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Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis / Haifa Tamiminia in Geocarto international, vol 38 n° inconnu ([01/01/2023])
[article]
Titre : Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis Type de document : Article/Communication Auteurs : Haifa Tamiminia, Auteur ; Bahram Salehi, Auteur ; Masoud Mahdianpari, Auteur ; et al., Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse d'image orientée objet
[Termes IGN] biomasse aérienne
[Termes IGN] boosting adapté
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification pixellaire
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Extreme Gradient Machine
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Landsat
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] New York (Etats-Unis ; état)
[Termes IGN] réserve naturelleRésumé : (auteur) Forest above-ground biomass (AGB) estimation provides valuable information about the carbon cycle. Thus, the overall goal of this paper is to present an approach to enhance the accuracy of the AGB estimation. The main objectives are to: 1) investigate the performance of remote sensing data sources, including airborne light detection and ranging (LiDAR), optical, SAR, and their combination to improve the AGB predictions, 2) examine the capability of tree-based machine learning models, and 3) compare the performance of pixel-based and object-based image analysis (OBIA). To investigate the performance of machine learning models, multiple tree-based algorithms were fitted to predictors derived from airborne LiDAR data, Landsat, Sentinel-2, Sentinel-1, and PALSAR-2/PALSAR SAR data collected within New York’s Adirondack Park. Combining remote sensing data from multiple sources improved the model accuracy (RMSE: 52.14 Mg ha−1 and R2: 0.49). There was no significant difference among gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGBoost) models. In addition, pixel-based and object-based models were compared using the airborne LiDAR-derived AGB raster as a training/testing sample. The OBIA provided the best results with the RMSE of 33.77 Mg ha−1 and R2 of 0.81 for the combination of optical and SAR data in the GBM model. Numéro de notice : A2022-331 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2071475 Date de publication en ligne : 27/04/2022 En ligne : https://doi.org/10.1080/10106049.2022.2071475 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100607
in Geocarto international > vol 38 n° inconnu [01/01/2023][article]Detection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM / Jiehua Cai in Engineering Geology, vol 305 (August 2022)
[article]
Titre : Detection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM Type de document : Article/Communication Auteurs : Jiehua Cai, Auteur ; Lu Zhang, Auteur ; Jie Dong, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 106730 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie des risques
[Termes IGN] déformation de surface
[Termes IGN] données lidar
[Termes IGN] données multisources
[Termes IGN] effondrement de terrain
[Termes IGN] géomorphologie
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image optique
[Termes IGN] image Sentinel-SAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] MNS lidar
[Termes IGN] MNS SRTM
[Termes IGN] séisme
[Termes IGN] Setchouan (Chine)
[Termes IGN] surveillance géologiqueRésumé : (auteur) On 8th August 2017, a catastrophic Ms. 7.0 earthquake with a focal depth of 20 km struck the Jiuzhaigou County in Sichuan Province, China. It exerted a strong influence on the slope stability within the surrounding areas and triggered numerous secondary geohazards including rockfalls and other co-seismic landslides, which incurred drastic surface changes, and thus can be easily identified from cloud-free high-resolution optical imagery. Most of such landslides became stabilized shortly after the earthquake while others moving very slowly for years. In contrast, some slopes were destabilized without significant surface change into slow-moving landslides, which may pose long-term potential threats to people's life and property. Therefore, it is crucial to accurately identify these slow-moving landslides and regularly monitor their post-seismic activity. In this study, we employed the synthetic aperture radar interferometry (InSAR) techniques to detect and monitor slow-moving landslides after the earthquake in the Jiuzhaigou area, and analyzed the impacts of the earthquake on these landslides through integration of multi-source data (InSAR, Lidar, optical image, and field survey). As a result, 16 slow-moving landslides were detected by InSAR in the Jiuzhaigou area, including several historical landslides. The results of time-series InSAR analyses enabled identification of three kinds of landslide evolution modes affected by the earthquake, i.e. acceleration of deformation of pre-existing landslides, reactivation of dormant landslide, and remobilization of earthquake-triggered landslide. Each mode is supported by detailed analyses of multi-source data. The results demonstrated that satellite InSAR combined with high-resolution Lidar and optical data can provide a cost-effective approach of post-earthquake geohazards detection and monitoring. Numéro de notice : A2022-469 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.enggeo.2022.106730 Date de publication en ligne : 28/05/2022 En ligne : https://doi.org/10.1016/j.enggeo.2022.106730 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100811
