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Integrating Land Use Change and Vegetation Resilience to Assess Ecological Impacts of Expressway Construction: A Case Study of the Linghua Expressway

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The rapid expansion of road construction has significantly contributed to economic development and regional connectivity. However, linear infrastructure such as roads, railways, and utility corridors has also introduced considerable ecological disruptions. Although increasing global attention is being paid to mitigating these effects, most existing research primarily focuses on quantifying and monitoring external environmental changes (e.g., landscape structure or vegetation coverage) while often neglecting internal ecological dynamics such as ecosystem resilience. Previous road-ecology studies have extensively examined road-buffer effects, land-use/land-cover changes, vegetation-index dynamics, and landscape fragmentation. Therefore, the contribution of this study does not lie in proposing an entirely new class of indicators. Rather, it lies in applying a combined external–internal assessment framework to a recently constructed expressway corridor by jointly examining annual land-cover transitions and leaf area index (LAI)-derived temporal variability/resilience indicators across multiple distance buffers and spatial resolutions. This design allows us to compare whether structural land-cover changes and vegetation time-series responses show similar distance–decay patterns around the expressway corridor. The results show that: (1) Land-cover transformation was mainly concentrated within the first 500–1000 m from the expressway, especially for impervious surface expansion and vegetation loss. Multi-indicator distance-gradient analysis showed that land-cover change intensity and LAI-derived variability indicators gradually approached the distal reference condition at approximately 2000 m, which was therefore used as an empirical corridor-analysis boundary rather than a definitive ecological impact threshold. (2) Within the 2000 m buffer zone, forest area increased from 21.866 km2 in 2001 to 45.370 km2 in 2023, while impervious surface area increased from 3.016 km2 to 6.869 km2. During the construction and early operation period from 2018 to 2023, impervious surface area increased from 6.268 km2 to 6.869 km2, indicating localized artificial surface expansion along the expressway corridor. (3) During 2018–2023, the 30 m LAI product showed a 22.3% increase in coefficient of variation (CV), indicating enhanced relative LAI variability. In contrast, temporal autocorrelation (TAC) did not show the consistent increase expected under classical critical slowing down theory, suggesting that TAC-based evidence for resilience decline was weak or inconclusive during this short period. The observed TAC/CV changes were interpreted as critical slowing down (CSD)-related vegetation variability signals, rather than as a distinct or definitive critical slowing down signature. (4) The multi-resolution comparison showed weak pixel-level correspondence between the 30 m and 250 m LAI products, indicating clear scale dependence rather than robust multi-scale consistency. The 250 m data were useful for characterizing long-term regional background trends, whereas the 30 m data were more suitable for detecting localized corridor-scale vegetation variability. Thus, the multi-resolution analysis should be regarded as a scale-sensitivity assessment rather than as direct cross-scale validation.
Title: Integrating Land Use Change and Vegetation Resilience to Assess Ecological Impacts of Expressway Construction: A Case Study of the Linghua Expressway
Description:
The rapid expansion of road construction has significantly contributed to economic development and regional connectivity.
However, linear infrastructure such as roads, railways, and utility corridors has also introduced considerable ecological disruptions.
Although increasing global attention is being paid to mitigating these effects, most existing research primarily focuses on quantifying and monitoring external environmental changes (e.
g.
, landscape structure or vegetation coverage) while often neglecting internal ecological dynamics such as ecosystem resilience.
Previous road-ecology studies have extensively examined road-buffer effects, land-use/land-cover changes, vegetation-index dynamics, and landscape fragmentation.
Therefore, the contribution of this study does not lie in proposing an entirely new class of indicators.
Rather, it lies in applying a combined external–internal assessment framework to a recently constructed expressway corridor by jointly examining annual land-cover transitions and leaf area index (LAI)-derived temporal variability/resilience indicators across multiple distance buffers and spatial resolutions.
This design allows us to compare whether structural land-cover changes and vegetation time-series responses show similar distance–decay patterns around the expressway corridor.
The results show that: (1) Land-cover transformation was mainly concentrated within the first 500–1000 m from the expressway, especially for impervious surface expansion and vegetation loss.
Multi-indicator distance-gradient analysis showed that land-cover change intensity and LAI-derived variability indicators gradually approached the distal reference condition at approximately 2000 m, which was therefore used as an empirical corridor-analysis boundary rather than a definitive ecological impact threshold.
(2) Within the 2000 m buffer zone, forest area increased from 21.
866 km2 in 2001 to 45.
370 km2 in 2023, while impervious surface area increased from 3.
016 km2 to 6.
869 km2.
During the construction and early operation period from 2018 to 2023, impervious surface area increased from 6.
268 km2 to 6.
869 km2, indicating localized artificial surface expansion along the expressway corridor.
(3) During 2018–2023, the 30 m LAI product showed a 22.
3% increase in coefficient of variation (CV), indicating enhanced relative LAI variability.
In contrast, temporal autocorrelation (TAC) did not show the consistent increase expected under classical critical slowing down theory, suggesting that TAC-based evidence for resilience decline was weak or inconclusive during this short period.
The observed TAC/CV changes were interpreted as critical slowing down (CSD)-related vegetation variability signals, rather than as a distinct or definitive critical slowing down signature.
(4) The multi-resolution comparison showed weak pixel-level correspondence between the 30 m and 250 m LAI products, indicating clear scale dependence rather than robust multi-scale consistency.
The 250 m data were useful for characterizing long-term regional background trends, whereas the 30 m data were more suitable for detecting localized corridor-scale vegetation variability.
Thus, the multi-resolution analysis should be regarded as a scale-sensitivity assessment rather than as direct cross-scale validation.

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