Elevation-Dependent NDVI Dynamics in Arevik National Park (Syunik Province, Armenia): a 40-Year Spatio-Temporal Analysis (1985-2025)Abstract
Mountain ecosystems are highly sensitive to climate change due to pronounced environmental gradients and strong climatic variability. Understanding vegetation responses to ongoing warming is therefore essential for assessing ecosystem resilience and developing effective conservation strategies. This study investigates long-term vegetation dynamics and their relationship with climatic warming in Arevik National Park, located in the Syunik Province of southern Armenia. The analysis was conducted using Normalized Difference Vegetation Index (NDVI) data derived from Landsat 5 TM, 7 ETM+, 8 OLI, and 9 OLI-2 imagery for the period 1985-2025 at five-year intervals. Elevation data derived from a Digital Elevation Model (DEM) and August minimum and maximum temperature data obtained from the WorldClim database were integrated within a GIS environment to evaluate elevation-dependent vegetation responses. August was selected because it represents the driest period in the study area, minimizing the influence of seasonal precipitation variability and providing more reliable NDVI-based assessments of forest vegetation dynamics. The results revealed a clear warming trend across the study area, with both minimum and maximum August temperatures showing a gradual increase during the study period. NDVI analysis indicated an overall decline in vegetation greenness and productivity, although significant spatial heterogeneity was observed. Elevation-based analysis demonstrated contrasting vegetation responses along the altitudinal gradient. Negative NDVI trends were identified in elevation zones between 450 and 2400 m a.s.l., where vegetation greenness declined by up to 16.05%. In contrast, positive NDVI trends were recorded above 2400 m a.s.l., with the strongest increase (+25.77%) observed in the 2800-3200 m elevation range. Spatial change-detection analysis further confirmed the coexistence of areas exhibiting vegetation decline and vegetation expansion throughout the study area. The findings indicate that vegetation dynamics in Arevik National Park are strongly elevation-dependent and suggest that ongoing climatic warming affects mountain ecosystems differently across altitude zones. The integration of remote sensing, GIS analysis, and climatic datasets provides valuable insights into climate-vegetation relationships in the South Caucasus and supports evidence-based conservation and management of protected mountain landscapes under changing climatic conditions.
Keywords:
Climatic warming; Mountain ecosystems; Remote sensing
Resumo
Os ecossistemas montanhosos são altamente sensíveis às alterações climáticas devido aos acentuados gradientes ambientais e à forte variabilidade climática. Compreender as respostas da vegetação ao aquecimento em curso é, portanto, essencial para avaliar a resiliência dos ecossistemas e desenvolver estratégias eficazes de conservação. Este estudo investiga a dinâmica da vegetação a longo prazo e a sua relação com o aquecimento climático no Parque Nacional Arevik, localizado na província de Syunik, no sul da Arménia. A análise foi realizada utilizando dados do Índice de Vegetação por Diferença Normalizada (NDVI) derivados de imagens Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI e Landsat 9 OLI-2 para o período de 1985 a 2025, com intervalos de cinco anos. Dados de altitude obtidos a partir de um Modelo Digital de Elevação (DEM) e dados de temperatura mínima e máxima de agosto provenientes da base de dados WorldClim foram integrados num ambiente SIG (Sistema de Informação Geográfica) para avaliar as respostas da vegetação dependentes da altitude. Agosto foi selecionado por representar o período mais seco da área de estudo, minimizando a influência da variabilidade sazonal da precipitação e proporcionando avaliações mais fiáveis da dinâmica da vegetação florestal com base no NDVI. Os resultados revelaram uma clara tendência de aquecimento em toda a área de estudo, com aumentos graduais das temperaturas mínimas e máximas de agosto ao longo do período analisado. A análise do NDVI indicou um declínio geral da cobertura verde e da produtividade da vegetação, embora tenha sido observada uma significativa heterogeneidade espacial. A análise baseada na altitude demonstrou respostas contrastantes da vegetação ao longo do gradiente altitudinal. Foram identificadas tendências negativas do NDVI em zonas de altitude compreendidas entre 450 e 2400 m acima do nível do mar, onde a cobertura verde da vegetação diminuiu até 16,05%. Em contraste, foram registadas tendências positivas do NDVI acima dos 2400 m, com o aumento mais expressivo (+25,77%) observado na faixa altitudinal entre 2800 e 3200 m. A análise espacial de deteção de mudanças confirmou ainda a coexistência de áreas com declínio da vegetação e áreas com expansão da vegetação em toda a área de estudo. Os resultados indicam que a dinâmica da vegetação no Parque Nacional Arevik depende fortemente da altitude e sugerem que o aquecimento climático em curso afeta os ecossistemas montanhosos de forma diferenciada entre as várias zonas altitudinais. A integração de técnicas de deteção remota, análise SIG e conjuntos de dados climáticos fornece informações valiosas sobre as relações entre clima e vegetação no Sul do Cáucaso e apoia a conservação e a gestão baseadas em evidências de paisagens montanhosas protegidas sob condições climáticas em mudança.
