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Polarimetric radar vegetation index for biomass estimation in desert fringe ecosystems / Jisung Geba Chang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Polarimetric radar vegetation index for biomass estimation in desert fringe ecosystems Type de document : Article/Communication Auteurs : Jisung Geba Chang, Auteur ; Maxim Shoshany, Auteur ; Yisok Oh, Auteur Année de publication : 2018 Article en page(s) : pp 7102 - 7108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] allométrie
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] bassin méditerranéen
[Termes IGN] biomasse
[Termes IGN] carte de la végétation
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] données de terrain
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] polarimétrie radar
[Termes IGN] zone aride
[Termes IGN] zone semi-arideRésumé : (auteur) Biomass estimation of eastern Mediterranean shrublands was investigated using PALSAR full- and dual-polarization L-band and Sentinel-1 dual-polarization C-band data. First, we conducted an empirical assessment of single and multiple regressions between polarized backscattering coefficients and shrubland biomass distribution along the climatic gradient between semiarid and arid regions. We then found that the PALSAR L-band HV-polarized backscattering coefficient has higher biomass information content than Sentinel-1 C-band data. Based on a theoretical volume scattering model and a semiempirical model, we propose a new polarimetric radar vegetation index (PRVI) that utilizes the degree of polarization and the cross-polarized backscattering coefficient. The relationship between the new index and the biomass was assessed with reference to normalized difference vegetation index-based biomass estimates calculated using Landsat imagery. The PRVI was found to have higher correlation with biomass compared with other radar polarization parameters, in general, and an existing radar vegetation index (RVI), in particular. Assessment of PRVI-based biomass predictions compared with allometric data extracted from air photographs, Lidar, and field data for 67 sites across the desert fringe zone indicated moderate performance with an RMSE of 0.329 kg/m 2 , while an RVI-based biomass estimation had an RMSE of 0.439 kg/m². Numéro de notice : A2018-553 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2848285 Date de publication en ligne : 03/07/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2848285 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91659
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7102 - 7108[article]Polarization orientation angle and polarimetric SAR scattering characteristics of steep terrain / Jong-Sen Lee in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Polarization orientation angle and polarimetric SAR scattering characteristics of steep terrain Type de document : Article/Communication Auteurs : Jong-Sen Lee, Auteur ; Thomas L. Ainsworth, Auteur ; Yanting Wang, Auteur Année de publication : 2018 Article en page(s) : pp 7272 - 7281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] angle de visée
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] constante diélectrique
[Termes IGN] données polarimétriques
[Termes IGN] escarpement
[Termes IGN] humidité du sol
[Termes IGN] image radar moirée
[Termes IGN] image TOPSAR
[Termes IGN] modèle de diffusion du rayonnement
[Termes IGN] montagne
[Termes IGN] pente
[Termes IGN] polarimétrie radar
[Termes IGN] polarisation croisée
[Termes IGN] réflectance spectrale
[Termes IGN] rétrodiffusion de Bragg
[Termes IGN] teneur en eau de la végétationRésumé : (auteur) Polarization orientation angle (POA) is an important parameter of polarimetric radar scattering from slopes in mountainous region. It is known that surface tilted in azimuth direction and buildings not aligned in the along-track direction induce polarization orientation shifts. Earlier research has established orientation angle as a function of radar imaging geometry and surface slopes, and that POA estimation can be derived from polarimetric radar data using circular polarization. Besides these, polarimetric scattering from steep slopes and its relation to POA remain not well understood. In this paper, we address these issues by adopting a tilted surface model based on Bragg scattering. We have found that, as the azimuthal slope increases, |VV| decreases at a faster rate than |HH|, they become equal, when POA is ±45°, and |HH| > |VV| afterward. In other words, the Pauli component, |HH-VV| reduced to zero at POA = ± 45°, and the typical Bragg scattering characteristics of |VV| > |HH| does not apply when steep slope is present inducing |POA| > 45°. Furthermore, the cross-pol |HV| does not always increase with azimuth slope but also reaches a maximum then decreases to zero. In addition, we investigate the effect of soil moisture on polarimetric SAR (PolSAR) scattering characteristics of steep terrain and the effect of vegetation over surface on POA estimation. The latter is demonstrated with NASA/JPL TOPSAR L-band PolSAR data and C-band InSAR data. Another significance of this paper is that it provides a direct and rigorous derivation of POA equations. The earlier version was derived from a different concept. Numéro de notice : A2018-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2849931 Date de publication en ligne : 01/08/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2849931 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91662
