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Semantic segmentation of land cover from high resolution multispectral satellite images by spectral-spatial convolutional neural network / Ekrem Saralioglu in Geocarto international, vol 37 n° 2 ([15/01/2022])  

Public [article]  inGeocarto international > vol 37 n° 2 [15/01/2022] . - pp 657 - 677 Titre : Semantic segmentation of land cover from high resolution multispectral satellite images by spectral-spatial convolutional neural network Type de document : Article/Communication Auteurs : Ekrem Saralioglu, Auteur ; Oguz Gungor, Auteur Année de publication : 2022 Article en page(s) : pp 657 - 677 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] image Ikonos [Termes IGN] image multibande [Termes IGN] image Pléiades-HR [Termes IGN] image Worldview [Termes IGN] occupation du sol [Termes IGN] segmentation sémantique [Termes IGN] Turquie Résumé : (auteur) Research to improve the accuracy of very high-resolution satellite image classification algorithms is still one of the hot topics in the field of remote sensing. Successful results of deep learning methods in areas such as image classification and object detection have led to the application of these methods to remote sensing problems. Recently, Convolutional Neural Networks (CNNs) are among the most common deep learning methods used in image classification, however, the use of CNN’s in satellite image classification is relatively new. Due to the high computational complexity of 3D CNNs, which aim to extract both spatial and spectral information, 2D CNNs focussing on the extraction of spatial information are often preferred. High-resolution satellite images, however, contain crucial spectral information as well as spatial information. In this study, a 3D-2D CNN model using both spectral and spatial information was applied to extract more accurate land cover information from very high-resolution satellite images. The model was applied on a Worldview-2 satellite image including agricultural product areas such as tea, hazelnut groves and land use classes such as buildings and roads. The results of the CNN based model were also compared against those of the Support Vector Machine (SVM) and Random Forest (RF) algorithms. The post-classification accuracies were obtained using 800 control points generated by a web interface created for crowdsourcing purposes. The classification accuracy was 95.6% for the 3D-2D CNN model, 89.2% for the RF and 86.4% for the SVM. Numéro de notice : A2022-305 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10106049.2020.1734871 Date de publication en ligne : 04/03/2020 En ligne : https://doi.org/10.1080/10106049.2020.1734871 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100379 [article]

An improved approach based on terrain-dependent mathematical models for georeferencing pushbroom satellite images / Behrooz Moradi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 1 (January 2021) . - pp 53 - 69 Titre : An improved approach based on terrain-dependent mathematical models for georeferencing pushbroom satellite images Type de document : Article/Communication Auteurs : Behrooz Moradi, Auteur ; Mohammad Javad Valadan Zoej, Auteur ; Sayad Yaghoobi, Auteur ; Somayeh Yavari, Auteur Année de publication : 2021 Article en page(s) : pp 53 - 69 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] géoréférencement [Termes IGN] image à haute résolution [Termes IGN] image Geoeye [Termes IGN] image Ikonos [Termes IGN] Iran [Termes IGN] modèle géométrique de prise de vue [Termes IGN] modèle par fonctions rationnelles [Termes IGN] modélisation 3D Résumé : (Auteur) Recently, linear features in remotely sensed imagery have gained much attention because of their unique characteristics compared to other control features. For georeferencing high-resolution satellite images, the observations in the mathematical equations (slope and y-intercept) of the corresponding control lines in the two spaces are considered the same based on recent studies. However, the use of such assumptions causes error and reduces the accuracy of registration. The aim of this article is to present a methodology based on a quasi-observation assumption in the mathematical equations in the process of georeferencing. Experimental results for IKONOS and GeoEye images over two different cities of Iran indicate that the quasi-observation assumption can increase the average registration accuracy up to 48.96% and 24.77% using 3D-affine and rational function models, respectively. This improvement in accuracy increases the processing time by 31.48% over traditional approaches; however, the proposed methodology can be regarded as an efficient solution. Numéro de notice : A2021-057 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.1.53 Date de publication en ligne : 01/01/2021 En ligne : https://doi.org/10.14358/PERS.87.1.53 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96768 [article]