in Engineering Geology > vol 305 (August 2022) . - n° 106730[article]Fusion of optical, radar and waveform LiDAR observations for land cover classification / Huiran Jin in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)
[article]
Titre : Fusion of optical, radar and waveform LiDAR observations for land cover classification Type de document : Article/Communication Auteurs : Huiran Jin, Auteur ; Giorgos Mountrakis, Auteur Année de publication : 2022 Article en page(s) : pp 171 - 190 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse comparative
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion d'images
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Landsat-TM
[Termes IGN] image multitemporelle
[Termes IGN] occupation du solRésumé : (Auteur) Land cover is an integral component for characterizing anthropogenic activity and promoting sustainable land use. Mapping distribution and coverage of land cover at broad spatiotemporal scales largely relies on classification of remotely sensed data. Although recently multi-source data fusion has been playing an increasingly active role in land cover classification, our intensive review of current studies shows that the integration of optical, synthetic aperture radar (SAR) and light detection and ranging (LiDAR) observations has not been thoroughly evaluated. In this research, we bridged this gap by i) summarizing related fusion studies and assessing their reported accuracy improvements, and ii) conducting our own case study where for the first time fusion of optical, radar and waveform LiDAR observations and the associated improvements in classification accuracy are assessed using data collected by spaceborne or appropriately simulated platforms in the LiDAR case. Multitemporal Landsat-5/Thematic Mapper (TM) and Advanced Land Observing Satellite-1/ Phased Array type L-band SAR (ALOS-1/PALSAR) imagery acquired in the Central New York (CNY) region close to the collection of airborne waveform LVIS (Land, Vegetation, and Ice Sensor) data were examined. Classification was conducted using a random forest algorithm and different feature sets in terms of sensor and seasonality as input variables. Results indicate that the combined spectral, scattering and vertical structural information provided the maximum discriminative capability among different land cover types, giving rise to the highest overall accuracy of 83% (2–19% and 9–35% superior to the two-sensor and single-sensor scenarios with overall accuracies of 64–81% and 48–74%, respectively). Greater improvement was achieved when combining multitemporal Landsat images with LVIS-derived canopy height metrics as opposed to PALSAR features, suggesting that LVIS contributed more useful thematic information complementary to spectral data and beneficial to the classification task, especially for vegetation classes. With the Global Ecosystem Dynamics Investigation (GEDI), a recently launched LiDAR instrument of similar properties to the LVIS sensor now operating onboard the International Space Station (ISS), it is our hope that this research will act as a literature summary and offer guidelines for further applications of multi-date and multi-type remotely sensed data fusion for improved land cover classification. Numéro de notice : A2022-228 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.03.010 Date de publication en ligne : 17/03/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.03.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100214
in ISPRS Journal of photogrammetry and remote sensing > vol 187 (May 2022) . - pp 171 - 190[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2022051 SL Revue Centre de documentation Revues en salle Disponible 081-2022053 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2022052 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt An approach to extracting digital elevation model for undulating and hilly terrain using de-noised stereo images of Cartosat-1 sensor / Litesh Bopche in Applied geomatics, vol 14 n° 1 (March 2022)
[article]
Titre : An approach to extracting digital elevation model for undulating and hilly terrain using de-noised stereo images of Cartosat-1 sensor Type de document : Article/Communication Auteurs : Litesh Bopche, Auteur ; Priti P. Rege, Auteur Année de publication : 2022 Article en page(s) : pp 39 - 55 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] filtrage du bruit
