Influence of climatic conditions on Normalized Difference Vegetation Index variability in forest in Poland (2002–2021)

Kulesza, Kinga; Hościło, Agata

doi:10.1002/met.2156

Cited by 5 publications

(6 citation statements)

References 62 publications

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“…This finding resonates with the wider body of research that underscores the importance of meteorological elements in vegetative trends [66]. For instance, Kulesza and Hościło [67] have concluded that rainfall is the most significant natural factor influencing forest health across Poland. Moreover, Pravalie et al [68] found that in mountain regions such as the Carpathians, the greening trend is more closely associated with temperature increases, while in our study area, precipitation has a more pronounced effect.…”

Section: Driving Factors Of Vegetation Change In High and Low-intensi...supporting

confidence: 58%

The Spatio-Temporal Variation of Vegetation and Its Driving Factors during the Recent 20 Years in Beijing

Chen,

Ji,

et al. 2024

Remote Sensing

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As the most important city in China, Beijing has experienced an economic soar, large-scale population growth and eco-environment changes in the last 20 years. Evaluating climate- and human-induced vegetation changes could reveal the relationship of vegetation-climate-human activities and provide important insights for the coordination of economic growth and environmental protection. Based on a long-term MODIS vegetation index dataset, meteorological data (temperature, precipitation) and impervious surface data, the Theil-Sen regression and the Mann-Kendall method are used to estimate vegetation change trends in this study and the residual analysis is utilized to distinguish the impacts of climate factors and human activities on vegetation restoration and degradation from 2000 to 2019 in Beijing. Our results show that the increasing vegetation areas account for 80.2% of Beijing. The restoration of vegetation is concentrated in the urban core area and mountainous area, while the degradation of vegetation is mainly concentrated in the suburbs. In recent years, the vegetation in most mountainous areas has changed from restoration to significant restoration, indicating that the growth of mountain vegetation has continued to restore. We also found that in the process of urban expansion, vegetation browning occurred in 53.1% of the urban built-up area, while vegetation greening occurred in the remaining area. We concluded that precipitation is the main climatic factor affecting the growth of vegetation in Beijing’s mountainous areas through correlation analysis. Human activities have significantly promoted the vegetation growth in the northern mountainous area thanks to the establishment of environmental protection areas. The negative correlation between vegetation and the impervious surface tends to gradually expand outwards, which is consistent with the trend of urban expansion. The positive correlation region remains stable, but the positive correlation is gradually enhanced. The response of vegetation to urbanization demonstrated a high degree of spatial heterogeneity. These findings indicated that human activities played an increasingly important role in influencing vegetation changes in Beijing.

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Section: Driving Factors Of Vegetation Change In High and Low-intensi...supporting

confidence: 58%

The Spatio-Temporal Variation of Vegetation and Its Driving Factors during the Recent 20 Years in Beijing

Chen,

Ji,

et al. 2024

Remote Sensing

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“…In the last two decades a slightly positive trend in condition of the forests in Poland was noticed, with a mean NDVI increase of 0.088×10 -3 per year (2002-2021) (Kulesza and Hościło, 2023). The biggest increase of mean annual NDVI (by 0.030 in 20 years) was observed in central-eastern Poland, while it was weaker in southern, western and northern edges of the study area.…”

Section: Basic Characteristics Of VI and Meteorological Elementsmentioning

confidence: 81%

“…The trend of mean annual T was positive over the entire research area, resulting in the increase in T by 1 to 1.6°C (in southern and eastern regions) (2002-2021) (Kulesza and Hościło, 2023). In central and eastern regions the statistically significant increase in ETo was also reported, with a mean increase of 1.79 mm per year (while mean annual ETo is ca.…”

Section: Basic Characteristics Of VI and Meteorological Elementsmentioning

confidence: 84%

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Coherency and time lag analyses between MODIS vegetation indices and climate across forest and grasslands in European temperate zone

