Spatio-temporal characteristics of Xinjiang grassland NDVI and its response to climate change from 1981 to 2018

陈春波, 李刚勇

doi:10.5846/stxb202201260251

Cited by 5 publications

(9 citation statements)

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“…It is reported that the abundant water and nutrient is the most ideal environmental condition for the occurrence of over compensation (Belsky, 1986; Liang et al., 2015). Because the object of this paper is marsh, in which water and nutrient is abundant, the phenomenon of over compensation may account for the positive correlation of T min with NDVI in marshes of China (X. Shen et al., 2020b).…”

Section: Discussionmentioning

confidence: 99%

“…The growing season of marshes in China is defined from May to September (X. Shen et al, 2020b;Y. J. Wang et al, 2020).…”

Section: Methodsmentioning

confidence: 99%

“…We used the simple linear regression to analyze the temporal trends of growing season NDVI and climate factors in China marshes from 2000 to 2019. The growing season of marshes in China is defined from May to September (X. Shen et al., 2020b; Y. J. Wang et al., 2020). The trends of NDVI (and climate factors) were calculated as follows (X. J. Shen et al., 2019):

θ_{slope} = \frac{(n \times \sum_{i = 1}^{n} i \times {NDVI}_{i}) - (true \sum_{i = 1}^{n} i true \sum_{i = 1}^{n} {NDVI}_{i})}{n \times \sum_{i = 1}^{n} i^{2} - {(\sum_{i = 1}^{n} i)}^{2}}

where n is the number of years analyzed, i.e.…”

Section: Methodsmentioning

confidence: 99%

“…Because the object of this paper is marsh, in which water and nutrient is abundant, the phenomenon of over compensation may account for the positive correlation of T min with NDVI in marshes of China (X. Shen et al, 2020b).…”

Section: Correlations Between Ndvi and Climate Factors In China's Mar...mentioning

confidence: 99%

“…(2019) noted that the growing season fractional vegetation coverage of freshwater marsh had a positive correlation with growing season temperature in Northeast China; Y. J. Wang et al. (2020) found that increased precipitation was beneficial to the marsh vegetation growth in the Songnen Plain; In the Tibet Plateau, some studies found that the growth of marsh vegetation was mainly affected by temperature, and the increase of temperature could obviously promote marsh vegetation growth (X. Shen et al., 2020b). In the temperate region of China, the increase of temperatures was reported to stimulate the growth of mangrove swamp vegetation, but inhibit the growth of salt marsh (Cavanaugh et al., 2014; Gabler et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Change of Marsh Vegetation and Its Response to Climate Change in China From 2000 to 2019

et al. 2021

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China has the third largest area of marshes in the world. Understanding the change of marsh, vegetation and its response to climate change in China is important for the protection of wetland ecosystem. Based on the climate and normalized difference vegetation index (NDVI) data, we investigated the spatiotemporal variation in vegetation and its response to climate change for different types of marshes in China. The results indicated that growing season NDVI increased significantly (0.02/decade, P < 0.01) over the whole marshes of China from 2000 to 2019. The increased precipitation and minimum temperature during the growing season could promote the growth of marsh vegetation over China. This study found for the first time that the increase of temperature during the day and at night had asymmetric effects on vegetation growth in marshes of China, and the positive effect of night warming was more significant. Spatially, increasing growing season precipitation was beneficial to the vegetation growth of herbaceous marshes, marsh meadows, inland salt marshes, and seasonal saltwater marshes in eastern Inner Mongolia. Increased growing season minimum temperature could greatly promote the vegetation growth of marsh meadows, herbaceous marshes, inland salt marshes, forest swamp, and bush swamp in cold and high‐altitude regions of Northern Northeast China and the Tibet Plateau. In the context of global climate change, more attention should be paid to the different responses of vegetation to climate change for different marsh types, especially when we use the model to simulate the impact of climate change on vegetation in different marsh regions of China.

