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Risk assessment and prediction of forest health for effective geo-environmental planning and monitoring of mining affected forest area in hilltop region / Narayan Kayet in Geocarto international, vol 37 n° 11 ([15/06/2022])  

Public [article]  inGeocarto international > vol 37 n° 11 [15/06/2022] . - pp 3091 - 3115 Titre : Risk assessment and prediction of forest health for effective geo-environmental planning and monitoring of mining affected forest area in hilltop region Type de document : Article/Communication Auteurs : Narayan Kayet, Auteur ; Khanindra Pathak, Auteur ; Abhisek Chakrabarty, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 3091 - 3115 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse de sensibilité [Termes IGN] analyse multicritère [Termes IGN] impact sur l'environnement [Termes IGN] mine [Termes IGN] prévention des risques [Termes IGN] processus de hiérarchisation analytique [Termes IGN] santé des forêts Résumé : (auteur) This paper focuses on forest health risk (FHR) assessment and prediction in the mining-affected forest region using AHP model based on multi-criteria analysis in a GIS platform. We considered a total twenty-eight (twenty two present and six predicted) causative parameters including climate, natural or geomorphological, forestry, topographical, environmental, and anthropogenic. The assessment results of FHR show that of the total existing forest area, 2.85% area under very high, 13.63% high, 31.98% moderate, 32.68% low, and 18.87% are under very low categories. According to the assessment and prediction FHR results, the very high-risk classes were found at mines surrounding forest compartments. The sensitivity analysis showed that some factors were more sensitive to FHR. The correlation results showed a negative relationship between FHR and distance from mines and foliar dust concentration. This work will provide a basic guideline for effective planning and management in forestry studies for the mining-affected region. Numéro de notice : A2022-585 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1849413 Date de publication en ligne : 08/12/2020 En ligne : https://doi.org/10.1080/10106049.2020.1849413 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101358 [article]