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Characterizing stream morphological features important for fish habitat using airborne laser scanning data / Spencer Dakin Kuiper in Remote sensing of environment, vol 272 (April 2022)  

Public [article]  inRemote sensing of environment > vol 272 (April 2022) . - n° 112948 Titre : Characterizing stream morphological features important for fish habitat using airborne laser scanning data Type de document : Article/Communication Auteurs : Spencer Dakin Kuiper, Auteur ; Nicholas C. Coops, Auteur ; Piotr Tompalski, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112948 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] bassin hydrographique [Termes IGN] cours d'eau [Termes IGN] données de terrain [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écosystème forestier [Termes IGN] forêt ripicole [Termes IGN] géomorphologie locale [Termes IGN] gestion forestière durable [Termes IGN] habitat animal [Termes IGN] modèle numérique de surface [Termes IGN] poisson (faune aquatique) [Termes IGN] semis de points [Termes IGN] structure d'un peuplement forestier [Termes IGN] Vancouver (Colombie britannique) Résumé : (auteur) Understanding changes in salmonid populations and their habitat is a critical issue given changing climate, their importance as a keystone species, and their cultural significance. Terrain features such as slope, gradient, and morphology, as well as forest structure attributes including canopy cover, height, and presence of on ground coarse wood, all influence the quality and quantity of salmonid habitat in forested ecosystems. The increasing availability of Airborne Laser Scanning (ALS) data for forest applications offers an opportunity to utilize these data for assessing the quality and quantity of habitat, which is often costly and difficult to characterize. ALS data provides detailed and accurate Digital Elevation Models (DEMs) under forest canopies, which in turn enable the characterization of detailed stream networks, as well as stream and terrain attributes important to salmonids. At the Nahmint watershed on Vancouver Island, British Columbia, Canada, we sampled six, 200 m long stream reaches, describing a range of terrain and stream features following standard data collection protocols. Our objective in this research was to use ALS data to estimate three attributes from the 3D point cloud and DEM that are known to be important for salmonids, including bankfull width,instream wood and discrete stream morphological units. Results indicate that ALS-based estimates had strong, significant, correlations with field-measured attributes (with Pearson's correlation of 0.80 and 0.81 for bankfull width and instream wood, respectively). Bankfull width was slightly underestimated using the ALS data (Bias = −1.01 m; MAD = 1.89 m; RMSD = 2.05 m) and 80% of instream wood pieces were detected. Using ALS-derived predictors in a Random Forest model, discrete stream morphological units (i.e. pools, riffles, glides, cascades) were classified with an overall accuracy of 85%, with pools having the highest user's class accuracy at 96%. Results presented herein indicate that ALS data can be used to provide a fine scale characterization of stream attributes that are required to identify salmonid habitat, providing critical information for sustainable forest management decision making, and providing a foundation for advanced salmonid habitat modeling. Numéro de notice : A2022-283 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.112948 Date de publication en ligne : 24/02/2022 En ligne : https://doi.org/10.1016/j.rse.2022.112948 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100301 [article]

Historical Vltava River valley–various historical sources within web mapping environment / Jiří Krejčí in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 1 (January 2022) . - n° 35 Titre : Historical Vltava River valley–various historical sources within web mapping environment Type de document : Article/Communication Auteurs : Jiří Krejčí, Auteur ; Jiří Cajthaml, Auteur Année de publication : 2022 Article en page(s) : n° 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] ArcGIS [Termes IGN] carte ancienne [Termes IGN] changement d'utilisation du sol [Termes IGN] données anciennes [Termes IGN] géoréférencement [Termes IGN] modélisation 3D [Termes IGN] point d'appui [Termes IGN] République Tchèque [Termes IGN] rivière [Termes IGN] système d'information historique [Termes IGN] vectorisation [Termes IGN] web mapping Résumé : (auteur) The article deals with a comprehensive information system of the historic Vltava River valley. This system contains a number of resources, which are described. For old maps, which are the basis of the whole system, their georeferencing and potential problems in creating seamless mosaics are described. Other sources of data include old photographs, which are localized and stored in the system, along with the definition point of the place from which they were probably taken. The vectorization of data is described, not only for area features used for the analysis of land-use changes, but also for the vectorization of contours. These were vectorized from old maps and are substantial for the creation of historic DEM. Vectorized footprints of buildings and vectors of other functional areas subsequently serve as a basis for the procedural modeling of the virtual 3D landscape. The creation of such a complex and broad information system cannot be described in one article. The aim of this text is to draw attention to a possible approach to the presentation and visualization of the historic landscape, along with links to important documents. Numéro de notice : A2022-038 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11010035 Date de publication en ligne : 04/01/2022 En ligne : https://doi.org/10.3390/ijgi11010035 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99380 [article]

