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InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico / Pascal Castellazzi in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)
[article]
Titre : InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico Type de document : Article/Communication Auteurs : Pascal Castellazzi, Auteur ; Jaime Garfias, Auteur ; Richard Martel, Auteur ; Charles Brouard, Auteur ; Alfonso Rivera, Auteur Année de publication : 2017 Article en page(s) : pp 33 - 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse diachronique
[Termes IGN] aquifère
[Termes IGN] bande C
[Termes IGN] image Envisat-ASAR
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] image Sentinel-SAR
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Mexique
[Termes IGN] subsidence
[Termes IGN] urbanisationRésumé : (auteur) This paper illustrates how InSAR alone can be used to delineate potential ground fractures related to aquifer system compaction. An InSAR-derived ground fracturing map of the Toluca Valley, Mexico, is produced and validated through a field campaign. The results are of great interest to support sustainable urbanization and show that InSAR processing of open-access Synthetic Aperture Radar (SAR) data from the Sentinel-1 satellites can lead to reliable and cost-effective products directly usable by cities to help decision-making.
The Toluca Valley Aquifer (TVA) sustains the water needs of two million inhabitants living within the valley, a growing industry, an intensively irrigated agricultural area, and 38% of the water needs of the megalopolis of Mexico City, located 40 km east of the valley. Ensuring water sustainability, infrastructure integrity, along with supporting the important economic and demographic growth of the region, is a major challenge for water managers and urban developers. This paper presents a long-term analysis of ground fracturing by interpreting 13 years of InSAR-derived ground displacement measurements. Small Baseline Subset (SBAS) and Persistent Scatterer Interferometry (PSI) techniques are applied over three SAR datasets totalling 93 acquisitions from Envisat, Radarsat-2, and Sentinel-1A satellites and covering the period from 2003 to 2016.
From 2003 to 2016, groundwater level declines of up to 1.6 m/yr, land subsidence up to 77 mm/yr, and major infrastructure damages are observed. Groundwater level data show highly variable seasonal responses according to their connectivity to recharge areas. However, the trend of groundwater levels consistently range from −0.5 to −1.5 m/yr regardless of the well location and depth. By analysing the horizontal gradients of vertical land subsidence, we provide a potential ground fracture map to assist in future urban development planning in the Toluca Valley.Numéro de notice : A2017-413 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2017.06.011 En ligne : https://doi.org/10.1016/j.jag.2017.06.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86300
in International journal of applied Earth observation and geoinformation > vol 63 (December 2017) . - pp 33 - 44[article]Pregnant with potential / Geoff Sawyer in GEO: Geoconnexion international, vol 16 n° 10 (October 2017)
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Titre : Pregnant with potential Type de document : Article/Communication Auteurs : Geoff Sawyer, Auteur Année de publication : 2017 Article en page(s) : pp 26 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] accès aux données
[Termes IGN] données Copernicus
[Termes IGN] image Sentinel-MSIRésumé : (éditeur) SENTINEL 2 was only launched a few months ago, but businesses are already looking for ways to use its data. Geoff Sawyer reports on the results of the latest Earsc industry survey Numéro de notice : A2017-686 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87388
in GEO: Geoconnexion international > vol 16 n° 10 (October 2017) . - pp 26[article]Examination of Sentinel-2A multi-spectral instrument (MSI) reflectance anisotropy and the suitability of a general method to normalize MSI reflectance to nadir BRDF adjusted reflectance / David P. Roy in Remote sensing of environment, vol 199 (15 September 2017)
[article]
Titre : Examination of Sentinel-2A multi-spectral instrument (MSI) reflectance anisotropy and the suitability of a general method to normalize MSI reflectance to nadir BRDF adjusted reflectance Type de document : Article/Communication Auteurs : David P. Roy, Auteur ; Jian Li, Auteur ; Hankui K. Zhang, Auteur ; Lin Yan, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 25 - 38 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] anisotropie
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] image Landsat
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Terra-MODIS
[Termes IGN] réflectance
[Termes IGN] Sentinel-2Résumé : (auteur) The Sentinel-2A multi-spectral instrument (MSI) acquires multi-spectral reflective wavelength observations with directional effects due to surface reflectance anisotropy and changes in the solar and viewing geometry. Directional effects were examined by considering two ten day periods of Sentinel-2A data acquired close to the solar principal and orthogonal planes over approximately 20° × 10° of southern Africa. More than 6.6 million (January 2016) and 10.6 million (April 2016) pairs of reflectance observations sensed 3 or 7 days apart in the forward and backscatter directions in overlapping Sentinel-2A orbit swaths were considered. The Sentinel-2A data were projected into the MODIS sinusoidal projection but first had to be registered due to a misregistration issue evident in the overlapping orbits. The top of atmosphere reflectance data were corrected to surface reflectance using the SEN2COR atmospheric correction software. Only pairs of forward and backward reflectance values that were cloud and snow-free, unsaturated, and had no significant change in their 3 or 7 day separation, were considered. The maximum observed Sentinel-2A view zenith angle was 11.93°. Greater BRDF effects were apparent in the January data (acquired close to the solar principal plane) than the April data (acquired close to the orthogonal plane) and at higher view zenith angle. For the January data the average difference between the surface reflectance in the forward and backward scatter directions at the Sentinel-2A scan edges increased with wavelength from 0.035 (blue), 0.047 (green), 0.057 (red), 0.078 (NIR), to about 0.1 (SWIR). These differences may constitute a significant source of noise for certain applications.
