Catalogue en ligne IGN

Bulletin Imagerie

Bulletin-imagerie

Improving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency / Jiaqi Tian in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)

Public

[article]
inISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 29 - 44

Titre :	Improving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency
Type de document :	Article/Communication
Auteurs :	Jiaqi Tian, Auteur ; Xiaolin Zhu, Auteur ; Jin Chen, Auteur ; et al., Auteur
Année de publication :	2021
Article en page(s) :	pp 29 - 44
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications de télédétection [Termes IGN] Enhanced vegetation index [Termes IGN] filtrage du bruit [Termes IGN] image Terra-MODIS [Termes IGN] indice de végétation [Termes IGN] lissage de données [Termes IGN] nébulosité [Termes IGN] phénologie [Termes IGN] série temporelle
Résumé :	(auteur) Vegetation phenology can be extracted from vegetation index (VI) time series of satellite data. The maximum value composite (MVC) procedure and smoothing filters have been conventionally used as standard methods to exclude noises in the VI time series before extracting the vegetation phenology [e.g., National Aeronautics and Space Administration (NASA) VNP22Q2 and United States Geological Survey (USGS) MCD12Q2 phenology products]. However, it is unclear how to optimize the MVC and smoothing filters to produce the most accurate phenology metrics given that cloud frequency varies spatially. This study designed two simulation experiments, namely (1) using only the MVC and (2) using the MVC and smoothing filters together to smooth the enhanced vegetation index (EVI) time series for detecting spring phenology, i.e., start of season (SOS), over the northern hemisphere (north of 30°N) on a 5° × 5° grid cell basis by the inflection point and relative threshold algorithms. The results revealed that (1) the inappropriate selection of MVC periods (e.g., too short or too long) affected the accuracy of the SOS extracted by both phenology detection algorithms; (2) a filtering process with optimal parameters can reduce the effects of the MVC period on SOS extraction to a considerable extent, i.e., 65% and 61% for iterative Savitzky–Golay (SG) and penalized cubic splines (SP) filters, respectively; (3) optimal parameters for both the MVC and smoothing filters showed significant spatial heterogeneity; and (4) validation with ground PhenoCam data indicated that optimal parameters of the MVC and smoothing filters can produce more accurate results than official vegetation phenology products that use uniform parameters. Specifically, the R2 values of the NASA product and the USGS product were 0.58 and 0.67, which were increased to 0.70 and 0.81, respectively, by the optimal smoothing process. Optimal parameters of the MVC and smoothing filters provided by this study in each 5° × 5° sub-region may help future studies to improve the accuracy of phenology detection from satellite VI time series.
Numéro de notice :	A2021-653
Affiliation des auteurs :	non IGN
Thématique :	FORET/IMAGERIE
Nature :	Article
nature-HAL :	ArtAvecCL-RevueIntern
DOI :	10.1016/j.isprsjprs.2021.08.003
date de publication en ligne :	14/08/2021
En ligne :	https://doi.org/10.1016/j.isprsjprs.2021.08.003
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98383

[article]

Integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images / Yijie Tang in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)

Public

[article]
inISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 130 - 150

Titre :	Integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images
Type de document :	Article/Communication
Auteurs :	Yijie Tang, Auteur ; Qunming Wang, Auteur ; Xiaohua Tong, Auteur ; et al., Auteur
Année de publication :	2021
Article en page(s) :	pp 130 - 150
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image optique [Termes IGN] données spatiotemporelles [Termes IGN] fusion d'images [Termes IGN] image multibande [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-OLCI [Termes IGN] pouvoir de résolution géométrique [Termes IGN] réduction d'échelle [Termes IGN] réflectance
Résumé :	(auteur) Sentinel-3 is a newly launched satellite implemented by the European Space Agency (ESA) for global observation. The Ocean and Land Colour Imager (OLCI) sensor onboard Sentinel-3 provides 21 band images with a fine spectral resolution and is of great value for ocean, land and atmospheric monitoring. The two platforms (Sentinel-3A and -3B) can provide OLCI images at an almost daily temporal resolution. The coarse spatial resolution of the 21 band OLCI images (i.e., 300 m), however, limits greatly their utility for local, precise monitoring. Sentinel-2, another satellite provided by ESA, carries the Multispectral Imager (MSI) sensor which can supply much finer spatial resolution (e.g., 10 m and 20 m) images. This paper introduces a new fusion framework integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images, which has two parts. Based on bands with similar wavelengths (i.e., bands 2, 3, 4 and 8a for Sentinel-2 and bands Oa4, Oa6, Oa8 and Oa17 for Sentinel-3), the four Sentinel-3 bands are first downscaled to the spatial resolution of Sentinel-2 images by applying spatio-temporal fusion to Sentinel-2 MSI and Sentinel-3 OLCI images. Then, to take full advantage of all 21 available OLCI bands of the Sentinel-3 images, the extended image pair-based spatio-spectral fusion (EIPSSF) method is proposed in this paper to downscale the other 17 bands. EIPSSF is performed based on the new concept of the extended image pair (EIP) and by exploiting existing spatio-temporal fusion approaches. The framework consisting of spatio-temporal and spatio-spectral fusion is entirely general, which provides a practical solution for comprehensive downscaling of Sentinel-3 OLCI images for fine spatial, temporal and spectral resolution monitoring.
Numéro de notice :	A2021-654
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Article
nature-HAL :	ArtAvecCL-RevueIntern
DOI :	10.1016/j.isprsjprs.2021.08.012
date de publication en ligne :	24/08/2021
En ligne :	https://doi.org/10.1016/j.isprsjprs.2021.08.012
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98384

