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A remote sensing assessment index for urban ecological livability and its application / Junbo Yu in Geo-spatial Information Science, vol 26 n° inconnu ([01/08/2023])  

Public [article]  inGeo-spatial Information Science > vol 26 n° inconnu [01/08/2023] Titre : A remote sensing assessment index for urban ecological livability and its application Type de document : Article/Communication Auteurs : Junbo Yu, Auteur ; Xinghua Li, Auteur ; Xiaobin Guan, Auteur ; Huanfeng Shen, Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] afforestation [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] indicateur environnemental [Termes IGN] Wuhan (Chine) [Termes IGN] zone urbaine dense Mots-clés libres : The proposed Ecological Livability Index (ELI) covers five primary ecological indicators – greenness, temperature, dryness, water-wetness, and atmospheric turbidity – which are geometrically aggregated by non-equal weights based on an entropy method. Résumé : (auteur) Remote sensing provides us with an approach for the rapid identification and monitoring of spatiotemporal changes in the urban ecological environment at different scales. This study aimed to construct a remote sensing assessment index for urban ecological livability with continuous fine spatiotemporal resolution data from Landsat and MODIS to overcome the dilemma of single image-based, single-factor analysis, due to the limitations of atmospheric conditions or the revisit period of satellite platforms. The proposed Ecological Livability Index (ELI) covers five primary ecological indicators – greenness, temperature, dryness, water-wetness, and atmospheric turbidity – which are geometrically aggregated by non-equal weights based on an entropy method. Considering multisource time-series data of each indicator, the ELI can quickly and comprehensively reflect the characteristics of the Ecological Livability Quality (ELQ) and is also comparable at different time scales. Based on the proposed ELI, the urban ecological livability in the central urban area of Wuhan, China, from 2002 to 2017, in the different seasons was analyzed every 5 years. The ELQ of Wuhan was found to be generally at the medium level (ELI ≈0.6) and showed an initial trend of degradation but then improved. Moreover, the ecological livability in spring and autumn and near rivers and lakes was found to be better, whereas urban expansion has led to the outward ecological degradation of Wuhan, but urban afforestation has enhanced the environment. In general, this paper demonstrates that the ELI has an exemplary embodiment in urban ecological research, which will support urban ecological protection planning and construction. Numéro de notice : A2022-612 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2022.2072775 Date de publication en ligne : 14/06/2022 En ligne : https://doi.org/10.1080/10095020.2022.2072775 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101366 [article]

DEM generation from contours and a low-resolution DEM / Xinghua Li in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 135 - 147 Titre : DEM generation from contours and a low-resolution DEM Type de document : Article/Communication Auteurs : Xinghua Li, Auteur ; Huanfeng Shen, Auteur ; Ruitao Feng, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 135 - 147 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] apprentissage automatique [Termes IGN] détection de contours [Termes IGN] krigeage [Termes IGN] MNS ASTER [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] programmation par contraintes [Termes IGN] régularisation [Termes IGN] représentation discrète Résumé : (Auteur) A digital elevation model (DEM) is a virtual representation of topography, where the terrain is established by the three-dimensional co-ordinates. In the framework of sparse representation, this paper investigates DEM generation from contours. Since contours are usually sparsely distributed and closely related in space, sparse spatial regularization (SSR) is enforced on them. In order to make up for the lack of spatial information, another lower spatial resolution DEM from the same geographical area is introduced. In this way, the sparse representation implements the spatial constraints in the contours and extracts the complementary information from the auxiliary DEM. Furthermore, the proposed method integrates the advantage of the unbiased estimation of kriging. For brevity, the proposed method is called the kriging and sparse spatial regularization (KSSR) method. The performance of the proposed KSSR method is demonstrated by experiments in Shuttle Radar Topography Mission (SRTM) 30 m DEM and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m global digital elevation model (GDEM) generation from the corresponding contours and a 90 m DEM. The experiments confirm that the proposed KSSR method outperforms the traditional kriging and SSR methods, and it can be successfully used for DEM generation from contours. Numéro de notice : A2017-735 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.09.014 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.09.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88432 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017121	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017122	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt
081-2017123	DEP-EXM	Revue	Saint-Mandé	Dépôt en unité	Exclu du prêt