[Termes IGN] image ALOS
[Termes IGN] image Cartosat-1
[Termes IGN] Inde
[Termes IGN] MNS ASTER
[Termes IGN] MNS SRTM
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle par fonctions rationnelles
[Termes IGN] modèle stéréoscopique
[Termes IGN] points homologuesRésumé : (auteur) A digital elevation model (DEM) is established as an essential geospatial dataset requisite for many topographical and environmental applications. The freely available DEMs have low spatial resolution (SR ≥ 30 m) and comprise considerable vertical errors. The vertical errors are worsened in the undulating and hilly or rugged terrain regions. In this research, we introduced a study to investigate the effect of the noise reduction filters on the accuracy and quality of the DEMs for undulating and hilly terrain regions. The main objectives are to extract a high-quality DEM without collecting physical data like ground control points. DEM generation using de-noised stereo images is carried out using Rational Polynomial Coefficients of Cartosat-1 sensor and Automated Tie Point (ATP) selection. The ATP selection and distribution on the stereo images play a significant role in the DEM accuracy. The present paper also provides information about the optimum number of ATPs used for different topographic conditions. The altitude value of extracted DEM through de-noised stereo images and freely accessible DEMs is compared with reference to the ground truth value of the study region. The 3-D surface profile map of the DEM is used for visual interpretation. Numéro de notice : A2022-216 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-021-00412-0 Date de publication en ligne : 26/11/2021 En ligne : https://doi.org/10.1007/s12518-021-00412-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100086
in Applied geomatics > vol 14 n° 1 (March 2022) . - pp 39 - 55[article]Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations / Caglar Bayik in Natural Hazards, vol 109 n° 1 (October 2021)
[article]
Titre : Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations Type de document : Article/Communication Auteurs : Caglar Bayik, Auteur ; Saygin Abdikan, Auteur ; Alpay Ozdemir, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1201 - 1220 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse diachronique
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] données géologiques
[Termes IGN] données GNSS
[Termes IGN] effondrement de terrain
[Termes IGN] image ALOS
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Istanbul (Turquie)
[Termes IGN] surveillance géologique
[Termes IGN] urbanisationRésumé : (auteur) This study aims to detect recent landslide displacements caused by geological structure of the region where there is intense urbanization using advanced Interferometric Synthetic Aperture Radar (InSAR) techniques and with Global Navigation Satellite Systems (GNSS) observations in the Beylikdüzü and Esenyurt districts in Istanbul megacity, Turkey. In this study, multiple satellites with different frequencies (C-band, L-band) and periodic GNSS observations were employed. For the entire peninsula, we processed 149 images from the ascending orbit, 144 images from the descending orbit of Sentinel-1 (C-Band) and 24 ALOS-2 (L-band) images from the ascending orbit. The evaluations were carried out in the period between 2015 and 2020 for Sentinel-1 imagery and 2015–2020 for ALOS-2 imagery respectively. Since the study area is covered by dense settlements, the Persistent Scatterer InSAR (PSI) technique was utilized to determine the landslide behaviors. According to the results, for both orbits of the Sentinel-1, the horizontal displacement and the vertical displacement were observed in the range of − 10 to 6 mm. Compared to the magnitude of displacement signal measured by Sentinel-1, ALOS-2 data has higher values due to the high surface penetration of the L-band. The results showed that most of the old landslide regions are reactivated. Horizontal movement derived through Sentinel-1 showed that the highest movement overlaps with old landslides. L-band ALOS-2 provided better spatial coverage of landslide movement than C-band Sentinel-1 data, especially at the rural Numéro de notice : A2021-752 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT/URBANISME Nature : Article DOI : 10.1007/s11069-021-04875-7 Date de publication en ligne : 20/06/2021 En ligne : https://doi.org/10.1007/s11069-021-04875-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98737
