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Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series / Maylis Lopes in Methods in ecology and evolution, vol 11 n° 4 (April 2020)
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Titre : Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series Type de document : Article/Communication Auteurs : Maylis Lopes, Auteur ; Pierre-Louis Frison , Auteur ; Merry Crowson, Auteur ; Eleanor Warren-Thomas, Auteur ; et al., Auteur
Année de publication : 2020 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : pp 532 - 541 Note générale : bibliography Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] classification
[Termes IGN] fusion d'images
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] Indonésie
[Termes IGN] nébulosité
[Termes IGN] série temporelle
[Termes IGN] tourbière
[Termes IGN] zone intertropicaleRésumé : (auteur) The recent availability of high spatial and temporal resolution optical and radar satellite imagery has dramatically increased opportunities for mapping land cover at fine scales. Fusion of optical and radar images has been found useful in tropical areas affected by cloud cover because of their complementarity. However, the multitemporal dimension these data now offer is often neglected because these areas are primarily characterized by relatively low levels of seasonality and because the consideration of multitemporal data requires more processing time. Hence, land cover mapping in these regions is often based on imagery acquired for a single date or on an average of multiple dates. The aim of this work is to assess the added value brought by the temporal dimension of optical and radar time series when mapping land cover in tropical environments. Specifically, we compared the accuracies of classifications based on (a) optical time series, (b) their temporal average, (c) radar time series, (d) their temporal average, (e) a combination of optical and radar time series and (f) a combination of their temporal averages for mapping land cover in Jambi province, Indonesia, using Sentinel-1 and Sentinel-2 imagery. Using the full information contained in the time series resulted in significantly higher classification accuracies than using temporal averages (+14.7% for Sentinel-1, +2.5% for Sentinel-2 and +2% combining Sentinel-1 and Sentinel-2). Overall, combining Sentinel-2 and Sentinel-1 time series provided the highest accuracies (Kappa = 88.5%). Our study demonstrates that preserving the temporal information provided by satellite image time series can significantly improve land cover classifications in tropical biodiversity hotspots, improving our capacity to monitor ecosystems of high conservation relevance such as peatlands. The proposed method is reproducible, automated and based on open-source tools satellite imagery. Numéro de notice : A2020-875 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/2041-210X.13359 Date de publication en ligne : 27/01/2020 En ligne : https://doi.org/10.1111/2041-210X.13359 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99668
in Methods in ecology and evolution > vol 11 n° 4 (April 2020) . - pp 532 - 541[article]Monitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])
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Titre : Monitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys Type de document : Article/Communication Auteurs : Ashutosh Tiwari, Auteur ; Avadh Bihari Narayan, Auteur ; Ramji Dwivedi, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 535 - 558 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] arpentage
[Termes IGN] corrélation croisée maximale
[Termes IGN] covariance
[Termes IGN] données GNSS
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] effondrement de terrain
[Termes IGN] escarpement
[Termes IGN] image Sentinel-SAR
[Termes IGN] Inde
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] modèle numérique de surface
[Termes IGN] précipitation
[Termes IGN] surveillance géologique
[Termes IGN] tachéomètre électronique robotiséRésumé : (auteur) A robust geodetic framework comprising Terrestrial Laser Scanner (TLS), Global Navigation Satellite Systems (GNSS), Robotic Total Station (RTS) and Multi-temporal InSAR (MT-InSAR) was employed first in India to investigate a landslide-prone Sirobagarh region, Uttarakhand, at different spatial extents, and to evaluate the relationship amongst the displacement estimates obtained from the applied surveying techniques. TLS derived digital elevation models indicated displacements >5 m on the landslide upper scarp. GNSS- and RTS-based observations showed horizontal movements towards the Alaknanda river in the landslide slope direction (maximum values: 0.1305 and 0.045 m, respectively), and downward vertical motion (largest subsidence magnitude: −2.1315 and −0.030 m, respectively). MT-InSAR processing of Sentinel-1a images identified 21071 measurement pixels, highlighting subsidence around the landslide (mean velocity range: −0.110 to 0.008 m/year). Analysis of displacement vectors using vector equality, cross-covariance, cross-correlation and principal component analysis reveals that GNSS vertical displacement estimates were partially correlated with MT-InSAR measurements (correlated for epoch difference 2–3), whereas there was good cross-correlation between MT-InSAR and LiDAR observations throughout. The displacement estimates and their analyses evident unstable movement of the landslide scarp occurring due to debris flow and rainfall, and a relatively moderate subsidence activity in the surrounding areas lying in the landslide zone. Numéro de notice : A2020-144 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1524516 Date de publication en ligne : 23/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1524516 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94770
in Geocarto international > vol 35 n° 5 [01/04/2020] . - pp 535 - 558[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020051 RAB Revue Centre de documentation En réserve L003 Disponible Le sol s'affaisse, l'eau monte [Delta du Gange-Brahmapoutre-Meghna] / Marielle Mayo in Géomètre, n° 2179 (avril 2020)
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Titre : Le sol s'affaisse, l'eau monte [Delta du Gange-Brahmapoutre-Meghna] Type de document : Article/Communication Auteurs : Marielle Mayo, Auteur Année de publication : 2020 Article en page(s) : pp 46 - 48 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] delta
