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Comparison of classification methods for urban green space extraction using very high resolution worldview-3 imagery / S. Vigneshwaran in Geocarto international, vol 36 n° 13 ([15/07/2021])
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Titre : Comparison of classification methods for urban green space extraction using very high resolution worldview-3 imagery Type de document : Article/Communication Auteurs : S. Vigneshwaran, Auteur ; S. Vasantha Kumar, Auteur Année de publication : 2021 Article en page(s) : pp 1429 - 1442 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] classification orientée objet
[Termes IGN] espace vert
[Termes IGN] flore urbaine
[Termes IGN] image à très haute résolution
[Termes IGN] image Worldview
[Termes IGN] Inde
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] urbanismeRésumé : (auteur) Urban green space (UGS) plays a vital role in maintaining the ecological balance of a city and in ensuring healthy living of the city inhabitants. It is generally suggested that one-third of the city should be covered by green and to ensure this, the city administrators must have an accurate map of the existing UGS. Such a map would be useful to visualize the distribution of the existing green cover and also to find out the areas that can possibly be converted to UGS. Reported studies on UGS mapping have mostly used medium and high resolution images such as Landsat-TM, ETM+, Sentinel-2A, IKONOS, etc. However, studies on the use of very high resolution images for UGS extraction are very limited. The present study is a first attempt in utilizing the very high resolution Worldview-3 image for UGS extraction. Performance of different classification methods such as unsupervised, supervised, object based and normalized difference vegetation index (NDVI) were compared using the pan sharpened Worldview-3 image covering part of New Delhi in India. It was found that the unsupervised classification followed by manual recoding method showed superior performance with overall accuracy (OA) of 99% and κ coefficient of 0.98. Also, the OA achieved in the present study is the highest when compared to other reported studies on UGS extraction. The map of UGS revealed that almost 40% of the study area is covered by green which is more than the recommended value of 33% (one-third). In order to check the universality of the unsupervised classification approach in extracting UGS, Worldview-3 image covering Rio in Brazil was tested. It was found that an OA of 98% and κ coefficient of 0.95 were obtained which clearly indicate that the proposed approach would work very well in extracting UGS from any Worldview-3 imagery. Numéro de notice : A2021-553 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1665714 Date de publication en ligne : 18/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1665714 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98104
in Geocarto international > vol 36 n° 13 [15/07/2021] . - pp 1429 - 1442[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2021131 RAB Revue Centre de documentation En réserve L003 Disponible Detecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)
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Titre : Detecting high-temperature anomalies from Sentinel-2 MSI images Type de document : Article/Communication Auteurs : Yongxue Liu, Auteur ; Zhi Weifeng, Auteur ; Bihua Xu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 174 - 193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] anomalie thermique
[Termes IGN] éruption volcanique
[Termes IGN] image aérienne
[Termes IGN] image Landsat-OLI
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] image thermique
[Termes IGN] incendie
[Termes IGN] réflectance spectrale
[Termes IGN] risque technologique
[Termes IGN] série temporelle
[Termes IGN] température au solRésumé : (Auteur) High-temperature anomalies (HTAs) of the earth's surface, such as fires, volcanic activities, and industrial heat sources, have a profound impact on Earth's system. Sentinel-2 Multispectral Instrument (MSI) provides spatially-specific information for precisely measuring the location and extent of HTAs at a fine scale. However, detecting HTAs from MSI images remains challenging because the emitted radiance of an HTA in the short-wave infrared (SWIR) bands can be easily mixed with the reflected solar radiance background in the daytime; and an increasing number of atypical cases in MSI images need to be treated with the enhanced spatial resolution. A generic HTA detection approach that handles both anthropogenic and natural HTAs will broaden the scope of MSI applications. In this study, (i) we highlight two spectral characteristics of HTAs in the far-SWIR, near-SWIR, and NIR bands (i.e., (ρfar-SWIR - ρnear-SWIR)/ρNIR ≥ 0.45 and (ρfar-SWIR -ρnear-SWIR) ≥ ρnear-SWIR - ρNIR) that can effectively enhance HTAs from background geo-features, based on the reflectance spectra in airborne imaging spectrometer data. (ii) We propose a tri-spectral thermal anomaly index (TAI) that jointly uses the two high-temperature-sensitive SWIR bands and the high-temperature-insensitive NIR band to enhance HTAs, based on the above characteristics and a comprehensive sampling of different types of HTAs from 1,974 MSI images. (iii) We develop a TAI-based approach for MSI images to detect HTAs in general. The proposed approach was applied to detect different types of HTAs, including different biomass burnings, active volcanoes, and industrial HTAs, over a wide range of land-cover scenarios. Validations and comparisons demonstrate the proposed approach is reliable and performs better than the existing state-of-the-art HTA detection approaches. Evaluations on two types of small industrial HTAs, including operating kilns and enclosed landfill gas flares, show that the HTA detection probability of the TAI-based approach from time-series MSI images is ~ 84.91% and 88.23%, respectively. Further investigations show that the TAI-based approach also has good transferability in detecting HTAs from multispectral images acquired by Landsat-family satellites. Numéro de notice : A2021-372 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.05.008 Date de publication en ligne : 23/05/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.05.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97808
in ISPRS Journal of photogrammetry and remote sensing > vol 177 (July 2021) . - pp 174 - 193[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2021071 SL Revue Centre de documentation Revues en salle Disponible 081-2021073 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021072 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Estimation of tree height and aboveground biomass of coniferous forests in North China using stereo ZY-3, multispectral Sentinel-2, and DEM data / Yueting Wang in Ecological indicators, vol 126 (July 2021)
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Titre : Estimation of tree height and aboveground biomass of coniferous forests in North China using stereo ZY-3, multispectral Sentinel-2, and DEM data Type de document : Article/Communication Auteurs : Yueting Wang, Auteur ; Xiaoli Zhang, Auteur ; Zhengqi Guo, Auteur Année de publication : 2021 Article en page(s) : n° 107645 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] biomasse aérienne
[Termes IGN] Chine
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] forêt
[Termes IGN] hauteur des arbres
[Termes IGN] image Sentinel-MSI
[Termes IGN] image ZiYuan-3
[Termes IGN] modèle numérique de surface
[Termes IGN] Pinophyta
[Termes IGN] surveillance forestièreRésumé : (auteur) The forest tree height and aboveground biomass (AGB) are important indicators for monitoring changes and trends in forest carbon storage and terrestrial carbon fluxes. Accurate large-scale wall-to-wall mapping of the forest tree height and AGB remain challenging due to the limited data availability for extraction tree height and the data signal saturation problem in AGB estimation. In this study, we explored the potential of forest tree height mapping using stereo imageries, and analyzed whether accounting for such information, in addition to optical sensor data, could improve the performance of AGB estimations of coniferous forests in a case study in North China. First, a spatially continuous tree height product was obtained using Ziyuan-3 satellite (ZY-3) stereo images combined with a digital elevation model (DEM) obtained from Advanced Land Observing Satellite (ALOS) data. Second, two AGB estimation models were established by combining the forest tree height with vegetation index, spectral, biophysical (from Sentinel-2 images), and topographic variables. A random forest algorithm was utilized to evaluate the effect of including the tree height variable in the AGB estimation. The results showed that the tree height estimation using the nadir and forward views of the ZY-3 stereo images was more accurate than that based on the nadir and backward views from the same images. The AGB estimation model incorporating the tree height variable with a coefficient of determination value of 0.7789, a root mean square error (RMSE) value of 29.815 Mg/ha and a relative RMSE of 23.42% was more robust and effective, thereby demonstrating that the tree height variable can be used to alleviate the data signal saturation issue successfully. The proposed approach can provide new insight into forest tree height mapping and AGB products obtained from satellite stereo images and freely accessible Sentinel-2 multispectral images. Numéro de notice : A2021-942 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ecolind.2021.107645 En ligne : https://doi.org/10.1016/j.ecolind.2021.107645 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99753
