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Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)
[article]
Titre : Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data Type de document : Article/Communication Auteurs : P. Kumar, Auteur ; R. Prasad, Auteur ; D. K. Gupta, Auteur ; V. N. Mishra, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 942 - 956 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande C
[Termes IGN] blé (céréale)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] croissance végétale
[Termes IGN] cultures
[Termes IGN] données polarimétriques
[Termes IGN] estimation statistique
[Termes IGN] hiver
[Termes IGN] image Sentinel-SAR
[Termes IGN] Leaf Area Index
[Termes IGN] régression
[Termes IGN] régression linéaire
[Termes IGN] réseau neuronal artificiel
[Termes IGN] séparateur à vaste marge
[Termes IGN] teneur en eau de la végétationRésumé : (Auteur) In the present study, Sentinel-1A Synthetic Aperture Radar analysis of time series data at C-band was carried out to estimate the winter wheat crop growth parameters. Five different date images were acquired during January 2015–April 2015 at different growth stages from tillering to ripening in Varanasi district, India. The winter wheat crop parameters, i.e. leaf area index, vegetation water content (VWC), fresh biomass (FB), dry biomass (DB) and plant height (PH) were estimated using random forest regression (RFR), support vector regression (SVR), artificial neural network regression (ANNR) and linear regression (LR) algorithms. The Ground Range Detected products of Interferometric Wide (IW) Swath were used at VV polarization. The three different subplots of 1 m2 area were taken for the measurement of crop parameters at every growth stage. In total, 73 samples were taken as the training data-sets and 39 samples were taken as testing data-sets. The highest sensitivity (adj. R2 = 0.95579) of backscattering with VWC was found using RFR algorithm, whereas the lowest sensitivity (adj. R2 = 0.66201) was found for the PH using LR algorithm. Overall results indicate more accurate estimation of winter wheat parameters by the RFR algorithm followed by SVR, ANNR and LR algorithms. Numéro de notice : A2018-337 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1316781 Date de publication en ligne : 18/04/2017 En ligne : https://doi.org/10.1080/10106049.2017.1316781 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90551
in Geocarto international > vol 33 n° 9 (September 2018) . - pp 942 - 956[article]Complex-valued convolutional neural network and its application in polarimetric SAR image classification / Zhimian Zhang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 12 (December 2017)
[article]
Titre : Complex-valued convolutional neural network and its application in polarimetric SAR image classification Type de document : Article/Communication Auteurs : Zhimian Zhang, Auteur ; Haipeng Wang, Auteur ; Feng Xu, Auteur ; Ya-Qiu Jin, Auteur Année de publication : 2017 Article en page(s) : pp 7177 - 7188 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] apprentissage dirigé
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radar
[Termes IGN] réseau neuronal convolutifRésumé : (Auteur) Following the great success of deep convolutional neural networks (CNNs) in computer vision, this paper proposes a complex-valued CNN (CV-CNN) specifically for synthetic aperture radar (SAR) image interpretation. It utilizes both amplitude and phase information of complex SAR imagery. All elements of CNN including input-output layer, convolution layer, activation function, and pooling layer are extended to the complex domain. Moreover, a complex backpropagation algorithm based on stochastic gradient descent is derived for CV-CNN training. The proposed CV-CNN is then tested on the typical polarimetric SAR image classification task which classifies each pixel into known terrain types via supervised training. Experiments with the benchmark data sets of Flevoland and Oberpfaffenhofen show that the classification error can be further reduced if employing CV-CNN instead of conventional real-valued CNN with the same degrees of freedom. The performance of CV-CNN is comparable to that of existing state-of-the-art methods in terms of overall classification accuracy. Numéro de notice : A2017-770 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2743222 En ligne : https://doi.org/10.1109/TGRS.2017.2743222 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88810
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 12 (December 2017) . - pp 7177 - 7188[article]Incidence angle dependence of first-year sea ice backscattering coefficient in Sentinel-1 SAR Imagery over the kara sea / Marko P. Mäkynen in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)
[article]
Titre : Incidence angle dependence of first-year sea ice backscattering coefficient in Sentinel-1 SAR Imagery over the kara sea Type de document : Article/Communication Auteurs : Marko P. Mäkynen, Auteur ; Juha Karvonen, Auteur Année de publication : 2017 Article en page(s) : pp 6170 - 6181 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] angle d'incidence
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radar