Palavras-chave:
Aquecimento climático; Ecossistemas montanhosos; Deteção remota
1 Introduction
Climate change is considered one of the most important drivers of contemporary ecosystem dynamics, significantly influencing vegetation distribution, productivity, and long-term ecological stability. Mountain ecosystems are particularly sensitive to climatic changes due to pronounced altitudinal gradients and rapid variations in temperature and moisture conditions (Parmesan 2006; Pepin et al. 2015).
In mountainous regions, vegetation responses to climate change are often non-uniform across different elevation zones. Rising temperatures can lead to an upward shift of vegetation belts, changes in growing seasons, and variations in ecosystem productivity. Therefore, the study of elevation-dependent vegetation dynamics is essential for assessing the impacts of global warming on forest ecosystems (Lenoir et al. 2008; Nakhutsrishvili 2013).
Remote sensing techniques, particularly the Normalized Difference Vegetation Index (NDVI), are widely used for monitoring vegetation conditions and assessing long-term ecological changes. NDVI is a reliable indicator of vegetation greenness and photosynthetic activity, enabling the spatial and temporal assessment of ecosystem dynamics over large areas and extended time periods (Kooistra et al. 2024; Tucker 1979 )․
Previous studies have shown that vegetation changes are closely linked to climatic factors, particularly temperature and precipitation, especially in mountainous regions where climate varies sharply with elevation (Nemani et al. 2003; Körner 2007). However, in the South Caucasus, including Armenia, long-term and spatially detailed studies on elevation-dependent vegetation dynamics remain limited. The South Caucasus, and particularly the southern part of Armenia, is characterized by high landscape and climatic diversity, where the impacts of climate change on forest ecosystems are still not sufficiently studied (Krever et al. 2001; Fick & Hijmans 2017)․ In this context, Arevik National Park represents a valuable natural laboratory due to its wide elevation range and diverse ecological conditions.
Therefore, the aim of this study is to assess long-term changes in forest vegetation across different elevation zones in Arevik National Park and to investigate their relationship with ongoing global warming using NDVI-based remote sensing analysis and GIS methods over the period 1985-2025. Climatic variables derived from the WorldClim database, specifically August minimum and maximum temperature data, were also considered as indicators of seasonal climatic variation, as August corresponds to the period of maximum summer climatic stress and minimal precipitation influence, allowing for more robust comparisons of vegetation dynamics over time.
Remote sensing-based NDVI analysis is widely applied for monitoring vegetation change and evaluating ecosystem responses to environmental and climatic variability (Chang, Chiang & Dai 2023), making it an appropriate approach for investigating long-term vegetation dynamics in mountain ecosystems.
1.1 Study Area
The study area is located in the South Caucasus region of the Republic of Armenia (Figure 1). The research was conducted in a forested section of Arevik National Park, situated in Syunik Province in the southern part of the country (Figure 2). The study area covers approximately 460 km² and is characterized by complex mountainous terrain, diverse ecological conditions, and extensive forest ecosystems.
Owing to its wide elevational range, the area encompasses several climatic and landscape zones. The climatic zones include arid subtropical climate with hot summers and mild winters, subtropical climate with warm summers and relatively mild winters, temperate climate with warm summers and relatively humid mild winters, moderately humid temperate climate throughout all seasons, temperate climate with short cool summers and cold winters, and high-mountain tundra climate (EcoPortal Armenia 2025)․ Correspondingly, the landscape structure comprises submountain semi-desert landscapes (300-500 m above sea level (a.s.l.)), low- and middle-mountain forest shelter belt landscapes (400-1000 m), low- and middle-mountain forest landscapes (800-2300 m), middle-mountain meadow-steppe landscapes (2200-2600 m), high-mountain subalpine landscapes (2400-2800 m), and high-mountain alpine landscapes (2800-3400 m) (Ministry of Nature Protection of the Republic of Armenia 2014)․
This pronounced environmental heterogeneity provides an excellent natural setting for investigating elevation-dependent vegetation dynamics. The wide range of climatic conditions and landscape types enables the assessment of how vegetation activity, represented by NDVI, has changed across different elevation zones over the period 1985-2025 and how these changes are associated with long-term climatic trends, particularly temperature variations under ongoing climate warming.
