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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)  

Public [article]  inApplied geomatics > vol 14 n° 1 (March 2022) . - pp 57 - 63 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 géographique Résumé : (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 [article]

Assessment 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)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 2 (February 2022) . - n° 84 Titre : Assessment and mapping soil water erosion using RUSLE approach and GIS tools: Case of Oued el-Hai watershed, Aurès West, Northeastern of Algeria Type de document : Article/Communication Auteurs : Aida Bensekhria, Auteur ; Rabah Bouhata, Auteur Année de publication : 2022 Article en page(s) : n° 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] Algérie [Termes IGN] Aurès, massif des [Termes IGN] bassin hydrographique [Termes IGN] carte thématique [Termes IGN] conservation des ressources naturelles [Termes IGN] érosion hydrique [Termes IGN] modèle RUSLE [Termes IGN] outil d'aide à la décision [Termes IGN] système d'information géographique Résumé : (auteur) The problem of soil water erosion is one of the primary causes of agro-pedological heritage degradation. The combined effect of natural factors and inappropriate human actions has weakened the soil, which seriously threatens the region’s fertile lands and soils, which can ultimately lead to an irreversible situation of desertification. This study focuses on analysis and mapping of the vulnerability to erosion in Oued el-Hai watershed, Algeria, based on a technical methodology that combines the universal soil loss equation (USLE) with the geographic information system (GIS) tools. The results are organized into three main classes of different rate values, from one area to another, depending on the influence of different factors that control the erosion process. The highest loss rate value is greater than 30 t·ha−1·yr−1 and covers 23.2% of the total area, mainly located in the mountainous areas with steep slopes. However, the minimum potential erosion rate value is mainly located on the plain, with an average of 10 t·ha−1·yr−1 covering 45.2% of the total area of the watershed. The estimate of potential water erosion has given alarming results. The total area of the watershed could lose a rate of 16.69 t·ha−1·yr−1 (on average) each year. The method and results described in this article are valuable for understanding the soil erosion risk and are useful for managing and planning land use that will avoid land degradation. Hence, the results of this study are considered an important document which constitutes a decision support tool in terms of the management and protection of natural resources. Numéro de notice : A2022-119 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11020084 Date de publication en ligne : 24/01/2022 En ligne : https://doi.org/10.3390/ijgi11020084 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99650 [article]

Soil 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)  

Public [article]  inNatural Hazards > vol 110 n° 2 (January 2022) . - pp 937 - 959 Titre : Soil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS Type de document : Article/Communication Auteurs : Sumedh R. Kashiwar, Auteur ; Manik Chandra Kundu, Auteur ; Usha R. Dongarwar, Auteur Année de publication : 2022 Article en page(s) : pp 937 - 959 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte d'occupation du sol [Termes IGN] carte thématique [Termes IGN] dégradation des sols [Termes IGN] érosion [Termes IGN] érosion hydrique [Termes IGN] image Landsat-8 [Termes IGN] image Sentinel-MSI [Termes IGN] Inde [Termes IGN] modèle numérique de surface [Termes IGN] modèle RUSLE [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] précipitation [Termes IGN] rive [Termes IGN] système d'information géographique Résumé : (auteur) The agricultural land of the whole world is deteriorating due to the loss of top fertile soil reducing agricultural productivity and groundwater availability. Mainly, natural conditions and human manipulations have made soils extremely prone to soil erosion. Therefore, information on soil erosion status is of paramount importance to the policymakers for land conservation planning in a limited time. Spatial information systems like GIS and RS are known for their efficiencies. With that prospect, the GIS-based RUSLE model is used in this study to assess the soil erosion losses from Bhandara regions of Maharashtra, India. The study area comes under Wainganga sub-river basin, a portion of the Godavari River basin. We have prepared the required five potential parameters (R*K*LS*C*P) of RUSLE model on pixel-to-pixel basis. We have prepared the R factor map from monthly rainfall data of Indian Meteorological Department (IMD) and K factor map by digital the soil series map of NBSS & LUP, Govt. of India. We have used the digital elevation model data (DEM) of Cartosat-1 for LS-factor map, Landsat 8 and Sentinel-2A satellite dataset to generate LULC and NDVI map to obtain C and P factors. The results and satellite data were validated using Google Earth Pro and field observations. The results showed significant soil erosion from the river banks and wastelands near water bodies, with the soil loss values ranging between 20 and 40 t ha−1 yr−1. The land under reserved forest was very slight erosion-prone soil with soil loss of  Numéro de notice : A2022-180 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s11069-021-04974-5 Date de publication en ligne : 16/08/2021 En ligne : https://doi.org/10.1007/s11069-021-04974-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99856 [article]

Assessing land use–land cover change and soil erosion potential using a combined approach through remote sensing, RUSLE and random forest algorithm / Siddhartho Shekhar Paul in Geocarto international, vol 36 n° 4 ([01/03/2021])  

Public [article]  inGeocarto international > vol 36 n° 4 [01/03/2021] . - pp 361 - 375 Titre : Assessing land use–land cover change and soil erosion potential using a combined approach through remote sensing, RUSLE and random forest algorithm Type de document : Article/Communication Auteurs : Siddhartho Shekhar Paul, Auteur ; Jianbing Li, Auteur ; Yubao Li, Auteur ; Lei Shen, Auteur Année de publication : 2021 Article en page(s) : pp 361 - 375 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bassin hydrographique [Termes IGN] changement d'occupation du sol [Termes IGN] classification orientée objet [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] coupe rase (sylviculture) [Termes IGN] détection de changement [Termes IGN] érosion [Termes IGN] modèle RUSLE [Termes IGN] occupation du sol [Termes IGN] qualité des eaux [Termes IGN] utilisation du sol Résumé : (auteur) Numéro de notice : A2021-161 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1614099 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1614099 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97081 [article]