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7272 - 7281[article]Separating the influence of vegetation changes in polarimetric differential SAR interferometry / Virginia Brancato in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Separating the influence of vegetation changes in polarimetric differential SAR interferometry Type de document : Article/Communication Auteurs : Virginia Brancato, Auteur ; Irena Hajnsek, Auteur Année de publication : 2018 Article en page(s) : pp 6871 - 6883 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] biomasse
[Termes IGN] carte de la végétation
[Termes IGN] détection de changement
[Termes IGN] données polarimétriques
[Termes IGN] humidité du sol
[Termes IGN] image AIRSAR
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] polarimétrie radar
[Termes IGN] surface cultivée
[Termes IGN] télédétection en hyperfréquenceRésumé : (auteur) Soil moisture and wet biomass changes between two noninstantaneous SAR observations markedly affect the displacement estimates obtainable with Differential Interferometric Synthetic Aperture Radar (DInSAR). The separation, the modeling of these influences besides their uncoupling from the displacement signal, and the atmospheric disturbances are still unsolved issues for several repeat-pass interferometric applications. This paper focuses on the separation of vegetation changes from the other phase contributions affecting repeat-pass measurements over vegetated areas. These phase terms mainly relate to changes in soil moisture, atmospheric delays, and surface deformation. The separation is achieved with a first-order scattering solution decomposing the observed HH and VV DInSAR phases in the sum of several phase terms. The latter mainly consider the changes in soil surface scattering and in the two-way propagation through a vertically oriented vegetation canopy. No assumption is made on the spatiotemporal evolution of the displacement and atmosphere. The overall approach is tested on a L-band data set acquired over an agricultural area. Upon calibration, the model allows for estimating changes in wet biomass based on the nonzero HH–VV DInSAR phase difference observed over several birefringent agricultural fields. The obtained biomass estimates provide then a correction for the effect of vegetation changes on the observed HH and VV DInSAR phases. Deprived of the vegetation contribution, the remainder phase terms can be more easily explored for further analyses, e.g., the estimation of soil moisture changes and/or surface movements in vertically oriented vegetated areas. Numéro de notice : A2018-551 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2845368 Date de publication en ligne : 14/08/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2845368 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91639
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 6871 - 6883[article]Super-resolution of Sentinel-2 images : Learning a globally applicable deep neural network / Charis Lanaras in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)
[article]
Titre : Super-resolution of Sentinel-2 images : Learning a globally applicable deep neural network Type de document : Article/Communication Auteurs : Charis Lanaras, Auteur ; José Bioucas-Dias, Auteur ; Silvano Galliani, Auteur ; Emmanuel P. Baltsavias, Auteur ; Konrad Schindler, Auteur Année de publication : 2018 Article en page(s) : pp 305 - 319 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] bande spectrale
[Termes IGN] échantillonnage de données
[Termes IGN] erreur moyenne quadratique
[Termes IGN] image à basse résolution
[Termes IGN] image Sentinel-MSI
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] pas d'échantillonnage au sol
[Termes IGN] pouvoir de résolution spectrale
[Termes IGN] réseau neuronal convolutifRésumé : (Auteur) The Sentinel-2 satellite mission delivers multi-spectral imagery with 13 spectral bands, acquired at three different spatial resolutions. The aim of this research is to super-resolve the lower-resolution (20 m and 60 m Ground Sampling Distance – GSD) bands to 10 m GSD, so as to obtain a complete data cube at the maximal sensor resolution. We employ a state-of-the-art convolutional neural network (CNN) to perform end-to-end upsampling, which is trained with data at lower resolution, i.e., from 40 20 m, respectively 360 60 m GSD. In this way, one has access to a virtually infinite amount of training data, by downsampling real Sentinel-2 images. We use data sampled globally over a wide range of geographical locations, to obtain a network that generalises across different climate zones and land-cover types, and can super-resolve arbitrary Sentinel-2 images without the need of retraining. In quantitative evaluations (at lower scale, where ground truth is available), our network, which we call DSen2, outperforms the best competing approach by almost 50% in RMSE, while better preserving the spectral characteristics. It also delivers visually convincing results at the full 10 m GSD. Numéro de notice : A2018-540 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.09.018 Date de publication en ligne : 21/10/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.09.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91554
