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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)  

Public [article]  inForest ecology and management > vol 528 (January-15 2023) . - n° 120639 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 tampon Résumé : (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 [article]

Comparative analysis of estimation of slope-length gradient (LS) factor for entire Afghanistan / Ahmad Ansari in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 14 n° 1 (2023) . - n° 2200890 Titre : Comparative analysis of estimation of slope-length gradient (LS) factor for entire Afghanistan Type de document : Article/Communication Auteurs : Ahmad Ansari, Auteur ; Gökmen Tayfur, Auteur Année de publication : 2023 Article en page(s) : n° 2200890 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Afghanistan [Termes IGN] bassin hydrographique [Termes IGN] érosion [Termes IGN] gradient de pente [Termes IGN] modèle numérique de surface [Termes IGN] modèle RUSLE [Termes IGN] système d'information géographique Résumé : (auteur) Slope length gradient (LS) is one of the crucial factors in the Universal Soil Loss Equations (USLE, RUSLE). This study aimed at estimating the slope-length and slope-steepness (LS) factor for the entire watersheds of Afghanistan by using three different methods, namely; (1) LS-TOOLMFD (Method 1); (2) The Method of Equations (Method 2); and (3) The approach of Moore and Burch (Method 3). The first method uses the digital elevation model (DEM) in the ASCII format, and the other two methods use the DEM in the spatial domain. The results show that the LS-factor of the study area ranges from 0.01 to 44.31, with a mean of 5.24 and standard deviation of 6.95, according to Method 1; 0.03 to 163.49, with a mean of 9.6 and standard deviation of 13.58, according to Method 2; and 0 to 3985, with a mean of 7.16 and standard deviation of 29.7, according to Method 3. The study reveals that Methods 1 and 2 are more appropriate than Method 3 because Method 3 yields high LS-factor values close to or at streamlines located near mountainous regions. The highest LS values are found to be in the northeast, north, and central regions of Afghanistan, which is consistent with the high mountains and deep valley geomorphology, indicating that these regions are particularly vulnerable to soil erosion by rainfall-runoff processes. The sediment delivery ratio (SDR) for the Upper-Helmand River Basin (Upper-HRB) is also estimated by the RUSLE, employing the LS factors produced by the three methods. The results revealed that the average annual soil loss is found to be, respectively, 9.3, 18.2, and 11.1 (ton/ha/year) by using the three methods, corresponding to SDR of 23.5%, 12.1%, and 19.9%. Numéro de notice : A2023-193 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475705.2023.2200890 Date de publication en ligne : 18/04/2023 En ligne : https://doi.org/10.1080/19475705.2023.2200890 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103074 [article]

Sediment yield estimation in GIS environment using RUSLE and SDR model in Southern Ethiopia / Dawit Kanito in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 14 n° 1 (2023) . - n° 2167614 Titre : Sediment yield estimation in GIS environment using RUSLE and SDR model in Southern Ethiopia Type de document : Article/Communication Auteurs : Dawit Kanito, Auteur ; Dawit Bedadi, Auteur ; Samuel Feyissa, Auteur Année de publication : 2023 Article en page(s) : n° 2167614 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse de sensibilité [Termes IGN] bassin hydrographique [Termes IGN] Ethiopie [Termes IGN] image Landsat [Termes IGN] modèle RUSLE [Termes IGN] précipitation [Termes IGN] sédiment [Termes IGN] système d'information géographique Résumé : (auteur) Soil erosion and sediment yields are the current limitations and future threats to agriculture, water resources and hydropower projects particularly in developing countries. Estimating the extent and comprehending the spatial distribution of hotspot area is crucial to implement evidence-based soil and water conservation (SWC) measures with limited resources. The study used RUSLE and SDR models in ArcGIS 10.8 environment. The RUSLE model was found to be highly sensitive to C factor followed by LS factor. The result indicated that the annual soil loss varies from 0 to 359.99 t ha−1 yr−1 with 22.31 t ha−1 yr−1 as a mean annual. Besides, the estimated sediment yield ranged from 0 to 42.5 t ha−1 yr−1 with a mean value of 12.02 t ha−1 yr−1. The finding revealed that the central west (SW_5) and northeast (SW_4) parts of the watershed yield higher sediment. The result also signified that about 52.9% of the eroded materials including soil and nutrients are transferred to the outlet. The outcome of our finding undoubtedly aids in the identification of hotspot areas for the adoption of appropriate SWC measures. Hence, adopting RUSLE and SDR for Gununo watershed and another watershed having similar biophysical and environmental factors is suggested. Numéro de notice : A2023-155 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475705.2023.2167614 Date de publication en ligne : 26/01/2023 En ligne : https://doi.org/10.1080/19475705.2023.2167614 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102841 [article]