The suitability of a recently published methodology developed to generate Landsat nadir BRDF-adjusted reflectance (NBAR) was examined for Sentinel-2A application. The methodology uses fixed MODIS BRDF spectral parameters and is attractive because it has little sensitivity to the land cover type, condition, or surface disturbance and can be derived in a computationally efficient manner globally. It was applied to the southern Africa Sentinel-2A data and shown to reduce Sentinel-2A BRDF effects. The average difference between the reflectance in the forward and backward scatter directions at the Sentinel-2A scan edges was smaller in the NBAR data than in the corresponding surface reflectance data. Residual BRDF effects in the Sentinel-2A NBAR data occurred likely because of atmospheric correction and sensor calibration errors and inadequacies in the NBAR derivation approach. These issues are discussed with recommendations for future research including global and red-edge Sentinel-2A NBAR derivation that were not considered in this study.Numéro de notice : A2017-416 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.06.019 En ligne : https://doi.org/10.1016/j.rse.2017.06.019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86309
in Remote sensing of environment > vol 199 (15 September 2017) . - pp 25 - 38[article]Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications / Amanda Veloso in Remote sensing of environment, vol 199 (15 September 2017)
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Titre : Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications Type de document : Article/Communication Auteurs : Amanda Veloso, Auteur ; Stéphane Mermoz, Auteur ; Alexandre Bouvet, Auteur ; Thuy Le Toan, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 415 - 426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] blé (céréale)
[Termes IGN] cultures
[Termes IGN] Glycine max
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] maïs (céréale)
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surveillance agricole
[Termes IGN] tournesol
[Termes IGN] variation saisonnière
[Termes IGN] variation temporelleRésumé : (auteur) Crop monitoring information is essential for food security and to improve our understanding of the role of agriculture on climate change, among others. Remotely sensing optical and radar data can help to map crop types and to estimate biophysical parameters, especially with the availability of an unprecedented amount of free Sentinel data within the Copernicus programme. These datasets, whose continuity is guaranteed up to decades, offer a unique opportunity to monitor crops systematically every 5 to 10 days. Before developing operational monitoring methods, it is important to understand the temporal variations of the remote sensing signal of different crop types in a given region. In this study, we analyse the temporal trajectory of remote sensing data for a variety of winter and summer crops that are widely cultivated in the world (wheat, rapeseed, maize, soybean and sunflower). The test region is in southwest France, where Sentinel-1 data have been acquired since 2014. Because Sentinel-2 data were not available for this study, optical satellites similar to Sentinel-2 are used, mainly to derive NDVI, for a comparison between the temporal behaviors with radar data. The SAR backscatter and NDVI temporal profiles of fields with varied management practices and environmental conditions are interpreted physically. Key findings from this analysis, leading to possible applications of Sentinel-1 data, with or without the conjunction of Sentinel-2, are then described. This study points out the interest of SAR data and particularly the VH/VV ratio, which is poorly documented in previous studies. Numéro de notice : A2017-418 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.07.015 En ligne : https://doi.org/10.1016/j.rse.2017.07.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86311
in Remote sensing of environment > vol 199 (15 September 2017) . - pp 415 - 426[article]A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform / Bangqian Chen in ISPRS Journal of photogrammetry and remote sensing, vol 131 (September 2017)
[article]
Titre : A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform Type de document : Article/Communication Auteurs : Bangqian Chen, Auteur ; Xiangming Xiao, Auteur ; Lianghao Pan, Auteur ; Russell Doughty, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 104 - 120 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] carte forestière
[Termes IGN] Chine
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] mangrove
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelleRésumé : (auteur) Due to rapid losses of mangrove forests caused by anthropogenic disturbances and climate change, accurate and contemporary maps of mangrove forests are needed to understand how mangrove ecosystems are changing and establish plans for sustainable management. In this study, a new classification algorithm was developed using the biophysical characteristics of mangrove forests in China. More specifically, these forests were mapped by identifying: (1) greenness, canopy coverage, and tidal inundation from time series Landsat data, and (2) elevation, slope, and intersection-with-sea criterion. The annual mean Normalized Difference Vegetation Index (NDVI) was found to be a key variable in determining the classification thresholds of greenness, canopy coverage, and tidal inundation of mangrove forests, which are greatly affected by tide dynamics. In addition, the integration of Sentinel-1A VH band and modified Normalized Difference Water Index (mNDWI) shows great potential in identifying yearlong tidal and fresh water bodies, which is related to mangrove forests. This algorithm was developed using 6 typical Regions of Interest (ROIs) as algorithm training and was run on the Google Earth Engine (GEE) cloud computing platform to process 1941 Landsat images (25 Path/Row) and 586 Sentinel-1A images circa 2015. The resultant mangrove forest map of China at 30 m spatial resolution has an overall/users/producer’s accuracy greater than 95% when validated with ground reference data. In 2015, China’s mangrove forests had a total area of 20,303 ha, about 92% of which was in the Guangxi Zhuang Autonomous Region, Guangdong, and Hainan Provinces. This study has demonstrated the potential of using the GEE platform, time series Landsat and Sentine-1A SAR images to identify and map mangrove forests along the coastal zones. The resultant mangrove forest maps are likely to be useful for the sustainable management and ecological assessments of mangrove forests in China. Numéro de notice : A2017-419 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.07.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.07.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86313
in ISPRS Journal of photogrammetry and remote sensing > vol 131 (September 2017) . - pp 104 - 120[article]Réservation
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