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A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions / Xiaodong Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)
[article]
Titre : A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions Type de document : Article/Communication Auteurs : Xiaodong Li, Auteur ; Feng Ling, Auteur ; Giles M. Foody, Auteur ; Yun Du, Auteur Année de publication : 2016 Article en page(s) : pp 3822 - 3841 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] changement d'occupation du sol
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] image à moyenne résolution
[Termes IGN] image à très haute résolution
[Termes IGN] image Landsat-OLI
[Termes IGN] image multibande
[Termes IGN] image Terra-MODIS
[Termes IGN] itérationRésumé : (auteur) The development of remote sensing has enabled the acquisition of information on land-cover change at different spatial scales. However, a trade-off between spatial and temporal resolutions normally exists. Fine-spatial-resolution images have low temporal resolutions, whereas coarse spatial resolution images have high temporal repetition rates. A novel super-resolution change detection method (SRCD) is proposed to detect land-cover changes at both fine spatial and temporal resolutions with the use of a coarse-resolution image and a fine-resolution land-cover map acquired at different times. SRCD is an iterative method that involves endmember estimation, spectral unmixing, land-cover fraction change detection, and super-resolution land-cover mapping. Both the land-cover change/no-change map and from–to change map at fine spatial resolution can be generated by SRCD. In this study, SRCD was applied to synthetic multispectral image, Moderate-Resolution Imaging Spectroradiometer (MODIS) multispectral image and Landsat-8 Operational Land Imager (OLI) multispectral image. The land-cover from–to change maps are found to have the highest overall accuracy (higher than 85%) in all the three experiments. Most of the changed land-cover patches, which were larger than the coarse-resolution pixel, were correctly detected. Numéro de notice : A2016--122 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2528583 En ligne : https://doi.org/10.1109/TGRS.2016.2528583 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84900
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 7 (July 2016) . - pp 3822 - 3841[article]Optical remotely sensed time series data for land cover classification: A review / Cristina Gómez in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)
[article]
Titre : Optical remotely sensed time series data for land cover classification: A review Type de document : Article/Communication Auteurs : Cristina Gómez, Auteur ; Joanne C. White, Auteur ; Michael A. Wulder, Auteur Année de publication : 2016 Article en page(s) : pp 55 – 72 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] classification automatique
[Termes IGN] détection de changement
[Termes IGN] image Landsat
[Termes IGN] image Sentinel-MSI
[Termes IGN] occupation du sol
[Termes IGN] série temporelle
[Termes IGN] surveillance agricole
[Termes IGN] traitement d'imageRésumé : (auteur) Accurate land cover information is required for science, monitoring, and reporting. Land cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring and mapping of land cover and land cover change in a consistent and robust manner over large areas is made possible with Earth Observation (EO) data. Land cover products satisfying a range of science and policy information needs are currently produced periodically at different spatial and temporal scales. The increased availability of EO data—particularly from the Landsat archive (and soon to be augmented with Sentinel-2 data)—coupled with improved computing and storage capacity with novel image compositing approaches, have resulted in the availability of annual, large-area, gap-free, surface reflectance data products. In turn, these data products support the development of annual land cover products that can be both informed and constrained by change detection outputs. The inclusion of time series change in the land cover mapping process provides information on class stability and informs on logical class transitions (both temporally and categorically). In this review, we present the issues and opportunities associated with generating and validating time-series informed annual, large-area, land cover products, and identify methods suited to incorporating time series information and other novel inputs for land cover characterization. Numéro de notice : A2016-578 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.03.008 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.03.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81716
in ISPRS Journal of photogrammetry and remote sensing > vol 116 (June 2016) . - pp 55 – 72[article]Unsupervised multitemporal spectral unmixing for detecting multiple changes in hyperspectral images / Sicong Liu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 5 (May 2016)
[article]
Titre : Unsupervised multitemporal spectral unmixing for detecting multiple changes in hyperspectral images Type de document : Article/Communication Auteurs : Sicong Liu, Auteur ; Lorenzo Bruzzone, Auteur ; Francesca Bovolo, Auteur ; Peijun Du, Auteur Année de publication : 2016 Article en page(s) : pp 2733 - 2748 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse infrapixellaire
[Termes IGN] détection de changement
[Termes IGN] image hyperspectrale
