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Extraction of impervious surface using Sentinel-1A time-series coherence images with the aid of a Sentinel-2A image / Wenfu Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 3 (March 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 3 (March 2021) . - pp 161-170 Titre : Extraction of impervious surface using Sentinel-1A time-series coherence images with the aid of a Sentinel-2A image Type de document : Article/Communication Auteurs : Wenfu Wu, Auteur ; Jiahua Teng, Auteur ; Qimin Cheng, Auteur ; Songjing Guo, Auteur Année de publication : 2021 Article en page(s) : pp 161-170 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] chatoiement [Termes IGN] cohérence [Termes IGN] cohérence temporelle [Termes IGN] extraction automatique [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] segmentation d'image [Termes IGN] segmentation multi-échelle [Termes IGN] série temporelle [Termes IGN] surface imperméable Résumé : (Auteur) The continuous increasing of impervious surface (IS) hinders the sustainable development of cities. Using optical images alone to extract IS is usually limited by weather, which obliges us to develop new data sources. The obvious differences between natural and artificial targets in interferometric synthetic-aperture radar coherence images have attracted the attention of researchers. A few studies have attempted to use coherence images to extract IS—mostly single-temporal coherence images, which are affected by de-coherence factors. And due to speckle, the results are rather fragmented. In this study, we used time-series coherence images and introduced multi-resolution segmentation as a postprocessing step to extract IS. From our experiments, the results from the proposed method were more complete and achieved considerable accuracy, confirming the potential of time-series coherence images for extracting IS. Numéro de notice : A2021-240 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.3.161 date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.14358/PERS.87.3.161 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97264 [article]

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Fully convolutional neural network for impervious surface segmentation in mixed urban environment / Joseph McGlinchy in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (February 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 2 (February 2021) . - pp 117 - 123 Titre : Fully convolutional neural network for impervious surface segmentation in mixed urban environment Type de document : Article/Communication Auteurs : Joseph McGlinchy, Auteur ; Brian Muller, Auteur ; Brian Johnson, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 117 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] croissance urbaine [Termes IGN] Denver [Termes IGN] exactitude des données [Termes IGN] image multibande [Termes IGN] image Worldview [Termes IGN] milieu urbain [Termes IGN] segmentation [Termes IGN] surface imperméable Résumé : (Auteur) The urgency of creating appropriate, high-resolution data products such as impervious cover information has increased as cities face rapid growth as well as climate change and other environmental challenges. This work explores the use of fully convolutional neural networks (FCNNs )—specifically UNet with a ResNet-152 encoder—in mapping impervious surfaces at the pixel level from WorldView-2 in a mixed urban/residential environment. We investigate three-, four-, and eight-band multispectral inputs to the FCNN. Resulting maps are promising in both qualitative and quantitative assessment when compared to automated land use/land cover products. Accuracy was assessed by F1 and average precision (AP) scores, as well as receiver operating characteristic curves, with area under the curve (AUC ) used as an additional accuracy metric. The four-band model shows the highest average test-set accuracies (F1, AP, and AUC of 0.709, 0.82, and 0.807, respectively), with higher AP and AUC than the automated land use/land cover products, indicating the utility of the blue-green-red-infrared channels for the FCNN. Improved performance was seen in residential areas, with worse performance in more densely developed areas. Numéro de notice : A2021-099 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.2.117 date de publication en ligne : 01/02/2021 En ligne : https://doi.org/10.14358/PERS.87.2.117 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97045 [article]

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Spatio-temporal relationship between land cover and land surface temperature in urban areas: A case study in Geneva and Paris / Xu Ge in ISPRS International journal of geo-information, vol 9 n° 10 (October 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 10 (October 2020) . - 24 p. Titre : Spatio-temporal relationship between land cover and land surface temperature in urban areas: A case study in Geneva and Paris Type de document : Article/Communication Auteurs : Xu Ge, Auteur ; Dasaraden Mauree, Auteur ; Roberto Castello, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 24 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse spatio-temporelle [Termes IGN] espace vert [Termes IGN] Genève [Termes IGN] ilot thermique urbain [Termes IGN] image Landsat-8 [Termes IGN] Normalized Difference Built-up Index [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] occupation du sol [Termes IGN] Paris (75) [Termes IGN] surface imperméable [Termes IGN] température au sol [Termes IGN] variation saisonnière [Termes IGN] zone urbaine Résumé : (auteur) Currently, more than half of the world’s population lives in cities, which leads to major changes in land use and land surface temperature (LST). The associated urban heat island (UHI) effects have multiple impacts on energy consumption and human health. A better understanding of how different land covers affect LST is necessary for mitigating adverse impacts, and supporting urban planning and public health management. This study explores a distance-based, a grid-based and a point-based analysis to investigate the influence of impervious surfaces, green area and waterbodies on LST, from large (distance and grid based analysis with 400 m grids) to smaller (point based analysis with 30 m grids) scale in the two mid-latitude cities of Paris and Geneva. The results at large scale confirm that the highest LST was observed in the city centers. A significantly positive correlation was observed between LST and impervious surface density. An anticorrelation between LST and green area density was observed in Paris. The spatial lag model was used to explore the spatial correlation among LST, NDBI, NDVI and MNDWI on a smaller scale. Inverse correlations between LST and NDVI and MNDWI, respectively, were observed. We conclude that waterbodies display the greatest mitigation on LST and UHI effects both on the large and smaller scale. Green areas play an important role in cooling effects on the smaller scale. An increase of evenly distributed green area and waterbodies in urban areas is suggested to lower LST and mitigate UHI effects. Numéro de notice : A2020-666 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9100593 date de publication en ligne : 10/10/2020 En ligne : https://doi.org/10.3390/ijgi9100593 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96143 [article]