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A review of image fusion techniques for pan-sharpening of high-resolution satellite imagery / Farzaneh Dadrass Javan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 101 - 117 Titre : A review of image fusion techniques for pan-sharpening of high-resolution satellite imagery Type de document : Article/Communication Auteurs : Farzaneh Dadrass Javan, Auteur ; Farhad Samadzadegan, Auteur ; Soroosh Mehravar, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 101 - 117 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] affinage d'image [Termes IGN] analyse de variance [Termes IGN] fusion d'images [Termes IGN] image Kompsat [Termes IGN] image à haute résolution [Termes IGN] image Geoeye [Termes IGN] image Ikonos [Termes IGN] image multibande [Termes IGN] image panchromatique [Termes IGN] image Pléiades-HR [Termes IGN] image Quickbird [Termes IGN] image Worldview [Termes IGN] netteté [Termes IGN] pansharpening (fusion d'images) [Termes IGN] pouvoir de résolution spectrale Résumé : (auteur) Pan-sharpening methods are commonly used to synthesize multispectral and panchromatic images. Selecting an appropriate algorithm that maintains the spectral and spatial information content of input images is a challenging task. This review paper investigates a wide range of algorithms, including 41 methods. For this purpose, the methods were categorized as Component Substitution (CS-based), Multi-Resolution Analysis (MRA), Variational Optimization-based (VO), and Hybrid and were tested on a collection of 21 case studies. These include images from WorldView-2, 3 & 4, GeoEye-1, QuickBird, IKONOS, KompSat-2, KompSat-3A, TripleSat, Pleiades-1, Pleiades with the aerial platform, and Deimos-2. Neural network-based methods were excluded due to their substantial computational requirements for operational mapping purposes. The methods were evaluated based on four Spectral and three Spatial quality metrics. An Analysis Of Variance (ANOVA) was used to statistically compare the pan-sharpening categories. Results indicate that MRA-based methods performed better in terms of spectral quality, whereas most Hybrid-based methods had the highest spatial quality and CS-based methods had the lowest results both spectrally and spatially. The revisited version of the Additive Wavelet Luminance Proportional Pan-sharpening method had the highest spectral quality, whereas Generalized IHS with Best Trade-off Parameter with Additive Weights showed the highest spatial quality. CS-based methods generally had the fastest run-time, whereas the majority of methods belonging to MRA and VO categories had relatively long run times. Numéro de notice : A2021-014 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.11.001 Date de publication en ligne : 21/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.11.001 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96418 [article]

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A novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 509 - 520 Titre : A novel method for separating woody and herbaceous time series Type de document : Article/Communication Auteurs : Qiang Zhou, Auteur ; Shuguang Liu, Auteur ; Michael J Hill, Auteur Année de publication : 2019 Article en page(s) : pp 509 - 520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Afrique australe [Termes IGN] bois [Termes IGN] extraction de la végétation [Termes IGN] image à haute résolution [Termes IGN] image Ikonos [Termes IGN] image Landsat-SWIR [Termes IGN] image Terra-MODIS [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] plante herbacée [Termes IGN] savane [Termes IGN] série temporelle [Termes IGN] variation saisonnière Résumé : (auteur) Mapping the spatial distribution of woody and herbaceous vegetation in high temporal resolution in savannas would be beneficial for modeling interrelationships between trees and grasses, and monitoring fuel loads and biomass for livestock. In this study, we developed a frequency decomposition method to separate woody and herbaceous vegetation components using Normalized Difference Vegetation Index (NDVI) time series. The results were validated using fractional cover data derived from high-resolution images. The validation revealed a close relationship between our decomposed NDVI and corresponding fractional cover (R2 = 0.55 and 0.64 for woody and herbaceous components, respectively). We examined the spatial and temporal patterns of the decomposed NDVI, where woody and herbaceous NDVI showed different responses to precipitation. The methods proposed in this study can be used to separate the woody and herbaceous NDVI time series as an alternative approach for monitoring woody and herbaceous vegetation interrelationships related to climatic drivers. Numéro de notice : A2019-259 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.509 Date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.509 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93062 [article]

