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A spatial distribution: Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil / Jiawei Liu in Science of the total environment, vol 859 n° 1 (February 2023)  

Public [article]  inScience of the total environment > vol 859 n° 1 (February 2023) . - n° 160112 Titre : A spatial distribution: Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil Type de document : Article/Communication Auteurs : Jiawei Liu, Auteur ; Hou Kang, Auteur ; Wendong Tao, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 160112 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] analyse en composantes principales [Termes IGN] autocorrélation spatiale [Termes IGN] cartographie des risques [Termes IGN] Chine [Termes IGN] distribution spatiale [Termes IGN] métal lourd [Termes IGN] pollution des sols [Termes IGN] risque de pollution [Termes IGN] traçabilité Résumé : (auteur) With the rapid development of urbanization, heavy metal pollution of soil has received great attention. Over-enrichment of heavy metals in soil may endanger human health. Assessing soil pollution and identifying potential sources of heavy metals are crucial for prevention and control of soil heavy metal pollution. This study introduced a spatial distribution - principal component analysis (SD-PCA) model that couples the spatial attributes of soil pollution with linear data transformation by the eigenvector-based principal component analysis. By evaluating soil pollution in the spatial dimension it identifies the potential sources of heavy metals more easily. In this study, soil contamination by eight heavy metals was investigated in the Lintong District, a typical multi-source urban area in Northwest China. In general, the soils in the study area were lightly contaminated by Cr and Pb. Pearson correlation analysis showed that Cr was negatively correlated with other heavy metals, whereas the spatial autocorrelation analysis revealed that there was strong association in the spatial distribution of eight heavy metals. The aggregation forms were more varied and the correlation between Cr contamination and other heavy metals was lower. The aggregation forms of Mn and Cu, Zn and Pb, on the other hand, were remarkably comparable. Agriculture was the largest pollution source, contributing 65.5 % to soil pollution, which was caused by the superposition of multiple heavy metals. Additionally, traffic and natural pollution sources contributed 17.9 % and 11.1 %, respectively. The ability of this model to track pollution of heavy metals has important practical significance for the assessment and control of multi-source soil pollution. Numéro de notice : A2023-009 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scitotenv.2022.160112 Date de publication en ligne : 11/11/2022 En ligne : https://doi.org/10.1016/j.scitotenv.2022.160112 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102115 [article]

GIS-based land-use suitability analysis for urban agriculture development based on pollution distributions / Fatemeh Kazemi in Land use policy, vol 123 (December 2022)  

Public [article]  inLand use policy > vol 123 (December 2022) . - n° 106426 Titre : GIS-based land-use suitability analysis for urban agriculture development based on pollution distributions Type de document : Article/Communication Auteurs : Fatemeh Kazemi, Auteur ; Nazanin Hosseinpour, Auteur Année de publication : 2022 Article en page(s) : n° 106426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] agriculture [Termes IGN] distribution spatiale [Termes IGN] espace vert [Termes IGN] Iran [Termes IGN] milieu urbain [Termes IGN] paysage urbain [Termes IGN] pollution atmosphérique [Termes IGN] pollution des sols [Termes IGN] processus de hiérarchisation analytique [Termes IGN] utilisation du sol Résumé : (auteur) With recent increases in urban population and development, agricultural lands have been changed to residential areas and industrial settlements. Such urban population growth increases necessitate emerging relatively new strategies and forms in urban parks and landscape designs to meet today's economic, social, and ecological needs toward sustainable development. Urban agriculture is one of the strategies for achieving sustainable development and creating multi-purpose landscapes. Such an approach appears to partially solve the problem of agricultural land reduction and degradation. However, urban pollutants seem to hinder the development of such a sustainable concept in the cities. This research aimed to identify suitable locations for urban agriculture in urban green spaces according to various contamination criteria and the uniform distribution of the green spaces in Mashhad, Iran. In this research, using an Analytical Hierarchy Process (AHP) and a Geographic Information System (GIS) facilitated the decision-making process. It also determined the importance of the land use criteria for urban agricultural development. The results showed that the most suitable areas for urban agricultural development with the least impact of pollutants in Mashhad were the suburbs, especially in the northeast and southeast parts. These research results have practical implications for planning urban agricultural development at the city level across the world. Numéro de notice : A2022-895 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.landusepol.2022.106426 Date de publication en ligne : 03/11/2022 En ligne : https://doi.org/10.1016/j.landusepol.2022.106426 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102244 [article]

Extracting event-related information from a corpus regarding soil industrial pollution / Chuanming Dong (2021)  