[Termes IGN] régression linéaireRésumé : (Auteur) We have studied the incidence angle (θ0) dependence of the sea ice backscattering coefficient (0.°) for Sentinel-1 (S-1) extra wide (EW) mode dualpolarization (HH/HV) synthetic aperture radar (SAR) imagery acquired over the Kara Sea under winter and summer melting conditions. The determination of the 0.° versus θ0 dependence was based on SAR image pairs acquired on ascending and descending orbits over the same sea ice area with a short time difference. The SAR noise floor was subtracted from the HV images. From the image pairs 1.1 by 1.1 km windows representing level first-year ice (LFYI) and deformed first-year ice (DFYI) were manually selected, and a linear regression was fit between the resulting 0.° and θ0 differences of the windows to estimate the slope b1 (dB/1°) between 0.° and θ0. For example, under winter condition b1 for DFYI at HHand HV-polarizations was found to be -0.24 and -0.16 dB/1°, respectively, and b1 for LFYI at HH-polarization was -0.25 dB/1°. It was not possible to determine a reliable b1 for LFYI at HV due to a contamination effect of the S-1 noise floor. The b1 values at HH compared well with previous studies. They can be used to compensate the 0.° incidence angle variation in the S-1 EW SAR images with good accuracy. The HH b1 values are applicable to other S-1 imaging modes and other C-band SAR sensors like RADARSAT-2. Unfortunately, the HV b1 values are specific to the S-1 EW mode due to the noise floor problem. Numéro de notice : A2017-744 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2720664 En ligne : https://doi.org/10.1109/TGRS.2017.2720664 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88778
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 11 (November 2017) . - pp 6170 - 6181[article]An information fusion approach for PALSAR data to retrieve soil moisture / Ankita Jain in Geocarto international, vol 32 n° 9 (September 2017)
[article]
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)
[article]
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]Distance measure based change detectors for polarimetric SAR imagery / Yonghong Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 9 (September 2016)PermalinkThe impacts of building orientation on polarimetric orientation angle estimation and model-based decomposition for multilook polarimetric SAR data in urban areas / Hongzhong Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkSoil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data / Lian He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)PermalinkGLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring / Erwan Motte in Sensors, vol 16 n° 5 (May 2016)PermalinkCompressive sensing for multibaseline polarimetric SAR tomography of forested areas / Xinwu Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkFirst results from the GLORIE polarimetric GNSS-R airborne campaign dedicated to land parameters estimation / Erwan Motte (2016)PermalinkRadar based classification prior to biomass retrieval from P-Band SAR data / Pierre-Louis Frison (2016)PermalinkCorrecting distortion of polarimetric SAR data induced by ionospheric scintillation / Jun Su Kim in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkForest height estimation by means of Pol-InSAR data inversion : The role of the vertical wavenumber / Florian Kugler in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)PermalinkTerraSAR-X dual-pol time-series for mapping of wetland vegetation / Julie Betbeder in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)PermalinkRandom Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features / Peijun Du in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)PermalinkCompilation de données radar et optiques pour la cartographie des classes d'occupation du sol aux environs du système lacustre de Bizerte (Tunisie du Nord) / Ibtissem Amri in Photo interprétation, European journal of applied remote sensing, vol 51 n° 2 (juin 2015)PermalinkA multidimensional extension of the concept of coherence in polarimetric SAR interferometry / Jose Luis Alvarez-Perez in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkPolarimetric incoherent target decomposition by means of independent component analysis / Nikola Besic in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkPolarimetric SAR speckle filtering and the extended sigma filter / Jong-Sen Lee in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkCalibration of SAR polarimetric images by means of a covariance matching approach / Alberto Villa in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkMultibaseline polarimetric synthetic aperture radar tomography of forested areas using wavelet-based distribution compressive sensing / Lei Liang in Journal of applied remote sensing, vol 9 (2015)PermalinkRelating statistical characteristics of cross-polarized phase difference to speckle noise / Huimin Li in Journal of applied remote sensing, vol 9 (2015)PermalinkAssessment of the relevance of information derived from the unmixing of polarimetric radar images / Sébastien Giordano (2015)PermalinkDémélange d’images radar polarimétrique par séparation thématique de sources / Sébastien Giordano (2015)Permalink