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Integrated environmental impact assessment of the Sasa tailing dam failure using remote sensing techniques

Adjiski Vancho, Zubíček Václav

Archives of Mining Sciences

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2025

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Vol. 70, no. 3

525--556

EN

Failures of tailings dams represent a critical environmental hazard, releasing mining by-products that cause long-term damage to nearby ecosystems. This research presents a detailed analysis using remote sensing techniques of the 2003 Sasa tailing dam disaster in North Macedonia. By utilising Landsat 5 imagery and Google Earth Engine (GEE), multiple spectral indices — including the Normalised Difference Vegetation Index (NDVI), Normalised Difference Moisture Index (NDMI), Normalised Difference Water Index (NDWI), Modified NDWI (MNDWI), and a turbidity proxy — were integrated to examine the immediate and spatial impacts on vegetation health, soil moisture, water presence, and sediment levels. The findings indicated significant ecological fluctuations along the river path, including vegetation stress, changes in soil moisture, water pooling, and turbidity. These effects displayed spatial gradients, diminishing further from the contamination pathway and forming distinct zones of influence. Certain intermediate areas showed anomalous disturbances, where sediment and hydrological changes impeded vegetation recovery. Pixel-level, buffer-based, and zone-based analyses - combined with Z-scores and correlation studies — revealed a complex post-disaster landscape. Weak correlation with topographic features suggested that localised conditions, rather than large-scale gradients, governed short-term ecological recovery. The study provides a framework for integrated, multi-index and multiscale environmental impact assessment, contributing to improved remediation strategies, disaster response planning, and sustainable management of post-mining landscapes.

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GIS- and AHP-based Decision Systems for Evaluating Optimal Locations of Photovoltaic Power Plants: Case Study of Republic of North Macedonia

Adjiski Vancho, Serafimovski Dalibor

Geomatics and Environmental Engineering

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2024

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Vol. 18, no. 1

51--82

EN

This study employs a geographic information system (GIS) and an analytical hierarchy process (AHP) to identify optimal locations for photovoltaic (PV) solar farms in the Republic of North Macedonia. It assesses land suitability using six criteria (solar irradiance, aspect, slope, distance from power lines, roads, and urban areas) and six constraints (urban settlements, agricultural zones, national parks, water bodies, steep slopes, elevations above 1500 m). A suitability map was created using a matrix of pairwise comparisons, and the weights for each criterion were calculated. The map was divided into four categories: highly suitable, suitable, less suitable, and unsuitable. The results showed that 11.6% of the study area was classified as being highly suitable, 40.1% as suitable, 3.6% as less suitable, and 0.8% as unsuitable. Additionally, restricted areas (comprised of national parks, residential and agricultural lands, elevations above 1500 m, and water surfaces with 1000 m buffer zones) accounted for 43.7% of the study area. Utilizing just 0.6% of highly suitable land for PV technology could generate approximately 2870 GWh annually, enough to meet the average electricity needs of the industrial sector across the eight administrative regions of R. N. Macedonia. The study offers a replicable GIS-based approach for solar energy planning, contributing to sustainable development and providing insights for integrating solar PV systems into the national energy strategy.

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Methodology for underground mining method selection

Mijalkovski Stojance, Peltechki Dragi, Despodov Zoran, Mirakovski Dejan, Adjiski Vancho, Doneva Nikolinka

Mining Science

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2021

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Vol. 28

201--216

EN

The mining method selection for underground mining is one of the most important decisions when designing a mine. This selection depends on the mining-geological, mining-technical and economic factors. The mining method selection for underground mining can be described as a multi-criteria decision-making process, as several factors are involved in the selection process. In this paper, a methodology for rational and optimal mining method selection for underground mining of metallic mineral resources has been developed. First, a rational selection of the four best-ranked mining methods for underground mining is performed using numerical methods (Nicholas' approach and the modified approach of Nicholas, i.e., UBC selection of mining method). This is followed by the optimal selection of underground mining method using multi-criteria decision-making methods (ELECTRE, PROMETHEE, AHP, and integrated AHP-PROMETHEE) and by comparing the obtained rankings, the optimal mining method is selected.