Descripteur
Termes IGN > sciences naturelles > sciences de la Terre et de l'univers > géosciences > géologie > pétrologie > sédimentologie > érosion
érosion
Commentaire :
géomorphologie.
>> cycle d'érosion, vallée. >>Terme(s) spécifique(s) : affouillement (génie hydraulique), affouillement (géomorphologie), météorisation (géomorphologie). Equiv. LCSH : Erosion. Domaine(s) : 530, 550. Voir aussi |
Documents disponibles dans cette catégorie (319)



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GIS-based planning of buffer zones for protection of boreal streams and their riparian forests / Heikki Mykrä in Forest ecology and management, vol 528 (January-15 2023)
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Titre : GIS-based planning of buffer zones for protection of boreal streams and their riparian forests Type de document : Article/Communication Auteurs : Heikki Mykrä, Auteur ; M.J. Annala, Auteur ; Anu Hilli, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120639 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] Alnus incana
[Termes IGN] Betula pendula
[Termes IGN] cours d'eau
[Termes IGN] données lidar
[Termes IGN] érosion hydrique
[Termes IGN] forêt ripicole
[Termes IGN] humidité du sol
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle RUSLE
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] protection de la biodiversité
[Termes IGN] Salix (genre)
[Termes IGN] zone boréale
[Termes IGN] zone tamponRésumé : (auteur) Forested buffer zones with varying width have been suggested as the most promising approach for protecting boreal riparian biodiversity, reducing erosion, and minimizing nutrient leaching from managed forestry areas. Yet, less optimal fixed-width approach is still largely used, likely because of its simple design and implementation. We examined the efficiency of varying-width buffer zones based on depth-to-water (DTW) index in protecting stream riparian plant communities. We further compared the economic costs of DTW-based buffer to commonly used 5, 10 and 15 m fixed-width buffers. We also included an additional buffer based on a combination of DTW and erosion risk (Revised Universal Soil Loss Equation, RUSLE) into these comparisons to see the extent and cost of a buffer that should maximize the protection of the linked aquatic environment. Plant species richness increased with increasing soil moisture and species preferring moist conditions, nutrient-rich soils and high pH were clearly more abundant adjacent to stream in areas with high predicted soil moisture than in dry areas. Differences in species richness were paralleled by differences in community composition and higher beta diversity of plant communities in wet than in dry riparian areas. There were also several indicator species typical for moist and nutrient-rich soils for wet riparian areas. Riparian buffer zones based on DTW were on average larger than 15 m wide fixed-width buffers. However, the cost for DTW-based buffer was lower than for fixed-width buffer zones when the cost was normalized by area. Simulated selective cutting decreased the costs, but cutting possibilities were variable among streams and depended on the characteristics of forest stands. Our results thus suggest a high potential of DTW in predicting wet areas and variable-width buffer zones based on these areas in the protection of riparian biodiversity and stream ecosystems. Numéro de notice : A2023-029 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1016/j.foreco.2022.120639 Date de publication en ligne : 13/11/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120639 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102148
in Forest ecology and management > vol 528 (January-15 2023) . - n° 120639[article]GIS and MCDMA prioritization based modeling for sub-watershed in Bastora river basin / Raid Mahmood Faisal in Geocarto international, vol 37 n° 23 ([15/10/2022])
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Titre : GIS and MCDMA prioritization based modeling for sub-watershed in Bastora river basin Type de document : Article/Communication Auteurs : Raid Mahmood Faisal, Auteur Année de publication : 2022 Article en page(s) : pp 6826 - 6847 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse multicritère
[Termes IGN] ArcGIS
[Termes IGN] érosion
[Termes IGN] géomorphométrie
[Termes IGN] Iraq
[Termes IGN] modèle RUSLE
