Assessing Long-Term Land-Cover Dynamics Along the Presnogorkovskaya–Zhanaesil Railway Corridor (1985–2024), Kazakhstan: A Landsat NDVI Buffer-Gradient Approach for Sustainable Rail Infrastructure

Balgyn Ashimova, Raikhan Beisenova and Ignacio Menéndez-Pidal ()
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Balgyn Ashimova: Environmental Management and Engineering Department, Faculty of Natural Sciences, L.N. Gumilyov Eurasian National University, Astana 010000, Kazakhstan
Raikhan Beisenova: Environmental Management and Engineering Department, Faculty of Natural Sciences, L.N. Gumilyov Eurasian National University, Astana 010000, Kazakhstan
Ignacio Menéndez-Pidal: Laboratorio de Geología, Departamento de Ingeniería y Morfología del Terreno, School of Civil Engineering, Technical University of Madrid, 28040 Madrid, Spain

Sustainability, 2025, vol. 17, issue 20, 1-21

Abstract: The development of railway infrastructure is considered a key driver of vegetation cover transformation, particularly in ecologically sensitive regions. This study aims to quantify the spatio-temporal impact of the Presnogorkovskaya–Zhanaesil railway corridor in Northern Kazakhstan over the period 1985–2024. Using Landsat imagery and a gradient method of comparative analysis with a control area, an innovative coefficient B was developed to assess changes across various vegetation categories. Multiple linear regression was used to determine the influence of natural factors, including precipitation, temperature, and elevation. The results indicate that while some categories (e.g., dense vegetation or wet areas) show consistent degradation near the railway, the observed patterns are also modulated by environmental gradients. Compared to the control area, buffer zones along the railway exhibit an increased presence of degraded land types (≈309 km 2 vs. ≈72 km 2 in the control) and a reduction in productive vegetation cover (over 100 km 2 loss), especially in recent years. The study concludes that the proposed method allows for a differentiated understanding of anthropogenic and natural drivers of vegetation change, offering a replicable approach for assessing the impact of linear infrastructure in other geographical contexts.

Keywords: railway infrastructure; remote sensing; buffer zones; land cover; anthropogenic impact (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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