Long-Term Geospatial Monitoring of Quarry Expansion Using Landsat Time Series and LandTrendr: A Case Study of Dargov Hill, Slovakia

Surface mining significantly alters land cover and vegetation, making long-term monitoring essential for assessing its environmental impacts. The objective of this study was to analyze the long-term development of the active Dargov quarry (Slovakia) during the period 2009–2025 using Landsat image time series. Changes in vegetation cover and exposed surfaces were assessed using the NDVI, BSI, and NDBI spectral indices in combination with the Mann–Kendall test, Sen’s slope estimator, and the LandTrendr algorithm. The results revealed a gradual decline in NDVI values accompanied by a concurrent increase in BSI and NDBI values within the active quarry, reflecting the expansion of exposed rock and soil surfaces associated with ongoing mining. Statistically significant trends (p < 0.05) were identified in 76.36% of NDVI pixels, 65.45% of BSI pixels, and 63.64% of NDBI pixels within the deposit boundary. The relationships between spectral indices and quarry production were also evaluated using Pearson’s correlation analysis. The spectral indices showed a substantially stronger relationship with cumulative quarry production than with annual production. The LandTrendr algorithm identified the most pronounced vegetation-cover changes primarily during 2019–2024, with 70.91% of the pixels in the Time of Largest Change output within the deposit boundary falling within this period. The proposed methodology provided a comprehensive assessment of the spatial and temporal patterns of changes associated with surface mining at the Dargov quarry and demonstrated its potential to support environmental monitoring, environmental impact assessment (EIA), and mineral resource management.

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Publication Details

Journal
Geomatics
Published
2026-09-01
DOI
https://doi.org/10.3390/geomatics6050098
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Long-Term Geospatial Monitoring of Quarry Expansion Using Landsat Time Series and LandTrendr: A Case Study of Dargov Hill, Slovakia

Diana Bobíková, Žofia Kuzevičová, Štefan Kuzevič, Michal Roman et al.
Geomatics
Remote Sensing in Agriculture
article

Long-Term Geospatial Monitoring of Quarry Expansion Using Landsat Time Series and LandTrendr: A Case Study of Dargov Hill, Slovakia

Diana Bobíková, Žofia Kuzevičová, Štefan Kuzevič, Michal Roman, Miroslava Stolična Vancova
article en

Abstract

Surface mining significantly alters land cover and vegetation, making long-term monitoring essential for assessing its environmental impacts. The objective of this study was to analyze the long-term development of the active Dargov quarry (Slovakia) during the period 2009–2025 using Landsat image time series. Changes in vegetation cover and exposed surfaces were assessed using the NDVI, BSI, and NDBI spectral indices in combination with the Mann–Kendall test, Sen’s slope estimator, and the LandTrendr algorithm. The results revealed a gradual decline in NDVI values accompanied by a concurrent increase in BSI and NDBI values within the active quarry, reflecting the expansion of exposed rock and soil surfaces associated with ongoing mining. Statistically significant trends (p < 0.05) were identified in 76.36% of NDVI pixels, 65.45% of BSI pixels, and 63.64% of NDBI pixels within the deposit boundary. The relationships between spectral indices and quarry production were also evaluated using Pearson’s correlation analysis. The spectral indices showed a substantially stronger relationship with cumulative quarry production than with annual production. The LandTrendr algorithm identified the most pronounced vegetation-cover changes primarily during 2019–2024, with 70.91% of the pixels in the Time of Largest Change output within the deposit boundary falling within this period. The proposed methodology provided a comprehensive assessment of the spatial and temporal patterns of changes associated with surface mining at the Dargov quarry and demonstrated its potential to support environmental monitoring, environmental impact assessment (EIA), and mineral resource management.

GeomaticsVol. 6(5)
Technical University of Košice (SK)
Openalex Percentile: Top 10%
Remote Sensing in Agriculture
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