[Termes IGN] processus de hiérarchisation analytiqueRésumé : (auteur) This study examines the watersheds in the Bastora river basin and builds a geographic model within ARC GIS software. The work was divided into three phases. The first phase was to obtain the results of 14 morphometric parameters to determine priorities, by using AHP model to extract the relative weights of the parameters. Then, these weights are adopted in building (SDI, TOPSIS and SAW) models to determine levels of priorities. The outputs were classified into five categories according to the degree of their susceptibility to erosion. The second phase includes creating another model to provide necessary data and tools for building the RUSLE model. The final phase validates of pairs of models (TOPSIS-RUSLE), (SDI-RUSLE), and (SAW-RUSLE) using least squares tool for comparison between the results. The results indicate a highly statistically significant relationship among all the previous pairs of models with clear preference recorded for (TOPSIS-RUSLE) models relationship. Numéro de notice : A2022-751 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1950848 Date de publication en ligne : 26/07/2021 En ligne : https://doi.org/10.1080/10106049.2021.1950848 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101743
in Geocarto international > vol 37 n° 23 [15/10/2022] . - pp 6826 - 6847[article]Remote sensing and GIS based Soil Loss Estimation for Bhutan, using RUSLE model / Sangay Gyeltshen in Geocarto international, Vol 37 n° 21 ([01/10/2022])
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Titre : Remote sensing and GIS based Soil Loss Estimation for Bhutan, using RUSLE model Type de document : Article/Communication Auteurs : Sangay Gyeltshen, Auteur ; Rabindra Adhikarib, Auteur ; Padam Bahadur Budha, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 6331 - 6350 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Bhoutan
[Termes IGN] distribution spatiale
[Termes IGN] effondrement de terrain
[Termes IGN] érosion
[Termes IGN] modèle RUSLE
[Termes IGN] système d'information géographique
[Termes IGN] télédétection
[Termes IGN] utilisation du solRésumé : (auteur) The repository of soil by water at a national and basin scale was estimated using the RUSLE empirical model which is the first of its kind in Bhutan. The annual soil loss is estimated and categorized into five categories: very low (800 t/yr). Sakteng and Jaldakha basins contributed the highest soil loss rate of 0.04 and 0.039 t/ha/yr, while considering on landuse pattern, non-built-up and landslide category encountered the highest soil loss of 4.09 and 0.7 t/ha/yr among others. Similarly, Tsirang, Samtse and Haa contributed the major soil loss of 0.03, 0.0298 and 0.02 t/ha/yr, respectively. The research can be used as an authentic instrument enabling the soil conservationist and the policymakers to evaluate the adverse impacts, prioritize the conservation efforts and investigate further to narrow down the causes of soil erosion. Numéro de notice : A2022-718 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1080/10106049.2021.1936210 Date de publication en ligne : 22/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1936210 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101646
in Geocarto international > Vol 37 n° 21 [01/10/2022] . - pp 6331 - 6350[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2022211 SL Revue Centre de documentation Revues en salle Disponible Cliff change detection using siamese KPCONV deep network on 3D point clouds / Iris de Gelis in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)
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Titre : Cliff change detection using siamese KPCONV deep network on 3D point clouds Type de document : Article/Communication Auteurs : Iris de Gelis, Auteur ; Zoé Bessin, Auteur ; Pauline Letortu, Auteur ; Marion Jaud, Auteur ; C. Delacourt, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 649 - 656 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] érosion côtière
[Termes IGN] falaise
[Termes IGN] semis de points
[Termes IGN] surveillance géologiqueMots-clés libres : KPConv = Kernel Point Convolution Résumé : (auteur) Mainly depending on their lithology, coastal cliffs are prone to changes due to erosion. This erosion could increase due to climate change leading to potential threats for coastal users, assets, or infrastructure. Thus, it is important to be able to understand and characterize cliff face changes at fine scale. Usually, monitoring is conducted thanks to distance computation and manual analysis of each cliff face over 3D point clouds to be able to study 3D dynamics of cliffs. This is time consuming and inclined to each one judgment in particular when dealing with 3D point clouds data. Indeed, 3D point clouds characteristics (sparsity, impossibility of working on a classical top view representation, volume of data, …) make their processing harder than 2D images. Last decades, an increase of performance of machine learning methods for earth observation purposes has been performed. To the best of our knowledge, deep learning has never been used for 3D change detection and categorization in coastal cliffs. Lately, Siamese KPConv brings successful results for change detection and categorization into 3D point clouds in urban area. Although the case study is different by its more random characteristics and its complex geometry, we demonstrate here that this method also allows to extract and categorize changes on coastal cliff face. Results over the study area of Petit Ailly cliffs in Varengeville-sur-Mer (France) are very promising qualitatively as well as quantitatively: erosion is retrieved with an intersection over union score of 83.86 %. Numéro de notice : A2022-444 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-3-2022-649-2022 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-3-2022-649-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100779