2 Materials and Methods
The aim of this study is to assess long-term changes in forest vegetation across different elevation zones in Arevik National Park, a protected area recognized for its high biodiversity and the presence of numerous endemic, rare, and threatened plant species characteristic of the South Caucasus region (UNEP-WCMC & IUCN 2025; UNDP 2015). The study also examines the relationship between these vegetation changes and ongoing climate warming using remote sensing data and GIS-based spatial analysis.
The methodological framework integrates remote sensing techniques, GIS-based spatial analysis, comparative cartographic methods, digital elevation model (DEM) analysis, and spatio-temporal assessment of vegetation dynamics. Elevation-based zoning was applied to investigate variations in vegetation activity along the altitudinal gradient and to evaluate the relationship between NDVI dynamics and climatic variables derived from the WorldClim database.
The study utilized NDVI datasets derived from Landsat satellite imagery, including Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2, together with digital elevation data and WorldClim temperature datasets (USGS 2025; WorldClim 2025)․ August minimum and maximum temperature layers were analyzed at five-year intervals to identify long-term climatic trends and their potential influence on vegetation dynamics. August was selected because it is generally the driest month in the study area, when cloud cover and seasonal precipitation effects are minimal, providing the most reliable and comparable NDVI-based assessment of forest vegetation dynamics across different years. Spatial data processing, analysis, and visualization were performed using ArcGIS and Google Earth Pro software.
The Normalized Difference Vegetation Index (NDVI) was used as the primary indicator of vegetation condition and productivity. NDVI is widely applied in remote sensing studies to quantify vegetation greenness and is calculated using the following Equation 1:
NDVI = (NIR − RED) / (NIR + RED) (1)
NDVI is a widely used indicator of photosynthetic activity and vegetation vigor, derived from the contrast between red (RED) and near-infrared (NIR) spectral reflectance, which is strongly influenced by chlorophyll absorption and leaf cellular structure. NDVI values range from −1 to +1, where higher positive values indicate dense and healthy vegetation, while low or negative values correspond to bare soil, water bodies, or non-vegetated/degraded surfaces (Tucker 1979; EOS Data Analytics 2025)․ For Landsat imagery, NDVI was calculated using specific spectral bands: Band 3 (RED) and Band 4 (NIR) for Landsat 5 TM and 7 ETM+, and Band 4 (RED) and Band 5 (NIR) for Landsat 8 OLI and 9 OLI-2 (USGS 2025)․
The Shuttle Radar Topography Mission (SRTM) Version 3 Digital Elevation Model (DEM), provided by the U.S. Geological Survey (USGS) through the EarthExplorer platform, was used to derive elevation characteristics and classify the study area into discrete altitudinal zones for comparative vegetation analysis. The DEM has a spatial resolution of 30 m (1 arc-second) and is freely available for research and educational purposes. The elevation data enabled the assessment of elevation-dependent vegetation responses within the study region (USGS 2025; JAXA 2025; NASA EarthData 2025).
Climatic variables were obtained from the WorldClim database, a high-resolution global climate dataset (WorldClim 2025). In this study, August minimum and maximum temperature layers were extracted and analyzed at five-year intervals to evaluate long-term climatic trends and their potential influence on vegetation dynamics.
3 Results
The spatial analysis of the study area was first conducted using a two-dimensional elevation (relief) map, which illustrates the strong altitudinal variation within Arevik National Park ranging from 451 to 3200 m a.s.l. This representation allowed the identification of major topographic gradients and provided a basis for subsequent zonal classification of the terrain (Figure 3).
To further visualize the complex mountainous structure, a three-dimensional digital terrain model was generated. The 3D representation clearly highlights the pronounced ruggedness of the relief and the spatial distribution of elevation differences across the study area. This approach improves the understanding of topographic heterogeneity and its potential influence on local microclimatic conditions (Figure 4).
