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

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.

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

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