Use of multi-temporal and multi-sensor data for continental water body extraction in the context of the SWOT mission / Nicolas Gasnier (2022)  

Public Titre : Use of multi-temporal and multi-sensor data for continental water body extraction in the context of the SWOT mission Type de document : Thèse/HDR Auteurs : Nicolas Gasnier, Auteur ; Florence Tupin, Directeur de thèse ; Loïc Denis, Directeur de thèse Editeur : Paris : Institut Polytechnique de Paris Année de publication : 2022 Importance : 213 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse de doctorat présentée à l’Institut Polytechnique de Paris, spécialité Images Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] base de données localisées [Termes IGN] détection d'objet [Termes IGN] détection de changement [Termes IGN] données hydrographiques [Termes IGN] hauteurs de mer [Termes IGN] image multitemporelle [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] image SWOT [Termes IGN] lac [Termes IGN] rivière [Termes IGN] série temporelle [Termes IGN] télédétection en hyperfréquence Index. décimale : THESE Thèses et HDR Résumé : (Auteur) Spaceborne remote sensing provides hydrologists and decision-makers with data that are essential for understanding the water cycle and managing the associated resources and risks. The SWOT satellite, which is a collaboration between the French (CNES) and American (NASA, JPL) space agencies, is scheduled for launch in 2022 and will measure the height of lakes, rivers, and oceans with high spatial resolution. It will complement existing sensors, such as the SAR and optical constellations Sentinel-1 and 2, and in situ measurements. SWOT represents a technological breakthrough as it is the first satellite to carry a near-nadir swath altimeter. The estimation of water levels is done by interferometry on the SAR images acquired by SWOT. Detecting water in these images is therefore an essential step in processing SWOT data, but it can be very difficult, especially with low signal-to-noise ratios, or in the presence of unusual radiometries. In this thesis, we seek to develop new methods to make water detection more robust. To this end, we focus on the use of exogenous data to guide detection, the combination of multi-temporal and multi-sensor data and denoising approaches. The first proposed method exploits information from the river database used by SWOT (derived from GRWL) to detect narrow rivers in the image in a way that is robust to both noise in the image, potential errors in the database, and temporal changes. This method relies on a new linear structure detector, a least-cost path algorithm, and a new Conditional Random Field segmentation method that combines data attachment and regularization terms adapted to the problem. We also proposed a method derived from GrabCut that uses an a priori polygon containing a lake to detect it on a SAR image or a time series of SAR images. Within this framework, we also studied the use of a multi-temporal and multi-sensor combination between Sentinel-1 SAR and Sentinel-2 optical images. Finally, as part of a preliminary study on denoising methods applied to water detection, we studied the statistical properties of the geometric temporal mean and proposed an adaptation of the variational method MuLoG to denoise it. Note de contenu : 1. Introduction 1.1 Context 1.2 Contributions 1.3 Organization of the manuscript I BACKGROUND ON SAR REMOTE SENSING AND WATER SURFACE MONITORING WITH SAR IMAGES 2. SAR images 2.1 Physics and statistics of SAR images 2.2 The SWOT mission 2.3 Sentinel-1 3. SAR water detection and hydrological prior 3.1 Water detection in SAR images 3.2 SWOT processing and products 3.3 Prior water masks and databases 4. Methodological background 4.1 Markov random fields 4.2 Variational methods for image denoising PROPOSED APPROACHES 5. Guided extraction of narrow rivers on SAR images using an exogenous river database 5.1 Introduction 5.2 Proposed river segmentation pipeline 5.3 Experimental results 5.4 Conclusion 6. Adaptation of the GrabCut method to SAR images: lake detection from a priori polygon 6.1 Single-date GrabCut method for lake detection from a priori polygon 6.2 Multitemporal and multi-sensor adaptations of the method 6.3 2D+T GrabCut of SAR images with temporal regularization for lake detection within an a priori mask 6.4 Joint 2D+T segmentation of SAR and optical images 7. Denoising of the temporal geometric mean 7.1 Introduction 7.2 Statistics of the temporal geometric mean of SAR intensities 7.3 Denoising method 7.4 Experiments 7.5 Application to change detection 7.6 Application to ratio-based denoising of single SAR images within a time series 7.7 Conclusion 8 Conclusion and perspectives Numéro de notice : 26762 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Images : Palaiseau : 2022 Organisme de stage : Télécom Paris nature-HAL : Thèse DOI : sans Date de publication en ligne : 17/02/2022 En ligne : https://tel.archives-ouvertes.fr/tel-03578831/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99823