[Termes IGN] image multitemporelleRésumé : (Auteur) This paper presents a novel multitemporal spectral unmixing (MSU) approach to address the challenging multiple-change detection problem in bitemporal hyperspectral (HS) images. Differently from the state-of-the-art methods that are mainly designed at a pixel level, the proposed technique investigates the spectral-temporal variations at a subpixel level. The considered change detection (CD) problem is analyzed in a multitemporal domain, where a bitemporal spectral mixture model is defined to analyze the spectral composition within a pixel. Distinct multitemporal endmembers (MT-EMs) are extracted according to an automatic and unsupervised technique. Then, a change analysis strategy is designed to distinguish the change and no-change MT-EMs. An endmember-grouping scheme is applied to the changed MT-EMs to detect the unique change classes. Finally, the considered multiple-change detection problem is solved by analyzing the abundances of the change and no-change classes and their contribution to each pixel. The proposed approach has been validated on both simulated and real multitemporal HS data sets presenting multiple changes. Experimental results confirmed the effectiveness of the proposed method. Numéro de notice : A2016-846 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2505183 En ligne : https://doi.org/10.1109/TGRS.2015.2505183 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82927
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 5 (May 2016) . - pp 2733 - 2748[article]Change detection between SAR images using a pointwise approach and graph theory / Minh-Tan Pham in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)
[article]
Titre : Change detection between SAR images using a pointwise approach and graph theory Type de document : Article/Communication Auteurs : Minh-Tan Pham, Auteur ; Grégoire Mercier, Auteur ; Julien Michel, Auteur Année de publication : 2016 Article en page(s) : pp 2020 - 2032 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bruit rose
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] graphe
[Termes IGN] image radar
[Termes IGN] image radar moirée
[Termes IGN] relation topologique
[Termes IGN] traitement du signal
[Termes IGN] voisinage (relation topologique)Résumé : (Auteur) This paper investigates the problem of change detection in multitemporal synthetic aperture radar (SAR) images. Our motivation is to avoid using a large-size dense neighborhood around each pixel to measure its change level, which is usually considered by classical methods in order to perform their accurate detectors. Therefore, we propose to develop a pointwise approach to detect land-cover changes between two SAR images employing the principle of signal processing on graphs. First, a set of characteristic points is extracted from one of the two images to capture the image's significant contextual information. A weighted graph is then constructed to encode the interaction among these keypoints and hence capture the local geometric structure of this first image. With regard to this graph, the coherence of the information carried by the two images is considered for measuring changes between them. In other words, the change level will depend on how much the second image still conforms to the graph structure constructed from the first image. Additionally, due to the presence of speckle noise in SAR imaging, the log-ratio operator will be exploited to perform the image comparison measure. Experimental results performed on real SAR images show the effectiveness of the proposed algorithm, in terms of detection performance and computational complexity, compared to classical methods. Numéro de notice : A2016-838 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2493730 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2493730 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82882
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 4 (April 2016) . - pp 2020 - 2032[article]Monitoring recovery after earthquakes through the integration of remote sensing, GIS, and ground observations: the case of L’Aquila (Italy) / Diana Contreras in Cartography and Geographic Information Science, Vol 43 n° 2 (April - May 2016)
[article]
Titre : Monitoring recovery after earthquakes through the integration of remote sensing, GIS, and ground observations: the case of L’Aquila (Italy) Type de document : Article/Communication Auteurs : Diana Contreras, Auteur ; Thomas Blaschke, Auteur ; Dirk Tiede, Auteur ; Marianne Jilge, Auteur Année de publication : 2016 Article en page(s) : pp 115 - 133 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de données
[Termes IGN] détection de changement
[Termes IGN] Italie
[Termes IGN] outil d'aide à la décision
[Termes IGN] séisme
[Termes IGN] système d'information géographiqueRésumé : (Auteur) The usefulness of remote sensing (RS), geographical information systems, and ground observations for monitoring changes in urban areas has been demonstrated through many examples over the last two decades. Research has generally focused on the relief phase following a disaster, but we have instead investigated the subsequent phases involving early recovery, recovery, and development. Our aim was to determine to what extent integration of the available tools, techniques, and methods can be used to efficiently monitor the progress of recovery following an earthquake. Changes in buildings within the Italian city of L’Aquila following the 2009 earthquake were identified from Earth observation data and are used as indicators of progress in the recovery process. These changes were identified through (1) visual analysis, (2) automated change detection using a set of decision rules formulated within an object-based image analysis framework, and (3) validation based on a combination of visual and semiautomated interpretations. An accuracy assessment of the automated analysis showed a producer accuracy of 81% (error of omission: 19%) and a user accuracy of 55% (error of commission: 45%). The use of RS made it possible for the identification of changes to be spatially exhaustive, and also to increase the number of categories used for a recovery index. In addition, using RS allowed the area requiring extensive fieldwork (to monitor the progress of the recovery process) to be reduced. Numéro de notice : A2016-282 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15230406.2015.1029520 En ligne : https://doi.org/10.1080/15230406.2015.1029520 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80853
in Cartography and Geographic Information Science > Vol 43 n° 2 (April - May 2016) . - pp 115 - 133[article]Réservation
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