in Natural Hazards > vol 109 n° 1 (October 2021) . - pp 1201 - 1220[article]Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model / Yanan Du in International journal of applied Earth observation and geoinformation, vol 102 (October 2021)PermalinkConiferous and broad-leaved forest distinguishing using L-band polarimetric SAR data / Fang Shang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)PermalinkShoreline changes along Northern Ibaraki Coast after the great East Japan earthquake of 2011 / Quang Nguyen Hao in Remote sensing, vol 13 n° 7 (April-1 2021)PermalinkSpectral–spatial-aware unsupervised change detection with stochastic distances and support vector machines / Rogério Galante Negri in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkComplémentarité des images optiques Sentinel-2 avec les images radar Sentinel-1 et ALOS-PALSAR-2 pour la cartographie de la couverture végétale : application à une aire protégée et ses environs au Nord-Ouest du Maroc via trois algorithmes d’apprentissage automatique / Siham Acharki in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkOptimizing flood mapping using multi-synthetic aperture radar images for regions of the lower mekong basin in Vietnam / Vu Anh Tuan in European journal of remote sensing, vol 54 n° 1 (2021)PermalinkImpact of forest disturbance on InSAR surface displacement time series / Paula M. Bürgi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)PermalinkPermalinkL-band SAR for estimating aboveground biomass of rubber plantation in Java Island, Indonesia / Bambang H Trisasongko in Geocarto international, vol 35 n° 12 ([01/09/2020])PermalinkFusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)PermalinkSoil moisture estimation with SVR and data augmentation based on alpha approximation method / Wei Xu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkExtracting impervious surfaces from full polarimetric SAR images in different urban areas / Sara Attarchi in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)PermalinkEstimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model / Mikhail L. Uss in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkComplex deformation at shallow depth during the 30 October 2016 Mw6.5 Norcia earthquake: interferencebetween tectonic and gravity processes? / Arthur Delorme in Tectonics, vol 39 n° 2 (February 2020)PermalinkLandslide displacement mapping based on ALOS-2/PALSAR-2 data using image correlation techniques and SAR interferometry: application to the Hell-Bourg landslide (Salazie Circle, La Réunion Island) / Daniel Raucoules in Geocarto international, vol 35 n° 2 ([01/02/2020])PermalinkSome thoughts on measuring earthquake deformation using optical imagery / Min Huang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkThe "Incense Road" from Petra to Gaza: an analysis using GIS and Cost functions / Motti Zohar in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)PermalinkArtificial neural network models by ALOS PALSAR data for aboveground stand carbon predictions of pure beech stands: a case study from northern of Turkey / Alkan Günlü in Geocarto international, Vol 35 n° 1 ([02/01/2020])PermalinkEstimation et suivi de la ressource en bois en France métropolitaine par valorisation des séries multi-temporelles à haute résolution spatiale d'images optiques (Sentinel-2) et radar (Sentinel-1, ALOS-PALSAR) / David Morin (2020)PermalinkIdentification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data / Guo-Hui Yao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)PermalinkRegional-scale forest mapping over fragmented landscapes using global forest products and Landsat time series classification / Viktor Myroniuk in Remote sensing, vol 12 n° 1 (January 2020)PermalinkComparative analysis of the accuracy of surface soil moisture estimation from the C- and L-bands / Mohammad El Hajj in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)PermalinkMulti-sensor prediction of Eucalyptus stand volume: A support vector approach / Guilherme Silverio Aquino de Souza in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkGeometric accuracy improvement of WorldView‐2 imagery using freely available DEM data / Mateo Gašparović in Photogrammetric record, vol 34 n° 167 (September 2019)PermalinkPolarimétrie radar complète et partielle pour le suivi des surfaces terrestres / Pierre-Louis Frison in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)PermalinkGeneration of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar / Yang Lei in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)PermalinkPermalinkPolarimetric 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)PermalinkAccuracy assessment of different digital surface models / Ugur Alganci in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkActive tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan) / Benoit Deffontaines in Natural Hazards and Earth System Sciences, vol 18 n° 3 ([01/03/2018])PermalinkExploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area / Saygin Abdikan in Geocarto international, vol 33 n° 1 (January 2018)PermalinkBayesian data combination for the estimation of ionospheric effects in SAR interferograms / Giorgio Gomba in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (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)PermalinkCritical 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)PermalinkMise en place d'une méthode