[Termes IGN] effondrement de terrain
[Termes IGN] Gange (fleuve)
[Termes IGN] géomorphologie locale
[Termes IGN] hydrodynamique
[Termes IGN] image Envisat
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] méthode robuste
[Termes IGN] montée du niveau de la mer
[Termes IGN] sédiment
[Termes IGN] submersion marine
[Termes IGN] subsidenceRésumé : (Auteur) Pour la première fois, une étude fondée sur une analyse robuste des données géospatiales offre une estimation fiable de la contribution de la subsidence du delta à la montée des eaux. Numéro de notice : A2020-180 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94848
in Géomètre > n° 2179 (avril 2020) . - pp 46 - 48[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 063-2020041 RAB Revue Centre de documentation En réserve L003 Disponible Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
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Titre : Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China Type de document : Article/Communication Auteurs : Mingyue Wang, Auteur ; Jun’e Fu, Auteur ; Zhitao Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] coefficient de corrélation
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] écosystème
[Termes IGN] Fleuve jaune (Chine)
[Termes IGN] image Aqua-MODIS
[Termes IGN] image SPOT
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] précipitation
[Termes IGN] série temporelle
[Termes IGN] température
[Termes IGN] variation saisonnièreRésumé : (auteur) Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area. Numéro de notice : A2020-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040282 Date de publication en ligne : 24/04/2020 En ligne : https://doi.org/10.3390/ijgi9040282 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95022
in ISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 17 p.[article]Temporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)
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Titre : Temporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau Type de document : Article/Communication Auteurs : Gaofei Yin, Auteur ; Ainong Li, Auteur ; Zhengjian Zhang, Auteur ; Guangbin Lei, Auteur Année de publication : 2020 Article en page(s) : pp 225 - 233 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] appariement d'images
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] Leaf Area Index
[Termes IGN] plateau
[Termes IGN] prairie
[Termes IGN] série temporelle
[Termes IGN] température au sol
[Termes IGN] TibetRésumé : (Auteur) Time series of leaf area index (LAI) products are now widely used, and the temporal validation is the prerequisite for their proper application. However, a systematical comparison between different products using both direct and indirect methods is still lacking. The objective of this paper is to assess and compare the temporal performances of four LAI products: Moderate Resolution Imaging Spectroradiometer (MODIS) LAI (MOD)15A2, MOD15A2h, Geoland2 Version 1 (GEOV1), and Global Land Surface Satellite (GLASS). The study area, which is dominated by grasslands, is located in the northeastern Tibetan Plateau (TP), and temperature is the main stress factor affecting grass growth. Both a correlation analysis with temperature and a direct comparison with temporally continuous LAI reference maps were implemented in our temporal validation experiments. The results show that no single product can capture the rapid change and the seasonal trend in LAI simultaneously, and the compositing period used in each product determines the quality of the corresponding LAI time series. The MOD15A2 and MOD15A2h products, which have short compositing windows (eight days), are suitable for detecting rapid change. A grazing-induced biomass decrease that occurred around day of year 205 in 2014 in our study area was clearly revealed in these two products. For the GEOV1 and GLASS products, which have compositing windows of 30 days and 1 year, respectively, the grazing date was shifted (GEOV1) or even invisible (GLASS). However, products with prolonged compositing windows may be more robust to observation noise, and the resulting products may be suitable for capturing the seasonal trend. This study highlights that the concurrent use of data from various sensors onboard different satellites, and the introduction of new generations of satellites (e.g., Gaofen-6), are two promising ways to further improve existing LAI time series. Numéro de notice : A2020-129 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.4.225 Date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.14358/PERS.86.4.225 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94804
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 4 (April 2020) . - pp 225 - 233[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)
PermalinkHow far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study / Enrico Borgogno Mondino in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)
PermalinkDimension reduction methods applied to coastline extraction on hyperspectral imagery / Ozan Arslan in Geocarto international, vol 35 n° 4 ([15/03/2020])
PermalinkAdvanced machine learning optimized by the genetic algorithm in ionospheric models using long-term multi-instrument observations / Wang Li in Remote sensing, vol 12 n° 5 (March 2020)
PermalinkAn original method for tree species classification using multitemporal multispectral and hyperspectral satellite data / Olga Grigorieva in Silva fennica, vol 54 n° 2 (March 2020)
PermalinkAssessing environmental impacts of urban growth using remote sensing / John C. Trinder in Geo-spatial Information Science, vol 23 n° 1 (March 2020)
PermalinkAssessing the shape accuracy of coarse resolution burned area identifications / Michael L. Humber in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
PermalinkAssessment of dense image matchers for digital surface model generation using airborne and spaceborne images – an update / Yilong Han in Photogrammetric record, vol 35 n° 169 (March 2020)
PermalinkAssessment of salt marsh change on Assateague Island National Seashore between 1962 and 2016 / Anthony Campbell in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 3 (March 2020)
PermalinkDeep SAR-Net: learning objects from signals / Zhongling Huang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)
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