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-3-2022 (2022 edition) . - pp 649 - 656[article]Influence of determinant factors towards soil erosion using ordinary least squared regression in GIS domain / Imran Ahmad in Applied geomatics, vol 14 n° 1 (March 2022)
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Titre : Influence of determinant factors towards soil erosion using ordinary least squared regression in GIS domain Type de document : Article/Communication Auteurs : Imran Ahmad, Auteur ; Jahier Abbas Shaaikh, Auteur ; Assefa Fenta, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 57 - 63 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] autocorrélation spatiale
[Termes IGN] érosion
[Termes IGN] Ethiopie
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle de régression
[Termes IGN] modèle RUSLE
[Termes IGN] régression
[Termes IGN] système d'information géographiqueRésumé : (auteur) An attempt has been made in this study to analyze the hotspots of soil erosion in Denbie Woreda, Ethiopia. A total of five determinant factors were multiplied (using raster calculator in GIS domain) and integrated to obtain the soil erosion hotspots of the area. These five determinant factors were used as exploratory variables to understand the spatial behavior of soil loss rates. The ordinary least squared (OLS) regression model diagnostics showed that the R-squared and adjusted R-squared values of the explanatory variables are 0.71 and 0.75 respectively. Variance inflation factor (VIF) values of the OLS range between 1.03 and 1.47 indicating the absence of multicollinearity among explanatory variables. Koenker (BP) statistic is statistically insignificant (p > 0.005) indicating that relationships modeled are consistent. The OLS regression model was subject to different tests to confirm its reliability. Spatial autocorrelation tool (Global Moran’s I) result showed that the residuals exhibit a Gaussian spatial pattern. This study proved that all the determinant factors of Revised Universal Soil Loss Equation played a significant role towards demarcation of soil loss rates. Numéro de notice : A2022-217 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s12518-021-00409-9 Date de publication en ligne : 27/11/2021 En ligne : https://doi.org/10.1007/s12518-021-00409-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100087
in Applied geomatics > vol 14 n° 1 (March 2022) . - pp 57 - 63[article]Monitoring coastal vulnerability by using DEMs based on UAV spatial data / Antonio Minervino Amodio in ISPRS International journal of geo-information, vol 11 n° 3 (March 2022)
PermalinkAssessment and mapping soil water erosion using RUSLE approach and GIS tools: Case of Oued el-Hai watershed, Aurès West, Northeastern of Algeria / Aida Bensekhria in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)
PermalinkSoil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS / Sumedh R. Kashiwar in Natural Hazards, vol 110 n° 2 (January 2022)
PermalinkÉvolution rétrospective et prospective d’un massif dunaire par imagerie multispectrale et LiDAR / Iris Jeuffrard (2022)
PermalinkHistorical shoreline analysis and field monitoring at Ennore coastal stretch along the Southeast coast of India / M. Dhananjayan in Marine geodesy, vol 45 n° 1 (January 2022)
PermalinkModalités et rythmes d'évolution des falaises des Vaches Noires (Normandie, France) : caractérisation et quantification des dynamiques hydrogravitaires par approches multi-scalaires / Thomas Roulland (2022)
PermalinkGIS to identify exposed shoreline sectors to wave impacts: case of El Tarf coast / Abdeldjalil Goumrasa in Applied geomatics, vol 13 n° 4 (December 2021)
PermalinkOBIA-based extraction of artificial terrace damages in the Loess plateau of China from UAV photogrammetry / Xuan Fang in ISPRS International journal of geo-information, vol 10 n° 12 (December 2021)
PermalinkEfficient measurement of large-scale decadal shoreline change with increased accuracy in tide-dominated coastal environments with Google Earth Engine / Yongjing Mao in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)
PermalinkEvaluation 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)
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