Extracting 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)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 41 n°12 (20 - 30 March 2020) . - pp 4644 - 4663 Titre : Extracting impervious surfaces from full polarimetric SAR images in different urban areas Type de document : Article/Communication Auteurs : Sara Attarchi, Auteur Année de publication : 2020 Article en page(s) : pp 4644 - 4663 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] extraction de données [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] matrice de co-occurrence [Termes IGN] niveau de gris (image) [Termes IGN] polarimétrie radar [Termes IGN] précision de la classification [Termes IGN] radar à antenne synthétique [Termes IGN] surface imperméable [Termes IGN] surveillance de l'urbanisation [Termes IGN] texture d'image [Termes IGN] zone urbaine Résumé : (auteur) Accurate mapping of impervious surface in urban areas is of great demand in environmental and socio-economic studies since impervious surface growth is recognized as an indicator of urbanization. To demonstrate the potential of full polarimetric Synthetic Aperture Radar (SAR) in impervious surface detection in different urban areas, this study focused on the exploitation of only SAR data. Three cities with different levels of urbanization – Tehran, Kordkuy, and Arak – have been selected to reduce the effect of input data on achieved results. Advanced Land Observing Satellite/Phased Array L-band Synthetic Aperture Radar (ALOS/PALSAR) images have been classified by support vector machine (SVM) with the help of training data from high-resolution satellite images. Quantitative assessment of classification accuracy revealed that Kordkuy, a not fully developed city (i.e. 84.2%) has the lowest accuracy and Arak, a medium urbanized city, has the highest accuracy (i.e. 90.0%). To further explore the efficiency of full polarimetric SAR, grey level co-occurrence matrix (GLCM) texture of polarized bands has been extracted and put into the classification procedure. The texture information of SAR data provided positive contribution to the impervious surface estimation in three study cases. The improvement is especially noted in dark impervious surface class. All three study areas show an increase of about 6–8% in classification accuracy. The results prove that single use of full polarimetric SAR images holds high potential in identifying impervious surfaces in urban areas. The findings are of great importance in frequent urban impervious surface mapping and monitoring especially in cloud-prone area, where the use of optical data as well as the fusion of optic and SAR data are limited. Numéro de notice : A2020-451 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2020.1723178 date de publication en ligne : 24/02/2020 En ligne : https://doi.org/10.1080/01431161.2020.1723178 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95539 [article]

Urban impervious surface estimation from remote sensing and social data / Yan Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 12 (December 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 12 (December 2018) . - pp 771 - 780 Titre : Urban impervious surface estimation from remote sensing and social data Type de document : Article/Communication Auteurs : Yan Yu, Auteur ; Jun Li, Auteur ; Changyu Zhu, Auteur ; Antonio J. Plaza, Auteur Année de publication : 2018 Article en page(s) : pp 771 - 780 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse des mélanges spectraux [Termes IGN] base de données routières [Termes IGN] Canton (Kouangtoung) [Termes IGN] contenu généré par les utilisateurs [Termes IGN] données issues des réseaux sociaux [Termes IGN] données localisées des bénévoles [Termes IGN] données vectorielles [Termes IGN] Google Maps [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-OLI [Termes IGN] OpenStreetMap [Termes IGN] point d'intérêt [Termes IGN] régression multiple [Termes IGN] réseau routier [Termes IGN] surface imperméable [Termes IGN] zone urbaine Résumé : (auteur) We propose an inspiring approach for accurate impervious surface estimation based on the integration of remote sensing and social data. The proposed approach exploits the strengths of two kind of heterogeneous features, i.e., physical features and social features, where the former ones are derived by a morphological attribute profiles-guided spectral mixture analysis model using remote sensing imagery, and the latter ones are obtained from the normalized kernel density of point of interest and vector road datasets. These two features are then integrated using a multivariable linear regression model to estimate impervious surfaces. The proposed method has been tested in the main urban area of Guangzhou, China, in pixel level and parcel level, respectively. The obtained results, with the overall RMSE of 10.98% and 10.90% for pixel level and parcel level, respectively, demonstrate the good performance of integrating remote sensing imagery and social data for mapping of urban impervious surface. Numéro de notice : A2018-549 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.12.771 date de publication en ligne : 01/12/2018 En ligne : https://doi.org/10.14358/PERS.84.12.771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91622 [article]

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An improved temporal mixture analysis unmixing method for estimating impervious surface area based on MODIS and DMSP-OLS data / Li Zhuo in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

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Fusion tardive d’images SPOT 6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)  

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A new scheme for urban impervious surface classification from SAR images / Hongsheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)  

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Exploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

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Per-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling : A case study in environmental remote sensing / Jing Gao in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)  

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Thorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping / Wojciech Drzewiecki in Geodesy and cartography, vol 66 n° 2 (December 2017)  

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Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987–2015) / Ronald C. Estoque in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)  

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Height uncertainty in digital terrain modelling with unmanned aircraft systems / Stig-Göran Mårtensson in Survey review, vol 49 n° 355 (October 2017)  

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Effects of using different sources of remote sensing and geographic information system data on urban stormwater 2D–1D modeling / Yi Hong in Applied sciences, vol 7 n° 9 (September 2017)  

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Urban land use/land cover discrimination using image-based reflectance calibration methods for hyperspectral data / Shailesh S. Deshpande in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 5 (May 2017)  

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