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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])
[article]
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] polygoneRésumé : (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
in Geocarto international > vol 36 n° 20 [01/12/2021] . - pp 2264 - 2278[article]Snow cover change assessment in the upper Bhagirathi basin using an enhanced cloud removal algorithm / Mritunjay Kumar Singh in Geocarto international, vol 36 n° 20 ([01/12/2021])
[article]
Titre : Snow cover change assessment in the upper Bhagirathi basin using an enhanced cloud removal algorithm Type de document : Article/Communication Auteurs : Mritunjay Kumar Singh, Auteur ; Renoj J. Thayyen, Auteur ; Sanjay K. Jain, Auteur Année de publication : 2021 Article en page(s) : pp 2279 - 2302 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] analyse spatio-temporelle
[Termes IGN] bassin hydrographique
[Termes IGN] bilan de masse
[Termes IGN] changement climatique
[Termes IGN] eau de fonte
[Termes IGN] filtrage spatiotemporel
[Termes IGN] glacier
[Termes IGN] Himalaya
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] Inde
[Termes IGN] manteau neigeux
[Termes IGN] MNS ASTER
[Termes IGN] nébulosité
[Termes IGN] nuage
[Termes IGN] variation saisonnièreRésumé : (auteur) This research paper proposes a new five-step protocol to enhance the result of existing cloud removal algorithms using Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products (SCPs). The study has been carried out for the upper Bhagirathi basin (up to Maneri Hydropower Project) located in the Western Himalaya. Gafurov and Bárdossy test employed to validate the performance of the proposed method, followed by comparing with the field observed snow cover duration (SCD) data. The result shows that the mean overall accuracy of the proposed method for cloud removal is about ∼95%. However, the cloud removal method by Gafurov and Bardossy also achieved similar mean overall accuracy but with the higher variability within the individual images as compared with the variability within the results obtained by the proposed method. SCD computed from cloud removed SCPs matched significantly with the field observed SCD for a point location, supporting the accuracy achieved by the cloud removal method. This study also examines the spatiotemporal variability of the snow cover in the study area during the past 18 years (2000–2018). During the observation period, no specific trend was observed for annual maximum snow cover, while yearly minimum snow cover in the basin showed an increasing trend since 2010. Seasonally, December and June month witnessed significant changes. December experienced a declining trend in snow cover between 3000–6000 m a.s.l. covering 88% of the basin area, whereas, June showed an increasing trend between 4500 to 6000 m (a.s.l.). This elevation range covers 61% of the basin area, including core 86% of the glacier area within the basin. September and October experienced the highest inter-annual snow cover variability. Maximum snow cover month of February and minimum snow cover month of August experienced the least variability. The present study suggests significant elevation-dependent increasing as well as the decreasing trend in the snow cover with seasonal contrast, which may affect the glaciers as well as the hydrological behavior of the basin. Numéro de notice : A2021-832 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1704069 Date de publication en ligne : 19/12/2021 En ligne : https://doi.org/10.1080/10106049.2019.1704069 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99005
in Geocarto international > vol 36 n° 20 [01/12/2021] . - pp 2279 - 2302[article]Spatial variability of suspended sediments in San Francisco Bay, California / Niky C. Taylor in Remote sensing, vol 13 n° 22 (November-2 2021)
[article]
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] variabilitéRésumé : (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
in Remote sensing > vol 13 n° 22 (November-2 2021) . - n° 4625[article]Evaluation of watershed soil erosion hazard using combination weight and GIS: a case study from eroded soil in Southern China / Shifa Chen in Natural Hazards, vol 109 n° 2 (November 2021)
[article]
Titre : Evaluation of watershed soil erosion hazard using combination weight and GIS: a case study from eroded soil in Southern China Type de document : Article/Communication Auteurs : Shifa Chen, Auteur ; Wen Liu, Auteur ; Yonghui Bai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1603 - 1628 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] ArcGIS
[Termes IGN] bassin hydrographique
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte thématique
[Termes IGN] cartographie des risques
[Termes IGN] Chine
[Termes IGN] combinaison linéaire ponderée
[Termes IGN] entropie
[Termes IGN] érosion hydrique
[Termes IGN] modèle numérique de surface
[Termes IGN] pondération
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] risque naturelRésumé : (auteur) Soil erosion is a type of land degradation caused by the interactive interaction of numerous factors, such as natural and socioeconomic conditions of a particular watershed. In this study, a comprehensive integrated methodology was used to evaluate the water erosion hazard in the Zhuxi watershed in Southern China, which is greatly affected by eroded soil. Ten indicators were selected, and a thematic layer map was generated for each indicator using Geographic Information System (GIS). The weight of each evaluation indicator was determined by combining analytic hierarchy process (AHP) with entropy method. Results show that the east and west sections of the Zhuxi watershed have very low and low grades of soil erosion hazards, respectively, and the middle part has the highest hazard. More than 60% of the area has high erosion hazard (moderate to very high). The intensity of soil erosion is lower than its hazard level, especially in high-grade hazard. The obtained results for erosion hazard level can be used to develop conservation strategies for the Zhuxi watershed. This study evaluates soil erosion hazard and offers reference for soil erosion control. Numéro de notice : A2021-851 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-021-04891-7 Date de publication en ligne : 05/07/2021 En ligne : https://doi.org/10.1007/s11069-021-04891-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99036