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Intersensor statistical matching for pansharpening : theoretical issues and practical solutions / Luciano Alparone in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4682 - 4695 Titre : Intersensor statistical matching for pansharpening : theoretical issues and practical solutions Type de document : Article/Communication Auteurs : Luciano Alparone, Auteur ; Andrea Garzelli, Auteur ; Gemine Vivone, Auteur Année de publication : 2017 Article en page(s) : pp 4682 - 4695 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] appariement d'histogramme [Termes IGN] appariement d'images [Termes IGN] image Ikonos [Termes IGN] image multibande [Termes IGN] image multicapteur [Termes IGN] image panchromatique [Termes IGN] image Worldview [Termes IGN] pansharpening (fusion d'images) [Termes IGN] résolution multiple Résumé : (Auteur) In this paper, the authors investigate the statistical matching of the panchromatic (Pan) image to the multispectral (MS) bands, also known as the histogram matching, for the two main classes of pansharpening methods, i.e., those based on component substitution (CS) or spectral methods and those based on multiresolution analysis (MRA) or spatial methods. Also, hybrid methods combining CS with MRA, like the widespread additive wavelet luminance proportional (AWLP), are investigated. It is shown that all spectral, spatial, and hybrid methods must perform a dynamics matching of the enhancing Pan to the individual MS bands for MRA or a combination of them (the component that shall be substituted) for CS. For hybrid methods, the problem is more complex and both types of histogram matching may be suitable. Such an intersensor balance may be either explicit or implicitly performed by the detail-injection model, e.g., the popular projective and multiplicative injection models. An experimental setup exploiting IKONOS and WorldView-2 data sets demonstrates that a correct histogram matching is the key to attain extra performance from established methods. As a first result of this paper, the AWLP method has been revisited and its performance significantly improved by simply performing the histogram matching of Pan to the individual MS bands, rather than to the intensity component, thereby losing the original proportionality feature. Numéro de notice : A2017-502 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2697943 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2697943 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86447 [article]

RPC-based coregistration of VHR imagery for urban change detection / Shabnam Jabari in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)  

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An intelligent geospatial processing unit for image classification based on geographic vector agents (GVAs) / Kambiz Borna in Transactions in GIS, vol 20 n° 3 (June 2016)  

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Earth observation-based multi-scale impact assessment of internally displaced person (IDP) camps on wood resources in Zalingei, Darfur / Kristin Spröhnle in Geocarto international, vol 31 n° 5 - 6 (May - June 2016)  

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Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation / Fateme Ameri in Photogrammetric record, vol 30 n° 152 (December 2015 - February 2016)  

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See the wood and the trees / Stratos Stylianidis in GEO: Geoconnexion international, vol 14 n° 4 (April 2015)

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Geostatistical methods for predicting soil moisture continuously in a subalpine basin / Katherine E. Williams in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 4 (April 2014)  

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Génération de modèles numériques de surface et détection de changements 3D à partir d'imagerie satellite stéréoscopique très haute résolution / Cyrielle Guerin (2014)  

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A combined object- and pixel-based image analysis framework for urban land cover classification of VHR imagery / Bahram Salehi in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)  

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Building a forward-mode three-dimensional reflectance model for topographic normalization of High-Resolution (1–5 m) imagery: validation phase in a forested environment / Stéphane Couturier in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)  

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Cartographie et suivi de la densité des arbres de l'arganeraie (Sud-Ouest du Maroc) à partir d'images de télédétection à haute résolution spatiale / Mbark Aouragh in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)  

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