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High-Resolution UAV-Based NDVI Monitoring Method for Sustainable Post-Mining Land Management

Sustainability · 6 May 2026 · 10.3390/su18094583

Abstract

The transition of coal regions under the European Green Deal and Just Transition Fund creates a need for quantitative, transparent monitoring of ecological recovery on post-mining land. This study presents an autonomous UAV-based methodology for high-resolution monitoring of vegetation dynamics on a reclaimed coal waste heap in Upper Silesia, Poland. A DJI Mavic 3 Multispectral platform with RTK positioning conducted approximately biweekly flights from August 2024 to October 2025 over three study plots acquiring RGB and multispectral imagery at approximately 4 cm/pixel. Photogrammetric processing in DJI Terra produced radiometrically corrected orthomosaics and NDVI maps, which were analyzed using an automated QGIS workflow for reprojection, clipping, NDVI-based classification, and quantification of vegetation area across three different reclamation variants. The results indicate that intensive soil conditioning through the application of compost derived from bio-waste achieved a maximum vegetation cover of 94.4%. This treatment consistently maintained the highest level of cover during periods of environmental stress and significantly surpassed both seeding-only treatments and those combining seeding with irrigation. Baseline vegetation cover below 6% confirmed the necessity of active reclamation. This workflow provides rapid and reproducible metrics that are suitable for adaptive management and regulatory reporting. It also offers a scalable template for monitoring coal waste heaps across Europe undergoing SDG-aligned reclamation.

Plant phenotyping relevance

UAVマルチスペクトル画像と自動QGISワークフローにより、植生被覆を plot レベルで定量化する再現可能な計測手法が研究の中心であるため、植物状態の画像ベース表現型計測として採用。

abstractThis study presents an autonomous UAV-based methodology for high-resolution monitoring of vegetation dynamics on a reclaimed coal waste heap
abstractan automated QGIS workflow for reprojection, clipping, NDVI-based classification, and quantification of vegetation area
abstractThis workflow provides rapid and reproducible metrics

Code and data availability

The paper describes UAV multispectral imagery, NDVI maps, and an automated QGIS workflow, but no public repository, dataset deposit, or author-provided URL for the imagery, phenotype measurements, or workflow is given. Supplementary Materials are referenced (equipment photos, screenshots) but no access URL appears in a

No evidence-backed public reproduction asset is currently recorded.

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