[article]

Investigating operational country-level crop monitoring with Sentinel~1 and~2 imagery / Nicolas David in Remote sensing letters, vol 12 n° 10 (October 2021)

Public

[article]
inRemote sensing letters > vol 12 n° 10 (October 2021) . - pp 970 - 982

Titre :	Investigating operational country-level crop monitoring with Sentinel~1 and~2 imagery
Type de document :	Article/Communication
Auteurs :	Nicolas David , Auteur ; Sébastien Giordano , Auteur ; Clément Mallet , Auteur
Année de publication :	2021
Projets :	MAESTRIA / Mallet, Clément
Article en page(s) :	pp 970 - 982
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image mixte [Termes IGN] chaîne de traitement [Termes IGN] France (administrative) [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] politique agricole commune [Termes IGN] surveillance agricole
Résumé :	(auteur) In this paper, we propose an operational solution for the yearly classification of crop parcels at national scale (namely France) for Land Parcel Identification System updating, under the Common Agricultural Policy (CAP) umbrella. Our pipeline is based on the ι2 open-source framework and fed with both time series of Sentinel-1 radar and Sentinel-2 optical images, with complementary contributions. Three conceivable scenarios are investigated with two sets of nomenclatures (17 and 43 classes): early, on-line, and late classifications. Experiments performed on 2017 show very satisfactory results (82–97%), locally almost on-par with state-of-the-art deep-based methods. We can conclude our framework offers a strong basis for country-scale operational deployment for 2020+CAP.
Numéro de notice :	A2021-600
Affiliation des auteurs :	UGE-LaSTIG (2020- )
Thématique :	IMAGERIE/INFORMATIQUE
Nature :	Article
nature-HAL :	ArtAvecCL-RevueIntern
DOI :	10.1080/2150704X.2021.1950940
En ligne :	https://doi.org/10.1080/2150704X.2021.1950940
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98222

[article]

Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation / Peng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)

Public

[article]
inISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 14 - 28

Titre :	Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation
Type de document :	Article/Communication
Auteurs :	Peng Liu, Auteur ; Zhenhong Li, Auteur ; Shicheng Wang, Auteur ; et al., Auteur
Année de publication :	2021
Article en page(s) :	pp 14 - 28
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse des mélanges spectraux [Termes IGN] chevauchement [Termes IGN] Chine [Termes IGN] discontinuité [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] interféromètrie par radar à antennes synthétiques multiple [Termes IGN] modèle numérique de surface [Termes IGN] ombre [Termes IGN] segmentation [Termes IGN] semis de points
Résumé :	(auteur) Staring spotlight images with a spatial resolution of up to tens of centimeters are good data sources for urban applications including displacement mapping. However, phase discontinuities, layover, and shadowing effect are also associated with staring spotlight interferograms, adding to the difficulties in height estimation and spatial phase unwrapping. The scattering mechanism of the staring spotlight images in the urban environment is complicated, thus it is difficult to simulate and remove the reference height of staring spotlight interferograms directly. In addition, global spatial phase unwrapping networks tend to smooth phase discontinuities. With the aim of implementing height estimation and phase unwrapping for TerraSAR-X Staring Spotlight interferograms, a workflow for phase unmixing of TerraSAR-X staring spotlight interferograms is proposed in this paper. The PS height is estimated in the baseline domain rather than the spatial domain. Taking into account the length and height change of each connection, the spatial phase unwrapping network is adjusted and segmented into isolated networks. The connected components of the adjusted spatial phase unwrapping network can be identified using graph theory. Spatial phase unwrapping is implemented in individual networks. The unfolded height phase is separated from the unwrapped phase, and the remaining phase is deformation dominated. Compared with the traditional global spatial phase unwrapping method, this study demonstrates the feasibility of the proposed least squares parameter search and graph partition based workflow in urban area, for phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation, as evidenced by external LiDAR DSM and temperature records.
Numéro de notice :	A2021-652
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Article
nature-HAL :	ArtAvecCL-RevueIntern
DOI :	10.1016/j.isprsjprs.2021.08.007
date de publication en ligne :	14/08/2021
En ligne :	https://doi.org/10.1016/j.isprsjprs.2021.08.007
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98382

