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Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images / Bin Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)
[article]
Titre : Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images Type de document : Article/Communication Auteurs : Bin Zhang, Auteur ; Ling Chang, Auteur ; Alfred Stein, Auteur Année de publication : 2021 Article en page(s) : pp 222 - 236 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] déformation de surface
[Termes IGN] données spatiotemporelles
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] points homologues
[Termes IGN] série temporelleRésumé : (auteur) A recent development in Interferometric Synthetic Aperture Radar (InSAR) technology is integrating multiple SAR satellite data to dynamically extract ground features. This paper addresses two relevant challenges: identification of common ground targets from different SAR datasets in space, and concatenation of time series when dealing with temporal dynamics. To address the first challenge, we describe the geolocation uncertainty of InSAR measurements as a three-dimensional error ellipsoid. The points, among InSAR measurements, which have error ellipsoids with a positive cross volume are identified as tie-point pairs representing common ground objects from multiple SAR datasets. The cross volumes are calculated using Monte Carlo methods and serve as weights to achieve the equivalent deformation time series. To address the second challenge, the deformation time series model for each tie-point pair is estimated using probabilistic methods, where potential deformation models are efficiently tested and evaluated. As an application, we integrated two Radarsat-2 datasets in Standard and Extra-Fine modes to map the subsidence of the west of the Netherlands between 2010 and 2017. We identified 18128 tie-point pairs, 5 intersection types of error ellipsoids, 5 deformation models, and constructed their long-term deformation time series. The detected maximum mean subsidence velocity in Line-Of-Sight direction is up to 15 . We conclude that our method removes limitations that exist in single-viewing-geometry SAR when integrating multiple SAR data. In particular, the proposed time-series modeling method is useful to achieve a long-term deformation time series of multiple datasets. Numéro de notice : A2021-414 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.04.005 Date de publication en ligne : 08/05/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.04.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97745
in ISPRS Journal of photogrammetry and remote sensing > vol 176 (June 2021) . - pp 222 - 236[article]The use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries / Nagihan Aslan in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)
[article]
Titre : The use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries Type de document : Article/Communication Auteurs : Nagihan Aslan, Auteur ; Dilek Koc-San, Auteur Année de publication : 2021 Article en page(s) : n° 416 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] ilot thermique urbain
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] image proche infrarouge
[Termes IGN] Normalized Difference Built-up Index
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Normalized Difference Water Index
[Termes IGN] occupation du sol
[Termes IGN] Soil Adjusted Vegetation Index
[Termes IGN] température au sol
[Termes IGN] Turquie
[Termes IGN] utilisation du solRésumé : (auteur) The aims of this study were to determine surface urban heat island (SUHI) effects and to analyze the land use/land cover (LULC) and land surface temperature (LST) changes for 11 time periods from the years 2002 to 2020 using Landsat time series images. Bursa, which is the fourth largest metropolitan city in Turkey, was selected as the study area, and Landsat multi-temporal images of the summer season were used. Firstly, the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), modified normalized difference water index (MNDWI) and index-based built-up index (IBI) were created using the bands of Landsat images, and LULC classes were determined by applying automatic thresholding. The LST values were calculated using thermal images and SUHI effects were determined. The results show that NDVI, SAVI, MNDWI and IBI indices can be used effectively for the determination of the urban, vegetation and water LULC classes for SUHI studies, with overall classification accuracies between 89.60% and 95.90% for the used images. According to the obtained results, generally the LST values increased for almost all land cover areas between the years 2002 and 2020. The SUHI magnitudes were computed by using two methods, and it was found that there was an important increase in the 18-year time period. Numéro de notice : A2021-516 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10060416 Date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.3390/ijgi10060416 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97936
in ISPRS International journal of geo-information > vol 10 n° 6 (June 2021) . - n° 416[article]Uncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery / Mahmoud Salah in Applied geomatics, vol 13 n° 2 (June 2021)
[article]
Titre : Uncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery Type de document : Article/Communication Auteurs : Mahmoud Salah, Auteur Année de publication : 2021 Article en page(s) : pp 261 - 275 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] appariement d'histogramme
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] Egypte
[Termes IGN] géoréférencement
[Termes IGN] image à très haute résolution
[Termes IGN] image Geoeye
[Termes IGN] image multitemporelle
[Termes IGN] incertitude des données
[Termes IGN] méthode robuste
[Termes IGN] modèle de Markov caché
[Termes IGN] occupation du sol
[Termes IGN] réseau neuronal artificiel