Kulesza,

Hościło

2023

Preprint

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Abstract. Identifying the climate-induced variability in the condition of vegetation is particularly important in the context of the recent climate change, and plants’ impact on mitigation of the climate change. In this paper, we present the coherence and time lags in the spectral response of three individual vegetation types in European temperate zone to the influencing meteorological factors, in the period 2002–2022. Vegetation condition in broadleaved forest, coniferous forest and pastures was measured with monthly anomalies of two spectral indices – NDVI and EVI. As meteorological elements we used monthly anomalies of temperature (T), precipitation (P), vapour pressure deficit (VPD), evapotranspiration (ETo), and teleconnection indices North Atlantic Oscillation (NAO) and North Sea Caspian Pattern (NCP). Periodicity in the time series was assessed using the Wavelet Transform, but no significant intra- or interannual cycles were detected in both vegetation (NDVI and EVI) and meteorological variables. In turn, coherence between NDVI/EVI and meteorological elements was described using the methods of Wavelet Coherence and Pearson’s linear correlation with time lag. In European temperate zone analysed in this study, NAO produces strong coherence mostly for forests, with circa 1 year delay and – a weaker coherence – with circa 3 year delay. For pastures these interannual patterns are hardly recognizable. The strongest relationships occur between condition of the vegetation and T and ETo – they show high coherence in both forests and pastures. There is a significant cohesion with 8–16 month (ca. 1 year) delay and 20–32 month (ca. 2 year) delay. More time lagged significant correlations between vegetation indices and T occur for forests than for pastures, suggesting a significant lag in the forests’ response to the changes in T.

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“…Several trend studies did not include a precise description of the effects at the forest level (phenological changes, mortality, or productivity changes). However, these studies commonly described changes in vegetation indices and associated changes in vegetation as a result of changing climatic conditions [101,109,110,[206][207][208][209][210][211][212][213][214].…”

Section: Trend Changementioning

confidence: 99%

Potential of Earth Observation to Assess the Impact of Climate Change and Extreme Weather Events in Temperate Forests—A Review

Wegler,

Kuenzer

2024

Remote Sensing

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Temperate forests are particularly exposed to climate change and the associated increase in weather extremes. Droughts, storms, late frosts, floods, heavy snowfalls, or changing climatic conditions such as rising temperatures or more erratic precipitation are having an increasing impact on forests. There is an urgent need to better assess the impacts of climate change and extreme weather events (EWEs) on temperate forests. Remote sensing can be used to map forests at multiple spatial, temporal, and spectral resolutions at low cost. Different approaches to forest change assessment offer promising methods for a broad analysis of the impacts of climate change and EWEs. In this review, we examine the potential of Earth observation for assessing the impacts of climate change and EWEs in temperate forests by reviewing 126 scientific papers published between 1 January 2014 and 31 January 2024. This study provides a comprehensive overview of the sensors utilized, the spatial and temporal resolution of the studies, their spatial distribution, and their thematic focus on the various abiotic drivers and the resulting forest responses. The analysis indicates that multispectral, non-high-resolution timeseries were employed most frequently. A predominant proportion of the studies examine the impact of droughts. In all instances of EWEs, dieback is the most prevailing response, whereas in studies on changing trends, phenology shifts account for the largest share of forest response categories. The detailed analysis of in-depth forest differentiation implies that area-wide studies have so far barely distinguished the effects of different abiotic drivers at the species level.

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Influence of climatic conditions on Normalized Difference Vegetation Index variability in forest in Poland (2002–2021)

Cited by 5 publications

References 62 publications

The Spatio-Temporal Variation of Vegetation and Its Driving Factors during the Recent 20 Years in Beijing

The Spatio-Temporal Variation of Vegetation and Its Driving Factors during the Recent 20 Years in Beijing

Coherency and time lag analyses between MODIS vegetation indices and climate across forest and grasslands in European temperate zone

Potential of Earth Observation to Assess the Impact of Climate Change and Extreme Weather Events in Temperate Forests—A Review

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