in Ecological indicators > vol 126 (July 2021) . - n° 107645[article]Evaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data / Asadollah Mirasi in Geocarto international, vol 36 n° 12 ([01/07/2021])
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Titre : Evaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data Type de document : Article/Communication Auteurs : Asadollah Mirasi, Auteur ; Asghar Mahmoudi, Auteur ; Hossein Navid, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1309-1304 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] blé (céréale)
[Termes IGN] données de terrain
[Termes IGN] image Landsat-OLI
[Termes IGN] image Terra-MODIS
[Termes IGN] Leaf Area Index
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] rendement agricole
[Termes IGN] Soil Adjusted Vegetation IndexRésumé : (Auteur) Normalized difference vegetation index (NDVI)-based models have been developed to derive wheat grain yields with multispectral images. In this regard, field measurements and Landsat 8 Operational Land Imager (OLI) data were used for two growing seasons to determine the relationships between NDVI and yields. The number of six statistic parameters were calculated from NDVI values to find the best agreement with actual yield data. A comparison of the results showed that sum-NDVI better matched field measurements. To compare the results of NDVI with other vegetation indices, we applied four other vegetation indices. Results indicated that estimation of wheat yields using sum-NDVI values was more accurate than estimation by sum of the four applied vegetation indices values. Also, the investigation of multi-temporal images showed that the critical time to estimate wheat yield using sum-NDVI values was the time that wheat grains were in the milky and maturity stages. Numéro de notice : A2021-377 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1641561 Date de publication en ligne : 16/07/2019 En ligne : https://doi.org/10.1080/10106049.2019.1641561 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97872
in Geocarto international > vol 36 n° 12 [01/07/2021] . - pp 1309-1304[article]Feux de forêts et technologies spatiales / Laurent Polidori in Géomètre, n° 2193 (juillet-août 2021)
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Titre : Feux de forêts et technologies spatiales Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2021 Article en page(s) : pp 21 - 21 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] image NPP-VIIRS
[Termes IGN] image Terra-MODIS
[Termes IGN] incendie de forêtRésumé : (éditeur) La récurrence des feux de forêts rend nécessaire une cartographie fiable pour la prévention, avec l’aide des satellites. Numéro de notice : A2021-508 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98161
in Géomètre > n° 2193 (juillet-août 2021) . - pp 21 - 21[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 063-2021071 RAB Revue Centre de documentation En réserve L003 Disponible Fluvial gravel bar mapping with spectral signal mixture analysis / Liza Stančič in European journal of remote sensing, vol 54 sup 1 (2021)
PermalinkMapping sandy land using the new sand differential emissivity index from thermal infrared emissivity data / Shanshan Chen in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
PermalinkMulti-scale coal fire detection based on an improved active contour model from Landsat-8 satellite and UAV images / Yanyan Gao in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)
PermalinkMultisensor data fusion for cloud removal in global and all-season Sentinel-2 imagery / Patrick Ebel in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
PermalinkSemantic unsupervised change detection of natural land cover with multitemporal object-based analysis on SAR images / Donato Amitrano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
PermalinkSemiCDNet: A semisupervised convolutional neural network for change detection in high resolution remote-sensing images / Daifeng Peng in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
PermalinkSpatio-temporal-spectral observation model for urban remote sensing / Zhenfeng Shao in Geo-spatial Information Science, vol 24 n° 3 (July 2021)
PermalinkA unified framework of bundle adjustment and feature matching for high-resolution satellite images / Xiao Ling in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)
PermalinkForest cover mapping and Pinus species classification using very high-resolution satellite images and random forest / Laura Alonso-Martinez in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)
PermalinkMarrying deep learning and data fusion for accurate semantic labeling of Sentinel-2 images / Guillemette Fonteix in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)
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