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Section: Discussionmentioning

confidence: 99%

“…The growing season of marshes in China is defined from May to September (X. Shen et al, 2020b;Y. J. Wang et al, 2020).…”

Section: Methodsmentioning

confidence: 99%

θ_{slope} = \frac{(n \times \sum_{i = 1}^{n} i \times {NDVI}_{i}) - (true \sum_{i = 1}^{n} i true \sum_{i = 1}^{n} {NDVI}_{i})}{n \times \sum_{i = 1}^{n} i^{2} - {(\sum_{i = 1}^{n} i)}^{2}}

where n is the number of years analyzed, i.e.…”

Section: Methodsmentioning

confidence: 99%

Section: Correlations Between Ndvi and Climate Factors In China's Mar...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Change of Marsh Vegetation and Its Response to Climate Change in China From 2000 to 2019

et al. 2021

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Diagnosis and Evolution Characteristics of Critical Water Security Problems in the Source Region of the Yellow River

Gao,

Liu,

Luan

et al. 2023

Pol. J. Environ. Stud.

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The source region of the Yellow River (SRYR) is continuously affected by climate change and human activities, and water security problems have long existed and are constantly changing, with the possibility of inducing a series of new risks. To diagnose the above problems and clarify their evolution features, based on the connotation of water security and its involved dimensions, this paper systematically reviews the relevant research results on water security in the SRYR, summarizes the water security problems and their evolution trend in the region from three aspects: water disasters, water ecology, and water supply security, and deeply analyzes the cascade effect of each water security problem. This paper provides a scientific basis for carrying out water disaster prevention and ecological restoration in the SRYR, which is conducive to optimizing the development and utilization of water resources in the context of adapting to climate change.

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Analysis of spatial and temporal variations of NDVI and its driving factors in the corridor of Lan-Xin railway

Chen,

Yan,

et al. 2024

Front. Environ. Sci.

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Introduction: Vegetation is the main factor of ecological stability, but the construction of largescale corridor projects will bring some damage to vegetation.Methods: Based on the NDVI, temperature and precipitation data of the growing season from 1990–2021 (June to September), this paper uses the maximum synthesis method, trend analysis method, correlation analysis method and coefficient of variation method to study the spatial-temporal changes and driving factors of NDVI in the past 32 years, taking the 30 km belt buffer zone along the Lan-Xin Railway as the research area. The influence range of railway construction on NDVI in different climatic conditions is analyzed.Results: The results showed that: (1) From 1990–2021, the average annual temperature of the growing season in the study area showed an increasing trend, the average annual precipitation showed a decreasing trend, and the average annual NDVI showed an increasing trend; NDVI was positively correlated with temperature in 54.04%, and positively correlated with precipitation in 62.88%. Precipitation had a greater effect on NDVI than temperature. (2) Under the same climatic conditions, the NDVI variability coefficient in the study area fluctuates significantly within 3,000–21,000 m along the railway line, stabilizing beyond 21,000 m; the impact range of railway construction on NDVI gradually increases with increasing precipitation within the same temperature range, and increases gradually with rising temperatures within the same precipitation range. (3) During the growing season (June to September) in the study area, when the temperature is below 25°C, NDVI increases initially with increasing precipitation before decreasing, showing an overall upward trend; when the temperature is above 25°C, NDVI initially increases with increasing precipitation before decreasing. High temperature and high precipitation will inhibit vegetation growth and reduce NDVI. The NDVI of the core area before the railway construction is larger than that of the background area, while the NDVI of the core area after the railway construction is smaller than that of the background area.Discussion: In short, the construction of Lan-Xin Railway has a certain influence on NDVI along the line. When studying the impact of large-scale engineering projects on vegetation in the future, higher resolution imagery can be used along with the incorporation of human activities' influence. These factors will enable more accurate and comprehensive research.

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Spatio-temporal characteristics of Xinjiang grassland NDVI and its response to climate change from 1981 to 2018

Cited by 5 publications

References 0 publications

Spatiotemporal Change of Marsh Vegetation and Its Response to Climate Change in China From 2000 to 2019

Spatiotemporal Change of Marsh Vegetation and Its Response to Climate Change in China From 2000 to 2019

Diagnosis and Evolution Characteristics of Critical Water Security Problems in the Source Region of the Yellow River

Analysis of spatial and temporal variations of NDVI and its driving factors in the corridor of Lan-Xin railway

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