[Termes IGN] utilisation du solRésumé : (auteur) Robust approaches for image change detection (ICD) are essential for a range of large-scale applications. However, the uncertainties involved in such approaches have not been fully addressed. To investigate this problem, this paper proposes a new approach for change detection from multi-temporal very high resolution (VHR) satellite imagery based on uncertainty detection and management. First, two GeoEye-1 images of Giza urban area (Egypt), acquired in 2009 and 2019, have been geographically co-registered and their histograms have been matched. Second, a set of feature attributes have been generated from the co-registered images. Third, the support vector machine (SVM) algorithm has been adopted to classify the data into four classes: building, tree, road, and ground. In this regard, the co-registered images along with the generated attributes have been applied as input data for the SVM to calculate the probability of each pixel belonging to each class. After that, the probability images for both epochs have been compared to model the uncertainty of changes. The uncertainty places are then evaluated to estimate their likelihood of being change or no change. Finally, the obtained results have been compared with manually digitized change detection map. Compared with using the widely used post-classification comparison (PCC) approach, the results suggest that (1) the proposed method has improved the overall accuracy of change detection by 13%; (2) the class-accuracies have been improved by 35.63%; and (3) the achieved accuracies for the proposed approach are less variable. Whereas the standard deviation (SD) of the accuracies obtained for the proposed approach is 6.80, the SD of those obtained for the PCC approach is 35.50. Numéro de notice : A2021-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00346-z Date de publication en ligne : 28/10/2020 En ligne : https://doi.org/10.1007/s12518-020-00346-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97737
in Applied geomatics > vol 13 n° 2 (June 2021) . - pp 261 - 275[article]Analysing the impact of climate change on hydrological ecosystem services in Laguna del Sauce (Uruguay) using the SWAT model and remote sensing data / Celina Aznarez in Remote sensing, vol 13 n°10 (May-2 2021)
[article]
Titre : Analysing the impact of climate change on hydrological ecosystem services in Laguna del Sauce (Uruguay) using the SWAT model and remote sensing data Type de document : Article/Communication Auteurs : Celina Aznarez, Auteur ; Patricia Jimeno-Sáez, Auteur ; Adrián López-Ballesteros, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2014 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] algue
[Termes IGN] bassin hydrographique
[Termes IGN] changement climatique
[Termes IGN] eau potable
[Termes IGN] érosion
[Termes IGN] gestion de l'eau
[Termes IGN] image satellite
[Termes IGN] modèle hydrographique
[Termes IGN] ressources en eau
[Termes IGN] risque naturel
[Termes IGN] service écosystémique
[Termes IGN] UruguayRésumé : (auteur) Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment. Numéro de notice : A2021-472 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13102014 Date de publication en ligne : 20/05/2021 En ligne : https://doi.org/10.3390/rs13102014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97820
in Remote sensing > vol 13 n°10 (May-2 2021) . - n° 2014[article]A compilation of snow cover datasets for Svalbard: A multi-sensor, multi-model study / Hannah Vickers in Remote sensing, vol 13 n°10 (May-2 2021)
[article]
Titre : A compilation of snow cover datasets for Svalbard: A multi-sensor, multi-model study Type de document : Article/Communication Auteurs : Hannah Vickers, Auteur ; Eirik Malnes, Auteur ; Ward van Pelt, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2002 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] données multicapteurs
[Termes IGN] image à haute résolution
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Terra-MODIS
[Termes IGN] manteau neigeux
[Termes IGN] modélisation
[Termes IGN] Normalized Difference Snow Index
[Termes IGN] série temporelle
[Termes IGN] surveillance hydrologique
[Termes IGN] SvalbardRésumé : (auteur) Reliable and accurate mapping of snow cover are essential in applications such as water resource management, hazard forecasting, calibration and validation of hydrological models and climate impact assessments. Optical remote sensing has been utilized as a tool for snow cover monitoring over the last several decades. However, consistent long-term monitoring of snow cover can be challenging due to differences in spatial resolution and retrieval algorithms of the different generations of satellite-based sensors. Snow models represent a complementary tool to remote sensing for snow cover monitoring, being able to fill in temporal and spatial data gaps where a lack of observations exist. This study utilized three optical remote sensing datasets and two snow models with overlapping periods of data coverage to investigate the similarities and discrepancies in snow cover estimates over Nordenskiöld Land in central Svalbard. High-resolution Sentinel-2 observations were utilized to calibrate a 20-year MODIS snow cover dataset that was subsequently used to correct snow cover fraction estimates made by the lower resolution AVHRR instrument and snow model datasets. A consistent overestimation of snow cover fraction by the lower resolution datasets was found, as well as estimates of the first snow-free day (FSFD) that were, on average, 10–15 days later when compared with the baseline MODIS estimates. Correction of the AVHRR time series produced a significantly slower decadal change in the land-averaged FSFD, indicating that caution should be exercised when interpreting climate-related trends from earlier lower resolution observations. Substantial differences in the dynamic characteristics of snow cover in early autumn were also present between the remote sensing and snow model datasets, which need to be investigated separately. This work demonstrates that the consistency of earlier low spatial resolution snow cover datasets can be improved by using current-day higher resolution datasets. Numéro de notice : A2021-438 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13102002 Date de publication en ligne : 20/05/2021 En ligne : https://doi.org/10.3390/rs13102002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97822
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