Climatic variability is commonly assessed using high-resolution global climate datasets, which provide spatially continuous temperature information suitable for long-term environmental and ecological analyses (WorldClim 2025; Liu et al. 2024; Shen & Liu 2022). The generated temperature maps reveal clear spatial differences in August thermal conditions and a pronounced elevation-dependent pattern across the study area (Figure 5). While localized warming is evident in several elevation zones over the study period, the temporal trend of the area-averaged August temperatures (Figure 6) indicates only a modest increase with minor interannual fluctuations. This apparent difference reflects the spatial heterogeneity of warming, whereby temperature changes vary considerably among elevation zones and therefore are not fully represented by a single mean value for the entire study area.
Elevation-dependent spatial patterns of August mean and maximum temperature across the study area during 1985-2024 at five-year intervals (a-i).
Temporal variation of minimum and maximum mean August temperatures in the study area at five-year intervals (1985-2024).
Figure 7 presents the spatial distribution of NDVI across the study area for August at five-year intervals between 1985 and 2025. The maps reveal pronounced spatial variability in vegetation activity and demonstrate changes in vegetation greenness across different elevation zones over time. Visual comparison indicates a gradual reduction in areas characterized by high NDVI values during the later observation periods, suggesting changes in vegetation condition and productivity. The temporal dynamics of vegetation activity were further examined using the mean NDVI values calculated for each observation year (Figure 8). The graph reveals an overall declining trend in NDVI throughout the study period, despite minor interannual fluctuations. Higher NDVI values were generally recorded during the earlier years, whereas lower values became more frequent in recent decades, indicating a gradual decrease in vegetation greenness and photosynthetic activity across the study area. Despite the observed increase in August temperatures during the study period, mean NDVI exhibited an overall declining trend, indicating that vegetation greenness did not increase in response to warming across the study area.
The observed decline in NDVI corresponds with the increasing temperature trend identified in Figures 5 and 6, suggesting a potential influence of ongoing climatic warming on vegetation dynamics within the study area.
Spatial distribution of August NDVI across the study area during 1985-2025 at five-year intervals.
Long-term changes in maximum August NDVI across the study area during 1985-2025. Author's own elaboration (2026).
The analysis of mean NDVI values across different elevation zones revealed a clear elevation-dependent pattern of vegetation change between 1985 and 2025 (Table 1). Negative NDVI trends were observed in all elevation ranges between 450 and 2400 m a.s.l., where the mean NDVI decreased by 1.48% to 16.05%. The most pronounced decline was recorded in the 1200-1600 m elevation zone (-16.05%), followed by the 800-1200 m (-13.22%) and 1600-2000 m (-11.81%) zones. In contrast, positive NDVI trends were identified at higher elevations above 2400 m a.s.l. The 2400-2800 m zone exhibited a modest increase of 2.43%, while the 2800-3200 m zone showed the strongest positive change (+25.77%). A slight increase was also observed in the highest elevation range (3200-3620 m), where NDVI increased by 0.13%. These results indicate that vegetation dynamics within the study area are strongly controlled by elevation, with lower and middle elevations experiencing a decline in vegetation greenness, whereas higher mountain zones exhibited a tendency toward vegetation expansion and increased productivity.
Elevation-dependent changes in mean NDVI values from 1985 to 2025. Author's own elaboration (2026).
The contrasting NDVI responses observed along the elevation gradient may be associated with the differential effects of climatic warming. Increasing temperatures appear to have exerted greater stress on vegetation at lower and middle elevations, while warmer conditions at higher elevations may have enhanced vegetation growth by extending the growing season and reducing thermal limitations.
To further investigate the spatial dynamics of vegetation change, NDVI change detection maps were generated by comparing NDVI values between 1985 and 2025 (Figure 9). The green areas shown in Figure 10 represent locations where NDVI increased relative to 1985, indicating improved vegetation greenness and photosynthetic activity over the study period. The most pronounced positive changes were concentrated mainly at elevations above approximately 2400 m a.s.l., suggesting enhanced vegetation activity in high-mountain environments under recent climatic warming.
Figure 10 presents the spatial distribution of negative NDVI changes between 1985 and 2025. Areas shown in green indicate locations where NDVI decreased relative to 1985, reflecting a reduction in vegetation greenness and productivity, primarily between approximately 450 and 2400 m a.s.l. The yellow areas represent locations that exhibited relatively high NDVI values in 1985 but showed lower NDVI values by 2025, indicating a decline in vegetation condition during the study period. Overall, the change detection maps demonstrate a clear altitudinal contrast, with increasing NDVI predominantly at higher elevations and decreasing NDVI across lower and middle elevations.