Particle swarm optimization based water index (PSOWI) for mapping the water extents from satellite images / Mohammad Hossein Gamshadzaei in Geocarto international, vol 36 n° 20 ([01/12/2021])  

Public [article]  inGeocarto international > vol 36 n° 20 [01/12/2021] . - pp 2264 - 2278 Titre : Particle swarm optimization based water index (PSOWI) for mapping the water extents from satellite images Type de document : Article/Communication Auteurs : Mohammad Hossein Gamshadzaei, Auteur ; Majid Rahimzadegan, Auteur Année de publication : 2021 Article en page(s) : pp 2264 - 2278 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse multibande [Termes IGN] analyse spectrale [Termes IGN] Arménie [Termes IGN] bande infrarouge [Termes IGN] cartographie thématique [Termes IGN] détection d'objet [Termes IGN] eau de surface [Termes IGN] extraction de traits caractéristiques [Termes IGN] Google Earth [Termes IGN] image à haute résolution [Termes IGN] image satellite [Termes IGN] indice d'humidité [Termes IGN] Iran [Termes IGN] occupation du sol [Termes IGN] optimisation par essaim de particules [Termes IGN] polygone Résumé : (auteur) Various spectral indices have been introduced to detect water extent from satellite images with different performances in various regions. The aim of this study is to provide an efficient index using particle swarm optimization (PSO) algorithm to detect water spread areas from satellite images with similar performance in different regions. This index is introduced for images containing water absorption bands from visible to middle infrared wavelengths. Eleven images were prepared from different satellites and water bodies with various environmental conditions. In addition, 40 pixels from water and 40 pixels from non-water regions were selected as training data for PSO algorithm. Results were evaluated using digitized polygons of water bodies on high-resolution images of Google Earth. The best results in PSO-based water index (PSOWI) were obtained by the combination of two bands (red and middle infrared). PSOWI represented proper performance in the selected various land covers and satellite images. Numéro de notice : A2021-831 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1700554 Date de publication en ligne : 12/12/2019 En ligne : https://doi.org/10.1080/10106049.2019.1700554 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99004 [article]