semi-automatique de cartographie de l'occupation des sols à partir d'images SAR polarimétriques / Monique Moine in Revue Française de Photogrammétrie et de Télédétection, n° 215 (mai - août 2017)PermalinkActive interseismic shallow deformation of the Pingting terraces (Longitudinal Valley – Eastern Taiwan) from UAV high-resolution topographic data combined with InSAR time series / Benoit Deffontaines in Geomatics, Natural Hazards and Risk, vol 8 (2017)PermalinkDetection of ground surface deformation caused by the 2016 Kumamoto earthquake by InSAR using ALOS-2 data / Basara Miyahara in Bulletin of the GeoSpatial Information authority of Japan, vol 64 (December 2016)PermalinkRelative importance analysis of Landsat, waveform LIDAR and PALSAR inputs for deciduous biomass estimation / Alyssa Endres in European journal of remote sensing, vol 49 n° 1 (2016)PermalinkInvestigation of ionospheric effects on SAR Interferometry (InSAR): A case study of Hong Kong / Wu Zhu in Advances in space research, vol 58 n° 4 (August 2016)PermalinkSource model from ALOS-2 ScanSAR of the 2015 Nepal earthquakes / Youtian Liu in Journal of applied geodesy, vol 10 n° 2 (June 2016)PermalinkToward operational compensation of ionospheric effects in SAR interferograms: the split-spectrum method / Giorgio Gomba in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)PermalinkApport de la télédétection radar satellitaire pour la cartographie de la forêt des Landes / Yousra Hamrouni (2016)PermalinkEstimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 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)PermalinkMeasuring urban volume: geospatial technique and application / Ronald C. Estoque in Tsukuba geoenvironmental sciences, vol 11 ([01/12/2015])PermalinkForest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI / Yuanwei Qin in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)PermalinkMultitemporal fluctuations in L-Band Backscatter from a japanese forest / Manabu Watanabe in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)PermalinkTropical forest canopy cover estimation using satellite imagery and airborne lidar reference data / Lauri Korhonen in Silva fennica, vol 49 n° 5 ([01/10/2015])PermalinkUnderstanding the effects of ALS pulse density for metric retrieval across diverse forest types / Phil Wilkes in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 8 (August 2015)PermalinkCartographie du châtaignier en Alsace par imagerie satellite multi-date / Colette Meyer in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)PermalinkSavannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data / Laven Naidoo 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)PermalinkMapping aboveground biomass in northern japanese forests using the ALOS PRISM digital surface model / Takeshi Motohka in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 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)PermalinkTemporal decorrelation in L-, C-, and X-band satellite radar interferometry for pasture on drained cs / Yu Morishita in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkApport de la télédétection radar polarimétrique pour la discrimination et la distribution spatiale des groupements végétaux / Florence Palla (2015)PermalinkRetrieving three-dimensional displacement fields of mining areas from a single InSAR pair / Zhi Wei Li in Journal of geodesy, vol 89 n° 1 (January 2015)PermalinkTopographic correction of ALOS-PALSAR images using InSAR-derived DEM / Anup Das in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)PermalinkModelling electrical conductivity of soil from backscattering coefficient of microwave remotely sensed data using artificial neural network / Walaiporn Phonphan in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)PermalinkLand cover and soil type mapping from spaceborne PolSAR Data at L-Band with probabilistic neural network / Oleg Antropov in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkQuantification of L-band InSAR coherence over volcanic areas using LiDAR and in situ measurements / Mélanie Arab-Sedze in Remote sensing of environment, vol 152 (September 2014)PermalinkAdvanced differential interferometry synthetic aperture radar techniques for deformation monitoring: a review on sensors and recent research development / O. Idrees Mohammed in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)PermalinkCoastal and marine ecological changes and fish cage culture development in Phu Quoc, Vietnam (2001 to 2011) / Diep Thi Hong Nguyen in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)PermalinkAn inventory of the above ground biomass in the Mau Forest Ecosystem, Kenya / Mwangi James Kinyanjui in Open journal of forestry, vol 4 n° 10 (July 2014)PermalinkAn effective morphological index in automatic recognition of built-up area suitable for high spatial resolution images as ALOS and SPOT data / Bo Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)PermalinkMonitoring coastal