[article]

Landslide susceptibility prediction based on image semantic segmentation / Bowen Du in Computers & geosciences, vol 155 (October 2021)

Public

[article]
inComputers & geosciences > vol 155 (October 2021) . - n° 104860

Titre :	Landslide susceptibility prediction based on image semantic segmentation
Type de document :	Article/Communication
Auteurs :	Bowen Du, Auteur ; Zirong Zhao, Auteur ; Xiao Hu, Auteur ; et al., Auteur
Année de publication :	2021
Article en page(s) :	n° 104860
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image optique [Termes IGN] aléa [Termes IGN] apprentissage automatique [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] effondrement de terrain [Termes IGN] image captée par drone [Termes IGN] modèle de simulation [Termes IGN] prévention des risques [Termes IGN] segmentation sémantique
Résumé :	(auteur)
Numéro de notice :	A2021-683
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Article
DOI :	10.1016/j.cageo.2021.104860
date de publication en ligne :	16/06/2021
En ligne :	https://doi.org/10.1016/j.cageo.2021.104860
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98408

[article]

Quantifying historical landscape change with repeat photography: an accuracy assessment of geospatial data obtained through monoplotting / Ulrike Bayr in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)

Public

[article]
inInternational journal of geographical information science IJGIS > vol 35 n° 10 (October 2021) . - pp 2026 - 2046

Titre :	Quantifying historical landscape change with repeat photography: an accuracy assessment of geospatial data obtained through monoplotting
Type de document :	Article/Communication
Auteurs :	Ulrike Bayr, Auteur
Année de publication :	2021
Article en page(s) :	pp 2026 - 2046
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse diachronique [Termes IGN] analyse du paysage [Termes IGN] angle d'incidence [Termes IGN] détection de changement [Termes IGN] données anciennes [Termes IGN] données multitemporelles [Termes IGN] image oblique [Termes IGN] modèle numérique de terrain [Termes IGN] monorestitution [Termes IGN] Norvège [Termes IGN] orthoimage géoréférencée [Termes IGN] photographie aérienne [Termes IGN] photographie terrestre [Termes IGN] point d'appui [Termes IGN] précision des données
Résumé :	(auteur) Traditional landscape photographs reaching back until the second half of the nineteenth century represent a valuable image source for the study of long-term landscape change. Due to the oblique perspective and the lack of geographical reference, landscape photographs are hardly used for quantitative research. In this study, oblique landscape photographs from the Norwegian landscape monitoring program are georeferenced using the WSL Monoplotting Tool with the aim of evaluating the accuracy of point and polygon features. In addition, the study shows how the resolution of the chosen digital terrain model and other factors affect accuracy. Points mapped on the landscape photograph had a mean displacement of 1.52 m from their location on a corresponding aerial photograph, while mapped areas deviated on average 5.6% in size. The resolution of the DTM, the placement of GCPs and the angle of incidence were identified as relevant factors to achieve accurate geospatial data. An example on forest expansion at the abandoned mountain farm Flysetra in Mid-Norway demonstrates how repeat photography facilitates the georectification process in the absence of reliable ground control points (GCPs) in very old photographs.
Numéro de notice :	A2021-656
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Article
nature-HAL :	ArtAvecCL-RevueIntern
DOI :	10.1080/13658816.2021.1871910
date de publication en ligne :	20/01/2021
En ligne :	https://doi.org/10.1080/13658816.2021.1871910
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98392

[article]