in ISPRS Journal of photogrammetry and remote sensing > vol 146 (December 2018) . - pp 305 - 319[article]Réservation
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[article]
Titre : Application of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak, Kerman, south of Iran Type de document : Article/Communication Auteurs : Morteza Safari, Auteur ; Abbas Maghsoudi, Auteur ; Amin Beiranvand Pour, Auteur Année de publication : 2018 Article en page(s) : pp 1186 - 1201 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse en composantes principales
[Termes IGN] bande spectrale
[Termes IGN] cuivre
[Termes IGN] émission thermique
[Termes IGN] filtre de déchatoiement
[Termes IGN] image Landsat-8
[Termes IGN] image Terra-ASTER
[Termes IGN] Iran
[Termes IGN] lithologie
[Termes IGN] prospection minérale
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] rayonnement proche infrarougeRésumé : (auteur) The Shahr-e-Babak region located in the Kerman metallogenic belt is one of the high potential segments of Urumieh–Dokhtar magmatic arc for porphyry copper and epithermal gold mineralization in the south of Iran. This high potential zone encompasses several porphyry copper deposits under exploitation, development and exploration stages. The aim of this study is to evaluate Landsat-8 data and comparison with the Advanced Spaceborne Thermal Emission and Reflection Radiometer data-sets for mapping hydrothermal alteration zones related to Cenozoic magmatic intrusions in Shahr-e-Babak region. Previous studies have proven the robust application of ASTER in lithological mapping and mineral exploration; nonetheless, the Landsat-8 data have high capability to map and detect hydrothermal alteration zones associated with porphyry copper and epithermal gold mineralization. In this investigation, several band combinations and multiplications, developed selective principal component analysis and image transformations were developed for discriminating hydrothermal alteration zones associated with porphyry copper mineralization using Landsat-8 data. Numéro de notice : A2019-048 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1334834 Date de publication en ligne : 12/06/2017 En ligne : https://doi.org/10.1080/10106049.2017.1334834 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92070
in Geocarto international > vol 33 n° 11 (November 2018) . - pp 1186 - 1201[article]Object-based crop classification using multi-temporal SPOT-5 imagery and textural features with a Random Forest classifier / Huanxue Zhang in Geocarto international, vol 33 n° 10 (October 2018)PermalinkEstimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)PermalinkConnecting infrared spectra with plant traits to identify species / Maria F. Buitrago in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkA statistical approach to preprocess and enhance C-band SAR images in order to detect automatically marine oil slicks / Zhour Najoui in IEEE Transactions on geoscience and remote sensing, vol 56 n° 5 (May 2018)PermalinkCartographier le relief sous les forêts, et le substrat sous les déserts de sable : les attentes de la mission radar Biomass / Laurent Polidori in XYZ, n° 154 (mars - mai 2018)PermalinkUnderstanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery / Pablo J. Zarco-Tejada in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)PermalinkEstimation of surface roughness over bare agricultural soil from Sentinel-1 data / Mohammad Choker (2018)PermalinkTélédétection multispectrale et hyperspectrale des eaux littorales turbides / Morgane Larnicol (2018)PermalinkInSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico / Pascal Castellazzi in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)PermalinkRemote sensing of species diversity using Landsat 8 spectral variables / Sabelo Madonsela in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)PermalinkThe potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)PermalinkAn information fusion approach for PALSAR data to retrieve soil moisture / Ankita Jain in Geocarto international, vol 32 n° 9 (September 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)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)PermalinkDisplacement monitoring and modelling of a high-speed railway bridge using C-band Sentinel-1 data / Qihuan Huang in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)PermalinkSemiautomatic detection and classification of materials in historic buildings with low-cost photogrammetric equipment / Javier Sanchez in Journal of Cultural Heritage, vol 25 (May - June 2017)PermalinkAn unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data — A case study in complex temperate forest stands / Sahra Abdullahi in International journal of applied Earth observation and geoinformation, vol 57 (May 2017)PermalinkEvaluation of multisource data for glacier terrain mapping : a neural net approach / Aparna Shukla in Geocarto international, vol 32 n° 5 (May 2017)PermalinkForest classification and impact of BIOMASS resolution on forest area and aboveground biomass estimation / Michael Schlund in International journal of applied Earth observation and geoinformation, vol 56 (April 2017)Permalink