Coastal land use and shoreline evolution along the Nador lagoon Coast in Morocco / Khalid El Khalidi in Geocarto international, vol 37 n° 25 ([01/12/2022])  

Public [article]  inGeocarto international > vol 37 n° 25 [01/12/2022] . - pp 7445 - 7461 Titre : Coastal land use and shoreline evolution along the Nador lagoon Coast in Morocco Type de document : Article/Communication Auteurs : Khalid El Khalidi, Auteur ; Amine Bourhili, Auteur ; Ingrida Bagdanavičiūtė, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 7445 - 7461 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] changement d'occupation du sol [Termes IGN] Corine Land Cover [Termes IGN] érosion côtière [Termes IGN] littoral méditerranéen [Termes IGN] Maroc [Termes IGN] orthoimage [Termes IGN] photographie aérienne [Termes IGN] surveillance du littoral [Termes IGN] système d'information géographique [Termes IGN] trait de côte [Termes IGN] utilisation du sol Résumé : (auteur) The coastal zone, a highly dynamic and complex environment, has important ecological and jurisdictional implications for governments and coastal managers. Based on the CORINE Land Cover classification system, this paper examined the effects of land use and land cover change (LULC) on the coastlines' dynamics along the ∼24 km barrier island of Nador lagoon on the Mediterranean coast of Morocco during a period of 62 years (1954–2016). The study utilized high-resolution orthoimages in the geographic information system (GIS) environment to characterize coastline evolution and LULC changes. The evolution of the coastline was assessed using a GIS tool, in particular the Digital Shoreline Analysis System (DSAS). The net rates of coastline change were calculated by using statistical methods: the End Point Rate (EPR) and the Linear Regression Rate (LRR). Results concerning the LULC changes showed that agricultural area and beach/dune classes decreased over the entire study period (62 years) by 11.14% and 28.45%, respectively. Urban fabric, shrub, forest, and saltmarsh/peat bog classes increased during the 62 years of evaluation by 2.69%, 19.92%, 16.77%, and 0.19%, respectively. Results regarding coastal analysis indicated that the accretion and erosion processes along the barrier island of the Nador lagoon (∼24km) were observed at 45% (10.6 km) and 55% (12.8 km) of the coastline, respectively. The beaches of Oulad Zehra and Oulad Aissa were characterized by erosion (−0.58 m/yr to −0.57 m/yr respectively), while accretion was observed on the beaches of Boukana and Kariat Arkmane at rates of +2.15 m/yr and +0.82 m/yr, respectively. This study highlighted that natural and anthropogenic processes have a strong influence on the erosion/accretion trends identified along the barrier island of Nador lagoon. The changes in LULC have affected the barrier island of the lagoon in two different forms: (1) a significant spatial conversion due to dune reforestation and (2) a fundamental spatial modification that affects the sea-lagoon connection (inlet) and the construction of new hard engineering structures. Numéro de notice : A2022-927 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10106049.2021.1974958 Date de publication en ligne : 15/09/2021 En ligne : https://doi.org/10.1080/10106049.2021.1974958 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102660 [article]