Soil erosion / António Vieira (2021)  

Public Titre : Soil erosion : current challenges and future perspectives in a changing world Type de document : Monographie Auteurs : António Vieira, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2021 Importance : 152 p. ISBN/ISSN/EAN : 978-1-83962-300-4 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] acquisition d'images [Termes IGN] Algérie [Termes IGN] Bénin [Termes IGN] changement d'occupation du sol [Termes IGN] couvert végétal [Termes IGN] érosion côtière [Termes IGN] état du sol [Termes IGN] Ethiopie [Termes IGN] image captée par drone [Termes IGN] image RVB [Termes IGN] indice de végétation [Termes IGN] Indonésie [Termes IGN] modèle RUSLE [Termes IGN] montagne [Termes IGN] occupation du sol [Termes IGN] orthoimage [Termes IGN] photogrammétrie aérienne [Termes IGN] Pix4D [Termes IGN] protection des sols [Termes IGN] risque naturel [Termes IGN] Rwanda [Termes IGN] système d'information géographique Résumé : (Editeur) Soil erosion is a major environmental issue with a worldwide impact and direct and indirect effects on soil productivity and consequently on human survival. Although a natural process, soil erosion has increased significantly due to human intervention, especially in the last centuries, through diverse activities such as intensive agriculture, overgrazing, urban sprawl, deforestation, and industrial and mining activities. Presently, soil erosion and degradation promoted by human action have reached extreme levels, necessitating urgent measures to promote soil conservation and rehabilitation. This book presents perspectives on soil erosion occurring in different parts of the world as well as some successful initiatives and strategies for soil conservation and rehabilitation. Note de contenu : 1. RGB Spectral Indices for the Analysis of Soil Protection by Vegetation Cover against Erosive Processes / Henry Antonio Pacheco Gil and Argenis de Jesús Montilla Pacheco 2. Spatial Estimation of Soil Erosion Risk Using RUSLE/GIS Techniques and Practices Conservation Suggested for Reducing Soil Erosion in Wadi Mina Catchment (Northwest, Algeria) / Ahmed Benchettouh, Sihem Jebari and Lakhdar Kouri 3. Remote Sensing and GIS-Based Soil Loss Estimation Using RUSLE in Bahir Dar Zuria District, Ethiopia / Nurhussen Ahmed Mohammed and Desale Kidane Asmamaw 4. Determination of the Most Priority Conservation Areas Based on Population Pressure and Erosion Hazard Levels in Lesti Sub-Watershed, Malang Regency, Indonesia / Andi Setyo Pambudi 5. The Impacts of Soil Degradation Effects on Phytodiversity and Vegetation Structure on Atacora Mountain Chain in Benin (West Africa) / Farris Okou, Achille Assogbadjo and Brice Augustin Sinsin 6. Erosion Control Success Stories and Challenges in the Context of Sustainable Landscape Management, Rwanda Experience / Jules Rutebuka 7. Biochar: A Sustainable Approach for Improving Soil Health and Environment / Shreya Das, Samanyita Mohanty, Gayatri Sahu, Mausami Rana and Kiran Pilli Numéro de notice : 26759 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.91595 Date de publication en ligne : 12/05/2021 En ligne : https://doi.org/10.5772/intechopen.91595 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99775

Soil erosion assessment using RUSLE model and its validation by FR probability model / Amiya Gayen in Geocarto international, vol 35 n° 15 ([01/11/2020])  

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Comparative study of different models for soil erosion and sediment yield in Pairi watershed, Chhattisgarh, India / Tarun Kumar in Geocarto international, vol 35 n° 11 ([01/08/2020])  

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Uso de QGIS en la teledetección, Vol. 4. QGIS y sus aplicaciones en agua y en gestion del riego / Nicolas Baghdadi (2020)

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QGIS in Remote Sensing, Volume 4. QGIS and Applications in Water and Risks / Nicolas Baghdadi (2018)  

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Utilisation de QGIS en télédétection, Volume 4. QGIS et applications en eau et risques / Nicolas Baghdadi (2018)

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A GIS-based soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) (Lebna watershed, Cap Bon, Tunisia) / I. Gaubi in Natural Hazards, Vol. 86, n° 1 (Mars 2007)  

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Estimating the rainfall erosivity for management planning in the Eastern Desert, Egypt / Kh. M. Darwish in Geocarto international, Vol 31 n° 9 - 10 (October - November 2016)  

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Integration of remote sensing and GIS for evaluating soil erosion risk in northwestern Zhejiang, China / J. Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 9 (September 2012)  

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A genetic programming approach to estimate vegetation cover in the context of soil erosion assessment / C. Puente in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 4 (April 2011)  

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Evaluation du bilan d'érosion et de dépôt des sols au pré-Rif (Maroc) en utilisant le modèle RUSLE, la télédétection et l'analyse spatiale / A. El Garouani in Revue internationale de géomatique, vol 19 n° 3 (septembre - novembre 2009)  

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