Early detection of pine wilt disease using deep learning algorithms and UAV-based multispectral imagery / Run Yu in Forest ecology and management, vol 497 (1 October 2021)

Public

[article]
inForest ecology and management > vol 497 (1 October 2021) . - n° 119493

Titre :	Early detection of pine wilt disease using deep learning algorithms and UAV-based multispectral imagery
Type de document :	Article/Communication
Auteurs :	Run Yu, Auteur ; Youqing Luo, Auteur ; Quan Zhou, Auteur ; et al., Auteur
Année de publication :	2021
Article en page(s) :	n° 119493
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] dépérissement [Termes IGN] image captée par drone [Termes IGN] image multibande [Termes IGN] maladie phytosanitaire [Termes IGN] milieu tropical [Termes IGN] peuplement mélangé [Termes IGN] Pinus (genre) [Termes IGN] Pinus massoniana [Termes IGN] réflectance spectrale [Termes IGN] Ulmus (genre)
Résumé :	(auteur) Pine wilt disease (PWD) is a global devastating threat to forest ecosystems. Therefore, a feasible and effective approach to precisely monitor PWD infection is indispensable, especially at the early stages. However, a precise definition of “early stage” and a rapid and high-efficiency method to detect PWD infection have not been well established. In this study, we systematically divided the PWD infection into green, early, middle, and late stages based on the needle color, the resin secretion, and whether the pine wood nematode (PWN) was carried. Simultaneously, an unmanned aerial vehicle (UAV) equipped with multispectral cameras was used to obtain images. Two target detection algorithms (Faster R-CNN and YOLOv4) and two traditional machine learning algorithms based on feature extraction (random forest and support vector machine) were employed to realize the recognition of infected pine trees. Moreover, we took into consideration of the influence of green broad-leaved trees on the identification of pine trees at the early stage of PWD infection. We obtained the following results: (1) the accuracy of Faster R-CNN (60.98–66.7%) was higher than that of YOLOv4 (57.07–63.55%), but YOLOv4 outperformed in terms of model size, processing speed, training time, and testing time; (2) although the traditional machine learning models had higher accuracy (73.28–79.64%), they were not able to directly identify the object from the images; (3) the accuracy of early detection of PWD infection showed an increase of 3.72–4.29%, from 42.36–44.59% to 46.08–48.88%, when broad-leaved trees were considered. In this study, the combination of UAV-based multispectral images and target detection algorithms allowed us to monitor the occurrence of PWD and obtain the distribution of infected trees at an early stage, which can provide technical support for the prevention and control of PWD.
Numéro de notice :	A2021-658
Affiliation des auteurs :	non IGN
Thématique :	FORET/IMAGERIE
Nature :	Article
nature-HAL :	ArtAvecCL-RevueIntern
DOI :	10.1016/j.foreco.2021.119493
En ligne :	https://doi.org/10.1016/j.foreco.2021.119493
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98395

[article]

Automatic building detection with polygonizing and attribute extraction from high-resolution images / Samitha Daranagama in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)

Public

[article]
inISPRS International journal of geo-information > vol 10 n° 9 (September 2021) . - n° 606

Titre :	Automatic building detection with polygonizing and attribute extraction from high-resolution images
Type de document :	Article/Communication
Auteurs :	Samitha Daranagama, Auteur ; Apichon Witayangkurn, Auteur
Année de publication :	2021
Article en page(s) :	n° 606
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de Douglas-Peucker [Termes IGN] apprentissage profond [Termes IGN] détection du bâti [Termes IGN] image à haute résolution [Termes IGN] image captée par drone [Termes IGN] lissage de courbe [Termes IGN] orthophotoplan numérique [Termes IGN] polygonation [Termes IGN] segmentation sémantique
Résumé :	(auteur) Buildings can be introduced as a fundamental element for forming a city. Therefore, up-to-date building maps have become vital for many applications, including urban mapping and urban expansion analysis. With the development of deep learning, segmenting building footprints from high-resolution remote sensing imagery has become a subject of intense study. Here, a modified version of the U-Net architecture with a combination of pre- and post-processing techniques was developed to extract building footprints from high-resolution aerial imagery and unmanned aerial vehicle (UAV) imagery. Data pre-processing with the logarithmic correction image enhancing algorithm showed the most significant improvement in the building detection accuracy for aerial images; meanwhile, the CLAHE algorithm improved the most concerning UAV images. This study developed a post-processing technique using polygonizing and polygon smoothing called the Douglas–Peucker algorithm, which made the building output directly ready to use for different applications. The attribute information, land use data, and population count data were applied using two open datasets. In addition, the building area and perimeter of each building were calculated as geometric attributes.
Numéro de notice :	A2021-684
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Article
DOI :	10.3390/ijgi10090606
date de publication en ligne :	14/09/2021
En ligne :	https://doi.org/10.3390/ijgi10090606
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98410