Exploring the influencing factors in identifying soil texture classes using multitemporal Landsat-8 and Sentinel-2 data / Yanan Zhou in Remote sensing, vol 14 n° 21 (November-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 21 (November-1 2022) . - n° 5571 Titre : Exploring the influencing factors in identifying soil texture classes using multitemporal Landsat-8 and Sentinel-2 data Type de document : Article/Communication Auteurs : Yanan Zhou, Auteur ; Wei Wu, Auteur ; Hongbin Liu, Auteur Année de publication : 2022 Article en page(s) : n° 5571 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'occupation du sol [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] composition des sols [Termes IGN] données multitemporelles [Termes IGN] Extreme Gradient Machine [Termes IGN] Fleuve bleu (Chine) [Termes IGN] image Landsat-8 [Termes IGN] image Sentinel-MSI [Termes IGN] limon [Termes IGN] qualité du sol [Termes IGN] réflectance spectrale [Termes IGN] texture du sol Résumé : (auteur) Soil texture is a key soil property driving physical, chemical, biological, and hydrological processes in soils. The rapid development of remote sensing techniques shows great potential for mapping soil properties. This study highlights the effectiveness of multitemporal remote sensing data in identifying soil textural class by using retrieved vegetation properties as proxies of soil properties. The impacts of sensors, modeling resolutions, and modeling techniques on the accuracy of soil texture classification were explored. Multitemporal Landsat-8 and Sentinel-2 images were individually acquired at the same time periods. Three satellite-based experiments with different inputs, i.e., Landsat-8 data, Sentinel-2 data (excluding red-edge parameters), and Sentinel-2 data (including red-edge parameters) were conducted. Modeling was carried out at three spatial resolutions (10, 30, 60 m) using five machine-learning (ML) methods: random forest, support vector machine, gradient-boosting decision tree, categorical boosting, and super learner that combined the four former classifiers based on the stacking concept. In addition, a novel SHapley Addictive Explanation (SHAP) technique was introduced to explain the outputs of the ML model. The results showed that the sensors, modeling resolutions, and modeling techniques significantly affected the prediction accuracy. The models using Sentinel-2 data with red-edge parameters performed consistently best. The models usually gave better results at fine (10 m) and medium (30 m) modeling resolutions than at a coarse (60 m) resolution. The super learner provided higher accuracies than other modeling techniques and gave the highest values of overall accuracy (0.8429), kappa (0.7611), precision (0.8378), recall rate (0.8393), and F1-score (0.8398) at 30 m with Sentinel-2 data involving red-edge parameters. The SHAP technique quantified the contribution of each variable for different soil textural classes, revealing the critical roles of red-edge parameters in separating loamy soils. This study provides comprehensive insights into the effective modeling of soil properties on various scales using multitemporal optical images. Numéro de notice : A2022-856 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14215571 Date de publication en ligne : 04/11/2022 En ligne : https://doi.org/10.3390/rs14215571 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102104 [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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Correcting laser scanning intensity recorded in a cave environment for high-resolution lithological mapping: A case study of the Gouffre Georges, France / Michaela Nováková in Remote sensing of environment, vol 280 (October 2022)  

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Developing a GIS-based rough fuzzy set granulation model to handle spatial uncertainty for hydrocarbon structure classification, case study: Fars domain, Iran / Sahand Seraj in Geo-spatial Information Science, vol 25 n° 3 (October 2022)  

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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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Prediction of suspended sediment concentration using hybrid SVM-WOA approaches / Sandeep Samantaray in Geocarto international, vol 37 n° 19 ([15/09/2022])  

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Detection of potential gold mineralization areas using MF-fuzzy approach on multispectral data / Tohid Nouri in Geocarto international, Vol 37 n° 17 ([20/08/2022])  

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Advancements in underground mine surveys by using SLAM-enabled handheld laser scanners / Artu Ellmann in Survey review, vol 54 n° 385 (July 2022)  

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Assessing and mapping landslide susceptibility using different machine learning methods / Osman Orhan in Geocarto international, vol 37 n° 10 ([01/06/2022])  

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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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Efficient dike monitoring using terrestrial SFM photogrammetry / Laurent Froideval in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  

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