Spatial variability of suspended sediments in San Francisco Bay, California / Niky C. Taylor in Remote sensing, vol 13 n° 22 (November-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 22 (November-2 2021) . - n° 4625 Titre : Spatial variability of suspended sediments in San Francisco Bay, California Type de document : Article/Communication Auteurs : Niky C. Taylor, Auteur ; Raphael M. Kudela, Auteur Année de publication : 2021 Article en page(s) : n° 4625 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] baie [Termes IGN] échantillonnage [Termes IGN] estuaire [Termes IGN] image Sentinel-MSI [Termes IGN] pas d'échantillonnage au sol [Termes IGN] qualité des eaux [Termes IGN] réflectance [Termes IGN] San Francisco [Termes IGN] sédiment [Termes IGN] spectroradiométrie [Termes IGN] surface de l'eau [Termes IGN] surveillance du littoral [Termes IGN] turbidité des eaux [Termes IGN] variabilité Résumé : (auteur) Understanding spatial variability of water quality in estuary systems is important for making monitoring decisions and designing sampling strategies. In San Francisco Bay, the largest estuary system on the west coast of North America, tracking the concentration of suspended materials in water is largely limited to point measurements with the assumption that each point is representative of its surrounding area. Strategies using remote sensing can expand monitoring efforts and provide a more complete view of spatial patterns and variability. In this study, we (1) quantify spatial variability in suspended particulate matter (SPM) concentrations at different spatial scales to contextualize current in-water point sampling and (2) demonstrate the potential of satellite and shipboard remote sensing to supplement current monitoring methods in San Francisco Bay. We collected radiometric data from the bow of a research vessel on three dates in 2019 corresponding to satellite overpasses by Sentinel-2, and used established algorithms to retrieve SPM concentrations. These more spatially comprehensive data identified features that are not picked up by current point sampling. This prompted us to examine how much variability exists at spatial scales between 20 m and 10 km in San Francisco Bay using 10 m resolution Sentinel-2 imagery. We found 23–80% variability in SPM at the 5 km scale (the scale at which point sampling occurs), demonstrating the risk in assuming limited point sampling is representative of a 5 km area. In addition, current monitoring takes place along a transect within the Bay’s main shipping channel, which we show underestimates the spatial variance of the full bay. Our results suggest that spatial structure and spatial variability in the Bay change seasonally based on freshwater inflow to the Bay, tidal state, and wind speed. We recommend monitoring programs take this into account when designing sampling strategies, and that end-users account for the inherent spatial uncertainty associated with the resolution at which data are collected. This analysis also highlights the applicability of remotely sensed data to augment traditional sampling strategies. In sum, this study presents ways to supplement water quality monitoring using remote sensing, and uses satellite imagery to make recommendations for future sampling strategies. Numéro de notice : A2021-839 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13224625 Date de publication en ligne : 17/11/2021 En ligne : https://doi.org/10.3390/rs13224625 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99022 [article]

Tidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region / Paulo Victor N. Araújo in Natural Hazards and Earth System Sciences, vol 21 n° 11 (November 2021)  

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Automatic detection of inland water bodies along altimetry tracks for estimating surface water storage variations in the Congo basin / Frédéric Frappart in Remote sensing, vol 13 n° 19 (October-1 2021)  

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Combining photogrammetric and bathymetric data to build a 3D model of a canal tunnel / Emmanuel Moisan in Photogrammetric record, Vol 36 n° 175 (September 2021)  

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Ten years of Lake Taupō surface height estimates using the GNSS interferometric reflectometry / Lucas D. Holden in Journal of geodesy, vol 95 n° 7 (July 2021)  

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Fluvial gravel bar mapping with spectral signal mixture analysis / Liza Stančič in European journal of remote sensing, vol 54 sup 1 (2021)  

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Streams and rural abandonment are related to the summer activity of the invasive pest Drosophila suzukii in protected European forests / Alberto Maceda-Veiga in Forest ecology and management, vol 485 ([01/04/2021])  

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Evaluation du potentiel des series d’images multi-temporelles optique et radar des satellites Sentinel 1 & 2 pour le suivi d’une zone côtière en contexte tropical: cas de l’estuaire du Cameroun pour la période 2015-2020 / Nourdi Njutapvoui in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)  

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GIS-based spatial landslide distribution analysis of district Neelum, AJ&K, Pakistan / Shah Naseer in Natural Hazards, vol 106 n° 1 (March 2021)  

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Integrating runoff map of a spatially distributed model and thematic layers for identifying potential rainwater harvesting suitability sites using GIS techniques / Hamid Karimi in Geocarto international, vol 36 n° 3 ([15/02/2021])  

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Dynamics of inundation events in the rivers-estuaries-ocean continuum in Bengal delta : synergy between hydrodynamic modelling and spaceborne remote sensing / Md Jamal Uddin Kahn (2021)  

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