[article]

Binary space partitioning visibility tree for polygonal and environment light rendering / Hiroki Okuno in The Visual Computer, vol 37 n° 9 - 11 (September 2021)

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[article]
inThe Visual Computer > vol 37 n° 9 - 11 (September 2021) . - pp 2499 - 2511

Titre :	Binary space partitioning visibility tree for polygonal and environment light rendering
Type de document :	Article/Communication
Auteurs :	Hiroki Okuno, Auteur ; Kei Iwasaki, Auteur
Année de publication :	2021
Article en page(s) :	pp 2499 - 2511
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image optique [Termes IGN] arbre BSP [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] éclairage [Termes IGN] éclairement lumineux [Termes IGN] équation intégrale [Termes IGN] intensité lumineuse [Termes IGN] ombre [Termes IGN] polygone [Termes IGN] réflectance [Termes IGN] visibilité (optique)
Résumé :	(auteur) In this paper, we present a geometric approach to render shadows for physically based materials under polygonal light sources. Direct illumination calculation from a polygonal light source involves the triple product integral of the lighting, the bidirectional reflectance distribution function (BRDF), and the visibility function over the polygonal domain, which is computation intensive. To achieve real-time performance, work on polygonal light shading exploits analytical solutions of boundary integrals along the edges of the polygonal light at the cost of lacking shadowing effects. We introduce a hierarchical representation for the precomputed visibility function to retain the merits of closed-form solutions for boundary integrals. Our method subdivides the polygonal light into a set of polygons visible from a point to be shaded. Experimental results show that our method can render complex shadows with a GGX microfacet BRDF from polygonal light sources at interactive frame rates. In addition, our visibility representation can be easily incorporated into environment lighting.
Numéro de notice :	A2021-644
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Article
DOI :	10.1007/s00371-021-02181-8
date de publication en ligne :	14/06/2021
En ligne :	https://doi.org/10.1007/s00371-021-02181-8
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98345

[article]

Coniferous 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)

Public

[article]
inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7487 - 7499

Titre :	Coniferous and broad-leaved forest distinguishing using L-band polarimetric SAR data
Type de document :	Article/Communication
Auteurs :	Fang Shang, Auteur ; Taiga Saito, Auteur ; Saya Ohi, Auteur ; et al., Auteur
Année de publication :	2021
Article en page(s) :	pp 7487 - 7499
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] détection de changement [Termes IGN] détection de cible [Termes IGN] distribution spatiale [Termes IGN] forêt de feuillus [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] Japon [Termes IGN] Pinophyta [Termes IGN] polarimétrie radar
Résumé :	(auteur) This article proposes a coniferous and broad-leaved forest distinguishing method using L-band polarimetric SAR data based on the structure-orientation parameter. The structure-orientation parameter is one of the averaged Stokes vector-based discriminators which is sensitive to the composition of equivalent horizontal and vertical structures. In the proposed method, the structure-orientation parameters is compensated by employing the scattered power information to remove the influence of the topography. The final distinguishing result is generated based on the statistical feature of the compensated parameters. The experiments using several sets of ALOS2-PALSAR2 level 1.1 data prove that the proposed method has high performance for forest-type distinguishing.
Numéro de notice :	A2021-648
Affiliation des auteurs :	non IGN
Thématique :	FORET/IMAGERIE
Nature :	Article
nature-HAL :	ArtAvecCL-RevueIntern
DOI :	10.1109/TGRS.2020.3032468
date de publication en ligne :	03/11/2020
En ligne :	https://doi.org/10.1109/TGRS.2020.3032468
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=98355

[article]

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Bulletin Imagerie

Bulletin-imagerie

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2014-2021 IGN

IGN

Centre dedocumentationscientifique

Accueil

Sélection de la langue

Adresse

Se connecter

Actualité

L'actu !

Agenda

Informations pratiques

Bulletin Imagerie

Bulletin-imagerie

IGN / ENSG

L'IGN a pour vocation

Accès directs

2014-2021 IGN

Centre dedocumentation
scientifique