Public Titre : Extracting event-related information from a corpus regarding soil industrial pollution Type de document : Article/Communication Auteurs : Chuanming Dong , Auteur ; Philippe Gambette, Auteur ; Catherine Dominguès , Auteur Editeur : Setúbal [Portugal] : Science and Technology Publications - Scitepress Année de publication : 2021 Projets : 1-Pas de projet / Conférence : KDIR 2021, 13th International Conference on Knowledge Discovery and Information Retrieval 25/10/2021 27/10/2021 Setubal Portugal OA Proceedings Importance : pp 217 - 224 Note générale : bibliographie In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR, ISBN 978-989-758-533-3 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] apprentissage profond [Termes IGN] corpus [Termes IGN] découverte de connaissances [Termes IGN] données étiquetées d'entrainement [Termes IGN] pollution des sols [Termes IGN] site pollué [Termes IGN] traitement du langage naturel Résumé : (auteur) We study the extraction and reorganization of event-related information in texts regarding industrial pollution. The object is to build a memory of polluted sites that gathers the information about industrial events from various databases and corpora. An industrial event is described through several features as the event trigger, the industrial activity, the institution, the pollutant, etc. In order to efficiently collect information from a large corpus, it is necessary to automatize the information extraction process. To this end, we manually annotated a part of a corpus about soil industrial pollution, then we used it to train information extraction models with deep learning methods. The models we trained achieve 0.76 F-score on event feature extraction. We intend to improve the models and then use them on other text resources to enrich the polluted sites memory with extracted information about industrial events. Numéro de notice : C2021-068 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5220/0010656700003064 En ligne : https://dx.doi.org/10.5220/0010656700003064 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99540

Spectral Interference of Heavy Metal Contamination on Spectral Signals of Moisture Content for Heavy Metal Contaminated Soils / Haein Shin in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 4 (April 2020) . - pp 2266 - 2275 Titre : Spectral Interference of Heavy Metal Contamination on Spectral Signals of Moisture Content for Heavy Metal Contaminated Soils Type de document : Article/Communication Auteurs : Haein Shin, Auteur ; Jaehyung Yu, Auteur ; Lei Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2266 - 2275 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] arsenic [Termes IGN] bande spectrale [Termes IGN] bruit blanc [Termes IGN] contamination [Termes IGN] cuivre [Termes IGN] dégradation du signal [Termes IGN] échantillonnage [Termes IGN] humidité du sol [Termes IGN] interférence [Termes IGN] métal lourd [Termes IGN] modèle de régression [Termes IGN] plomb [Termes IGN] pollution des sols [Termes IGN] signature spectrale Résumé : (auteur) This article examined the spectral interference by heavy metal on the spectral signal of moisture content of heavy metal contaminated soils. Soil samples were collected from an abandoned mine area, and the chemical analysis revealed extremely high contamination amount of copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), and lead (Pb). The mineralogical analysis showed that the spectral signature of the heavy metal contaminated soils was manifested by secondary minerals. Water content suppressed the spectral reflectance of the soil samples but increased the absorption depths. Although a regression model can predict moisture content using the magnitude of the water absorption feature, the accuracy was much lower when the heavy metal concentration was extremely high. It indicates that geochemical reactions between the heavy metal cation and iron oxide/clay minerals may have affected the spectral responses of the contaminated soils at the water absorption bands. Our model also showed that there was a shift of the absorption features of moisture content if the heavy metal contamination level went up. Unlike normal soils, the absorption features of clay minerals and ferric iron were not able to accurately predict moisture in highly contaminated soils. Given the fact that the spectral bands selected in this article were associated with water absorption, the findings from this article may only be useful to a drone-based low-altitude remote sensing of soil moisture content. Numéro de notice : A2020-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2946297 Date de publication en ligne : 31/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2946297 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94860 [article]

Fusion entre bases de données hétérogènes concernant la pollution des sols [diaporama] / Chuanming Dong (2020)  

Public Titre : Fusion entre bases de données hétérogènes concernant la pollution des sols [diaporama] Type de document : Article/Communication Auteurs : Chuanming Dong , Auteur Editeur : GdR MaDICS Année de publication : 2020 Conférence : Atelier 2020 AGEE du second symposium GdR CNRS MaDICS 06/07/2020 06/07/2020 en ligne France programme Langues : Français (fre) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] acteur [Termes IGN] appariement de données localisées [Termes IGN] base de données localisées [Termes IGN] base de données thématiques [Termes IGN] données spatiotemporelles [Termes IGN] intégration de données [Termes IGN] polluant [Termes IGN] pollution des sols Numéro de notice : C2020-026 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://hal.archives-ouvertes.fr/hal-03198895/file/AGEE - Fusion entre bases de  [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97635

A machine learning approach to detect crude oil contamination in a real scenario using hyperspectral remote sensing / Ran Pelta in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)  

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Hyperspectral analysis of soil polluted with four types of hydrocarbons / Laura A. Reséndez-Hernández in Geocarto international, vol 34 n° 9 ([15/06/2019])  

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Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons / Guillaume Lassalle (2019)  

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Vers un observatoire agro-environnemental des territoires : Un système décisionnel multi-échelle pour le bassin de la Charente / Françoise Vernier in Revue internationale de géomatique, vol 27 n° 3 (juillet-septembre 2017)  

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Exceedance of critical loads and of critical limits impacts tree nutrition across Europe / Peter Waldner in Annals of Forest Science, vol 72 n° 7 (October 2015)  

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Sols et environnement, chiffres clés, édition 2015 / CGDD Commissariat Général au Développement Durable (2015)  

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BASIAS, inventaire et analyse de sites industriels des Bouches-du-Rhône / Jonathan Moreau (2012)

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Suivi actualisé d'indicateurs agricoles parcellaires sur des zones de protection de captages d'eau potable / V. Dardare in Géomatique expert, n° 76 (01/09/2010)

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L'environnement en France, édition 2010, 1. Rapport / CGDD Commissariat Général au Développement Durable (2010)

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L'environnement en France, édition 2010, 2. Synthèse / Bruno Trégouët (2010) 

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