in Natural Hazards > vol 109 n° 2 (November 2021) . - pp 1603 - 1628[article]Potential flood hazard zone mapping based on geomorphologic considerations and fuzzy analytical hierarchy model in a data scarce West African basin / Olabanji Aladejana in Geocarto international, vol 36 n° 19 ([01/11/2021])
[article]
Titre : Potential flood hazard zone mapping based on geomorphologic considerations and fuzzy analytical hierarchy model in a data scarce West African basin Type de document : Article/Communication Auteurs : Olabanji Aladejana, Auteur ; Ayobami T Salami, Auteur ; Olusola Olufayo Adetoro, Auteur Année de publication : 2021 Article en page(s) : pp 2160 - 2185 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] analyse de sensibilité
[Termes IGN] bassin hydrographique
[Termes IGN] Bénin
[Termes IGN] carte géomorphologique
[Termes IGN] cartographie des risques
[Termes IGN] indice d'humidité
[Termes IGN] inondation
[Termes IGN] processus de hiérarchisation analytique floue
[Termes IGN] ruissellement
[Termes IGN] système d'information géographiqueRésumé : (auteur) Fuzzy analytical hierarchy process (FAHP) was employed to map and rank flood hazard zones within the Northwest Benin Owena River Basin (NWBORB). Topographic wetness index, elevation, altitude above channel, slope, drainage density, convergence index, and runoff contributing to water accumulation/stagnation were processed to generate the flood hazard map of the basin. Values for the relative importance of each factor for flood occurrence were obtained using FAHP; these factors were super-imposed using weighted overlay. Sensitivity analysis of the weights was conducted to determine their influence on the overall analysis. The resultant flood hazard map was classified into five zones very high, high, moderate, low, and very low. Sensitivity analysis of the result showed that runoff and slope were the most sensitive factors in the analysis with values of 1.163 and 1.132, respectively. A comparison between flood hazard map and historical floods within the basin established the reliability of the methodology. Numéro de notice : A2021-764 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1687595 Date de publication en ligne : 11/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1687595 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98809
in Geocarto international > vol 36 n° 19 [01/11/2021] . - pp 2160 - 2185[article]A repeatable change detection approach to map extreme storm-related damages caused by intense surface runoff based on optical and SAR remote sensing: Evidence from three case studies in the South of France / Arnaud Cerbelaud in ISPRS Journal of photogrammetry and remote sensing, Vol 182 (December 2021)PermalinkTidal 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)PermalinkA vector-based method for drainage network analysis based on LiDAR data / Fangzheng Lyu in Computers & geosciences, vol 156 (November 2021)PermalinkAutomatic 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)PermalinkComparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada / Bernadett Dobre in Transactions in GIS, vol 25 n° 5 (October 2021)PermalinkDisaster intensity-based selection of training samples for remote sensing building damage classification / Luis Moya in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)PermalinkFlood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model / Gaurav Talukdar in Natural Hazards, vol 109 n° 1 (October 2021)PermalinkGeomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques / Peter G. Chirico in Journal of maps, vol 17 n° 4 (October 2021)PermalinkCombining photogrammetric and bathymetric data to build a 3D model of a canal tunnel / Emmanuel Moisan in Photogrammetric record, Vol 36 n° 175 (September 2021)PermalinkDevelopment of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt / Soha A. Mohamed in Natural Hazards, vol 108 n° 3 (September 2021)PermalinkMise en place d'un dispositif expérimental numérique pour l'enseignement des risques naturels avec le jeu vidéo Minetest / Jérôme Staub in Cartes & Géomatique, n° 245-246 (septembre - décembre 2021)PermalinkSentinel-1 sensitivity to soil moisture at high incidence angle and the impact on retrieval over seasonal crops / Davide Palmisano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)PermalinkA high-efficiency global model of optimization design of impervious surfaces for alleviating urban waterlogging in urban renewal / Huafei Yu in Transactions in GIS, Vol 25 n° 4 (August 2021)PermalinkRapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning / Xin Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkTen 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)PermalinkDEM- and GIS-based analysis of soil erosion depth using machine learning / Kieu Anh Nguyen in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)PermalinkFlood depth mapping in street photos with image processing and deep neural networks / Bahareh Alizadeh Kharazi in Computers, Environment and Urban Systems, vol 88 (July 2021)PermalinkFluvial gravel bar mapping with spectral signal mixture analysis / Liza Stančič in European journal of remote sensing, vol 54 sup 1 (2021)PermalinkSpatio-temporal-spectral observation model for urban remote sensing / Zhenfeng Shao in Geo-spatial Information Science, vol 24 n° 3 (July 2021)PermalinkA framework to manage uncertainty in the computation of waste collection routes after a flood / Arnaud Le Guilcher in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2021 (July 2021)Permalink