morphological changes using remote sensing and GIS in the Red river delta area, Vietnam / Si Son Tong in Photo interprétation, European journal of applied remote sensing, vol 50 n° 2 (juin 2014)PermalinkMultiple-entity based classification of airborne laser scanning data in urban areas / S. Xu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkStudy on the polarimetric characteristics of the Lop Nur arid area using PolSAR data / Zhihong Gao in Journal of applied remote sensing, vol 8 (2014)PermalinkAn innovative support vector machine based method for contextual image classification / Rogério Galante Negri in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkRetrieval of tropical forest biomass information from ALOS PALSAR data / Mahmudur Rahman in Geocarto international, vol 28 n° 5-6 (August - October 2013)PermalinkContribution des données ALOS et Landsat dans la cartographie et l'analyse des linéaments dans le Sahel central (Maroc occidental) / Adnane Habib in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)PermalinkInSAR-derived coseismic deformation of the 2010 Southeastern Iran earthquake (M6.5) and its relationship with the tectonic background in the South of Lut Block / Tomokazu Kobayashi in Bulletin of the GeoSpatial Information authority of Japan, vol 60 (March 2013)PermalinkDual-Polarimetric signatures of vegetation – a case study Biebrza / Dariusz Ziolkowski in Geoinformation issues, vol 5 n° 1 (2013)PermalinkAn underground-mining detection system based on DInSAR / Z. Hu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 2 (January 2013)PermalinkEvaluation de l'apport de la télédétection radar pour la cartographie des végétations dans le Parc du Pilat / Cécile Cazals (2013)PermalinkApports des données ALOS PALSAR polarimétriques à la détection des zones humides littorales (Sassandra, Côte d'Ivoire) / Kouakou Hervé Kouassi in Photo interprétation, European journal of applied remote sensing, vol 48 n° 4 (décembre 2012)Permalink3D coseismic displacement of 2010 Darfield, New Zealand earthquake estimated from multi-aperture InSAR and D-InSAR measurements / J. Hu in Journal of geodesy, vol 86 n° 11 (November 2012)PermalinkExtraction de MNT à partir de paires ou triplets PRISM / Valerio Baiocchi in Géomatique expert, n° 89 (01/11/2012)PermalinkMapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery / J. Dong in ISPRS Journal of photogrammetry and remote sensing, vol 74 (Novembrer 2012)PermalinkMonitoring ground subsidence in Shanghai maglev area using two kinds of SAR data / J. Wu in Journal of applied geodesy, vol 6 n° 3-4 (November 2012)PermalinkDetecting depolarized targets using a new geometrical perturbation filter / Armando Marino in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 1 (October 2012)PermalinkQuantifying deforestation in the Brazilian Amazon using advanced land observing satellite phased array L-band synthetic aperture radar (ALOS PALSAR) and shuttle imaging radar (SIR)-C data / M. Rahman in Geocarto international, vol 27 n° 6 (October 2012)PermalinkA comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region / Dong Lu ; E. Moran ; et al. in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)PermalinkIonospheric artifacts in simultaneous L-band InSAR and GPS observations / J. Chen in IEEE Transactions on geoscience and remote sensing, vol 50 n° 4 (April 2012)PermalinkPotential of texture measurements of two-date dual polarization PALSAR data for the improvement of forest biomass estimation / M. Sarker in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)PermalinkCharacterization of forests and deforestation in Cambodia using ALOS/PALSAR observation / R. Avtar in Geocarto international, vol 27 n° 2 (March 2012)PermalinkRelative radiometric correction of multi-temporal ALOS AVNIR-2 data for the estimation of forest attributes / Q. Xu in ISPRS Journal of photogrammetry and remote sensing, vol 68 (March 2012)PermalinkJoint processing of Landsat and ALOS-PALSAR data for forest mapping and monitoring / E. Lehmann in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkLong-term consecutive DInSAR for volume change estimation of land deformation / S. Sumantyo in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkThe crustal deformation and fault model of the 2011 off the Pacific coast of Tohoku earthquake / T. Imakiire in Bulletin of the GeoSpatial Information authority of Japan, vol 59 (December 2011)PermalinkElectromagnetic land surface classification through integration of optical and radar remote sensing data / J. Baek in IEEE Transactions on geoscience and remote sensing, vol 49 n° 4 (April 2011)PermalinkOrthorectification of VHR optical satellite data exploiting the geometric accuracy of TerraSAR-X data / Peter Reinartz in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)PermalinkPrecise georeferencing of long strips of ALOS imagery / Clive Simpson Fraser in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 1 (January 2011)Permalink