High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations / Linwei Yue in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 123 (January 2017) . - pp 20 - 34 Titre : High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations Type de document : Article/Communication Auteurs : Linwei Yue, Auteur ; Huanfeng Shen, Auteur ; Liangpei Zhang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 20 - 34 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] classification par réseau neuronal [Termes IGN] données ICEsat [Termes IGN] évaluation [Termes IGN] fusion d'images [Termes IGN] image SRTM [Termes IGN] image Terra-ASTER [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique mondial de surface [Termes IGN] Triangulated Irregular Network Résumé : (Auteur) The absence of a high-quality seamless global digital elevation model (DEM) dataset has been a challenge for the Earth-related research fields. Recently, the 1-arc-second Shuttle Radar Topography Mission (SRTM-1) data have been released globally, covering over 80% of the Earth’s land surface (60°N–56°S). However, voids and anomalies still exist in some tiles, which has prevented the SRTM-1 dataset from being directly used without further processing. In this paper, we propose a method to generate a seamless DEM dataset blending SRTM-1, ASTER GDEM v2, and ICESat laser altimetry data. The ASTER GDEM v2 data are used as the elevation source for the SRTM void filling. To get a reliable filling source, ICESat GLAS points are incorporated to enhance the accuracy of the ASTER data within the void regions, using an artificial neural network (ANN) model. After correction, the voids in the SRTM-1 data are filled with the corrected ASTER GDEM values. The triangular irregular network based delta surface fill (DSF) method is then employed to eliminate the vertical bias between them. Finally, an adaptive outlier filter is applied to all the data tiles. The final result is a seamless global DEM dataset. ICESat points collected from 2003 to 2009 were used to validate the effectiveness of the proposed method, and to assess the vertical accuracy of the global DEM products in China. Furthermore, channel networks in the Yangtze River Basin were also extracted for the data assessment. Numéro de notice : A2017-007 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.11.002 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.11.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83906 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017013	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017012	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

An integrated framework for the spatio–temporal–spectral fusion of remote sensing images / Huanfeng Shen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7135 - 7148 Titre : An integrated framework for the spatio–temporal–spectral fusion of remote sensing images Type de document : Article/Communication Auteurs : Huanfeng Shen, Auteur ; Xiangchao Meng, Auteur ; Liangpei Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 7135 - 7148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de fusion [Termes IGN] données spatiotemporelles [Termes IGN] fusion d'images [Termes IGN] fusion de données multisource [Termes IGN] image spectrale Résumé : (Auteur) Remote sensing satellite sensors feature a tradeoff between the spatial, temporal, and spectral resolutions. In this paper, we propose an integrated framework for the spatio-temporal-spectral fusion of remote sensing images. There are two main advantages of the proposed integrated fusion framework: it can accomplish different kinds of fusion tasks, such as multiview spatial fusion, spatio-spectral fusion, and spatio-temporal fusion, based on a single unified model, and it can achieve the integrated fusion of multisource observations to obtain high spatio-temporal-spectral resolution images, without limitations on the number of remote sensing sensors. The proposed integrated fusion framework was comprehensively tested and verified in a variety of image fusion experiments. In the experiments, a number of different remote sensing satellites were utilized, including IKONOS, the Enhanced Thematic Mapper Plus (ETM+), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Hyperspectral Digital Imagery Collection Experiment (HYDICE), and Système Pour l' Observation de la Terre-5 (SPOT-5). The experimental results confirm the effectiveness of the proposed method. Numéro de notice : A2016-926 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2596290 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2596290 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83332 [article]

Noise removal from hyperspectral image with joint spectral–spatial distributed sparse representation / Jie Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 9 (September 2016) . - pp 5425 - 5439 Titre : Noise removal from hyperspectral image with joint spectral–spatial distributed sparse representation Type de document : Article/Communication Auteurs : Jie Li, Auteur ; Qiangqiang Yuan, Auteur ; Huanfeng Shen, Auteur ; Liangpei Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 5425 - 5439 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage dirigé [Termes IGN] bruit (théorie du signal) [Termes IGN] données clairsemées [Termes IGN] filtrage du bruit [Termes IGN] image hyperspectrale [Termes IGN] représentation parcimonieuse Résumé : (Auteur) Hyperspectral image (HSI) denoising is a crucial preprocessing task that is used to improve the quality of images for object detection, classification, and other subsequent applications. It has been reported that noise can be effectively removed using the sparsity in the nonnoise part of the image. With the appreciable redundancy and correlation in HSIs, the denoising performance can be greatly improved if this redundancy and correlation is utilized efficiently in the denoising process. Inspired by this observation, a noise reduction method based on joint spectral-spatial distributed sparse representation is proposed for HSIs, which exploits the intraband structure and the interband correlation in the process of joint sparse representation and joint dictionary learning. In joint spectral-spatial sparse coding, the interband correlation is exploited to capture the similar structure and maintain the spectral continuity. The intraband structure is utilized to adaptively code the spatial structure differences of the different bands. Furthermore, using a joint dictionary learning algorithm, we obtain a dictionary that simultaneously describes the content of the different bands. Experiments on both synthetic and real hyperspectral data show that the proposed method can obtain better results than the other classic methods. Numéro de notice : A2016-902 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2564639 En ligne : https://doi.org/10.1109/TGRS.2016.2564639 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83095 [article]

A general variational framework considering cast shadows for the topographic correction of remote sensing imagery / Huifang Li in ISPRS Journal of photogrammetry and remote sensing, vol 117 (July 2016)  

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Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration / Wei He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)  

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Fusion of multi-scale DEMs using a regularized super-resolution method / Linwei Yue in International journal of geographical information science IJGIS, vol 29 n° 12 (December 2015)  

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A moving weighted harmonic analysis method for reconstructing high-quality SPOT VEGETATION NDVI time-series data / Gang Yang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)  

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A robust mosaicking procedure for high spatial resolution remote sensing images / Xinghua Li in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)  

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Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model / Qing Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 92 (June 2014)  

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Hyperspectral image denoising with a spatial–spectral view fusion strategy / Qiangqiang Yuan in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)  

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