Spatial distribution of negative NDVI changes in the study area between 1985 and 2025 ( a - d).
Overall, the NDVI change maps reveal a heterogeneous pattern of vegetation dynamics. While certain parts of the study area experienced an increase in vegetation activity, other areas showed a decline, demonstrating contrasting responses of ecosystems to environmental and climatic conditions over the period 1985-2025.
4 Discussion
The results of this study reveal long-term changes in climatic conditions and vegetation dynamics within the forest ecosystems of Arevik National Park. The analysis of August temperature data demonstrated a modest warming trend across the study area between 1985 and 2024, with spatially heterogeneous temperature patterns across different elevation zones. The NDVI analysis revealed an overall decline in vegetation greenness during the study period, although the magnitude and direction of change varied considerably across elevations. Lower and middle elevation zones exhibited predominantly negative NDVI trends, whereas higher mountain areas showed localized increases in vegetation greenness and productivity. The temporal dynamics of NDVI indicate that vegetation responses were characterized by both long-term trends and short-term fluctuations. The spatial distribution maps further demonstrate that vegetation changes are strongly elevation-dependent and cannot be adequately represented by a single area-averaged NDVI or temperature value for the entire study area. These findings highlight the heterogeneous response of mountain forest ecosystems to ongoing climatic warming and local environmental conditions.
A particularly important finding is the strong elevation-dependent pattern of vegetation change. Negative NDVI trends dominated the lower and middle elevation zones, whereas positive trends were observed at higher elevations above 2400 m a.s.l. The most substantial decline in vegetation activity occurred between 1200 and 1600 m, while the strongest increase was recorded in the 2800-3200 m elevation range. These contrasting responses suggest that vegetation at different elevations reacts differently to ongoing climatic warming. The decline in NDVI at lower elevations may be associated with increasing temperature stress and reduced moisture availability during the summer period. In contrast, warming conditions at higher elevations may have reduced thermal limitations on plant growth, thereby promoting vegetation expansion and increased productivity. Similar elevation-dependent responses have been reported in mountain regions worldwide, where climate warming often leads to vegetation decline in warmer lowlands and enhanced growth at higher elevations.
The spatial analysis of positive and negative NDVI changes further confirms the heterogeneous nature of vegetation responses within the study area. The coexistence of areas with increasing and decreasing vegetation activity highlights the importance of local topographic and climatic controls. Therefore, vegetation responses to climate change cannot be considered spatially uniform, even within a relatively limited mountainous region.
5 Conclusion and Recommendations
The integrated use of Landsat-derived NDVI, WorldClim climatic data, and GIS-based spatial analyses proved effective for evaluating long-term vegetation dynamics and climate-vegetation relationships in the mountainous ecosystems of Arevik National Park. The applied methodology successfully identified both temporal changes and elevation-dependent patterns in vegetation and thermal conditions over the study period.
The findings indicate that vegetation responses to climatic variability are strongly elevation-dependent. Lower and middle elevation zones exhibited declining vegetation greenness, whereas higher elevations showed localized increases in vegetation productivity, highlighting the heterogeneous nature of ecosystem responses within the study area.
Future monitoring efforts should incorporate multi-temporal satellite observations and climatic datasets to improve the understanding of long-term ecosystem dynamics under changing climatic conditions. Such approaches may contribute to evidence-based conservation planning and sustainable management strategies for protected mountain ecosystems in Armenia.
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Author's own cartographic elaboration by Sargis Sargsyanbased on Google Earth Pro, accessed in 2026.
Author's own cartographic elaboration by Sargis Sargsyan (2026).
Author's own cartographic elaboration by Sargis Sargsyan (2026).
Author's own cartographic elaboration by Sargis Sargsyan based on WorldClim climate data, DEM, and GIS analysis.
Author's own calculations based on WorldClim climate data (2026).
Author's own cartographic elaboration by Sargis Sargsyan based on Landsat satellite imagery and GIS analysis (2026).
Author's own cartographic elaboration by Sargis Sargsyan based on Landsat satellite imagery, DEM data, and GIS analysis (2026).
Author's own cartographic elaboration by Sargis Sargsyan based on Landsat satellite imagery, DEM data, and GIS analysis (2026).