accurate vegetation parameterization. Thus, there is a need to develop such an approach for soil moisture retrieval which minimize these limitations. Therefore, this paper deals with the soil moisture retrieval using fully polarimetric SAR data by fusing the information from different bands. Various polarimetric indices and observables were critically analysed, and found that the index; SPAN (total scattered power) gives better information of vegetation cover as compared to other indices/observables. Based on this, WCM model has been modified using SPAN as parameter and soil moisture content were retrieved. Numéro de notice : A2017-459 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1188163 Date de publication en ligne : 10/06/2016 En ligne : http://dx.doi.org/10.1080/10106049.2016.1188163 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86384
in Geocarto international > vol 32 n° 9 (September 2017) . - pp 1017 - 1033[article]Critical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect / Pooja Mishra in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)
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Titre : Critical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect Type de document : Article/Communication Auteurs : Pooja Mishra, Auteur ; Akanksha Garg, Auteur ; Dharmendra Singh, Auteur Année de publication : 2017 Article en page(s) : pp 4868 - 4877 Note générale : Bibliothèque Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] décomposition d'image
[Termes IGN] diffusion du rayonnement
[Termes IGN] données polarimétriques
[Termes IGN] image ALOS
[Termes IGN] image ALOS-PALSAR
[Termes IGN] occupation du sol
[Termes IGN] polarimétrie radar
[Termes IGN] valeur propre
[Termes IGN] zone urbaineRésumé : (Auteur) This paper critically analyzes several incoherent model-based decomposition methods for assessing the effect of deorientation in characterization of various land covers. It has been found that even after performing decomposition, ambiguity still occurs in scattering response from various land covers, such as urban and vegetation. Researchers introduced the concept of deorientation to remove this ambiguity. Therefore, in this paper, a critical analysis has been carried out using seven different three- and four-component decomposition methods with and without deorientation and two Eigen decomposition-based methods to investigate the scattering response on various land covers, such as urban, vegetation, bare soil, and water. The comprehensive evaluation of decomposition and deorientation effect has been performed by both visual and quantitative analyses. Two types of quantitative analysis have been performed; first, by observing percentage of scattering power and second, by analyzing the variation in the number of pixels in different land covers for each scattering contribution. The analysis shows that deorientation increases not only the power but also the number of pixels for surface and double bounce scattering. The number of pixels representing volume scattering remain almost the same for all the methods with or without deorientation, whereas volume scattering power reduces after deorientation. Eigen decomposition-based methods are observed to solve the problem of overestimation of volume scattering power. Numéro de notice : A2017-657 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2652060 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2652060 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87067
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 9 (September 2017) . - pp 4868 - 4877[article]ERTK: extra-wide-lane RTK of triple-frequency GNSS signals / Bofeng Li in Journal of geodesy, vol 91 n° 9 (September 2017)
PermalinkImproving BeiDou real-time precise point positioning with numerical weather models / Cuixian Lu in Journal of geodesy, vol 91 n° 9 (September 2017)
PermalinkApplication of ray-traced tropospheric slant delays to geodetic VLBI analysis / Armin Hofmeister in Journal of geodesy, vol 91 n° 8 (August 2017)
PermalinkColour Helmholtz stereopsis for reconstruction of dynamic scenes with arbitrary unknown reflectance / Nadejda Roubtsova in International journal of computer vision, vol 124 n° 1 (August 2017)
PermalinkRetrieving grassland canopy water content by considering the information from neighboring pixels / Binbin He in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 8 (August 2017)
PermalinkSimultaneous estimation of leaf area index, fraction of absorbed photosynthetically active radiation, and surface albedo from multiple-satellite data / Han Ma in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)
PermalinkPerformance evaluation of ionospheric time delay forecasting models using GPS observations at a low-latitude station / G. Sivavaraprasad in Advances in space research, vol 60 n° 2 (15 July 2017)
PermalinkCoverage of high biomass forests by the ESA BIOMASS mission under defense restrictions / João M.B. Carreiras in Remote sensing of environment, vol 196 (July 2017)
PermalinkDeveloping detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor / Abel Chemura in Geocarto international, vol 32 n° 7 (July 2017)
PermalinkGold – A novel deconvolution algorithm with optimization for waveform LiDAR processing / Tan Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)
PermalinkImpact of GPS differential code bias in dual- and triple-frequency positioning and satellite clock estimation / Haojun Li in GPS solutions, vol 21 n° 3 (July 2017)
PermalinkImproving the modeling of the atmospheric delay in the data analysis of the Intensive VLBI sessions and the impact on the UT1 estimates / Tobias Nilsson in Journal of geodesy, vol 91 n° 7 (July 2017)
PermalinkOptimum stochastic modeling for GNSS tropospheric delay estimation in real-time / Tomasz Hadas in GPS solutions, vol 21 n° 3 (July 2017)
PermalinkReal-time precise point positioning augmented with high-resolution numerical weather prediction model / Karina Wilgan in GPS solutions, vol 21 n° 3 (July 2017)
PermalinkStudy and mitigation of calibration factor instabilities in a water vapor Raman lidar / Leslie David in Atmospheric measurement techniques, vol 10 n° 7 (July 2017)
PermalinkWREP : A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops / Dong Li in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)
PermalinkAn adaptive weighted tensor completion method for the recovery of remote sensing images with missing data / Michael Kwok-Po Ng in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 2017)
PermalinkAngular reflectance of leaves with a dual-wavelength terrestrial lidar and its implications for leaf-bark separation and leaf moisture estimation / Steven Hancock in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 2017)
PermalinkAutomatic GPS ionospheric amplitude and phase scintillation detectors using a machine learning algorithm / Yu Jiao in Inside GNSS, vol 12 n° 3 (May - June 2017)
PermalinkDecomposition of LiDAR waveforms by B-spline-based modeling / Xiang Shen in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)
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