An Integrated Gis, Remote Sensing And Ai-Based Framework For Improving Monitoring Methodology Of Protected Natural Areas

dc.contributor.author	Kamolov Jakhongir Ilkhomovich
dc.date.accessioned	2026-01-29T20:51:47Z
dc.date.issued	2026-01-22
dc.description.abstract	Effective monitoring of protected natural areas is a critical prerequisite for biodiversity conservation, ecosystem sustainability, and evidence-based environmental management [1,2]. However, many existing monitoring systems remain fragmented, episodic, and weakly integrated with modern geospatial and analytical technologies, which limits their ability to detect spatial–temporal changes and emerging ecological risks in a timely manner
dc.format	application/pdf
dc.identifier.uri	https://zienjournals.com/index.php/tjm/article/view/6692
dc.identifier.uri	10.62480/tjms.2025.vol51.6692.pp12-16
dc.identifier.uri	https://asianeducationindex.com/handle/123456789/113160
dc.language.iso	eng
dc.publisher	Zien Journals
dc.relation	https://zienjournals.com/index.php/tjm/article/view/6692/5426
dc.rights	Copyright (c) 2026 Texas Journal of Multidisciplinary Studies
dc.rights	https://creativecommons.org/licenses/by-nc/4.0
dc.source	Texas Journal of Multidisciplinary Studies; Vol. 51 (2025): TJM; 12-16
dc.source	2770-0003
dc.subject	GIS-based monitoring
dc.subject	protected natural areas
dc.title	An Integrated Gis, Remote Sensing And Ai-Based Framework For Improving Monitoring Methodology Of Protected Natural Areas
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	Peer-reviewed Article

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