Authors: Xu, Yong
Title: Study of vegetation cover change and its driving forces
Language (ISO): en
Abstract: The dynamic change of vegetation cover exerts significant influences on the energetic and chemical circulation worldwide. Systematically monitoring the global vegetation cover change is critical to promote a better understanding of the basic biogeochemical processes, and their possible feedbacks to the global climate system. It is of great practical value to study dynamic vegetation variation related to climate change, human activities, and natural factors to explore the underlying relationships between vegetation cover change and its driving forces and the responding mechanisms of vegetation cover to the variability of the driving forces. Vegetation degradation is continually proceeding worldwide, but the degradation situation is more serious in developing countries than in developed countries. China is the largest developing country, and it has been experiencing significant socio-economic development, rapid urban expansion, and sharp population growth in eastern China in particular after launching the program of reform and opening-up termed "Socialism with Chinese Characteristics" in China in 1978. The unprecedented socio-economic development, urban expansion, and population growth have led to land use and land cover change, soil fertility decline, vegetation degradation, water contamination, and biodiversity loss in eastern China. Eastern China, a place with a highly developed socioeconomic status than other regions of China, covers seven provinces (e.g., Liaoning, Hebei, Shandong, Jiangsu, Zhejiang, Fujian, and Guangdong) and three municipalities (e.g., Beijing, Tianjin, and Shanghai) with an area of about 1.0277 million km2. It is of critical importance for monitoring the dynamic vegetation variation on multi-spatiotemporal scales, exploring the underlying relationship between vegetation cover change and its driving forces (e.g., climate forces, topographic forces, and socio-economic forces), and investigating the time lag effects of vegetation variation in response to climate variables (e.g., precipitation and temperature) in eastern China from 2001 to 2016. To achieve the objectives of this study, the Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index (NDVI) time series with a 250 m spatial resolution and a 16-day temporal resolution, monthly meteorological data from meteorological (automatic) base station , Digital Elevation Model data with a 30 m spatial resolution, socio-economic statistical data, and the map of land use types, gross domestic product, and population density in 2000 and 2015 with an 1 km spatial resolution, and the vector map of eastern China at city level were used. A set of mathematical methods such as the maximum value composite method, linear regression analysis, rescaled range analysis, coefficient of variation, Person’s correlation coefficient, t-test, and spatial analysis methods (e.g., surface analysis and overlap analysis) were applied in this study. This study aims at monitoring the dynamic change of vegetation cover and investigating the relationship between vegetation cover and its driving forces on multiple spatiotemporal scales in eastern China from 2001 to 2016. The objectives of this study are fulfilled and the main findings and new results of this study are summarized in following. The overall annual NDVI displays a distinctive spatial heterogeneity across eastern China, presenting a gradient decrease from the south to the north of eastern China. The spatial distribution of NDVI in spring, summer, and autumn follows a similar pattern, but the overall NDVI value is higher in summer than in spring and autumn. Our calculation indicated that, during the past 16 years, the vegetation cover had gradually increased in eastern China with a magnitude of 0.0003 year-1. Areas with a greening trend and areas with a browning trend account for 49% and 33% of the study area, respectively. Spatially, we found that the browning areas are mainly distributed in city centers and the three economic zones and its surrounding areas. Considering the vegetation variation on seasonal scale, NDVI performs an increasing trend in spring and autumn but a decreasing trend in summer. In this study, we detected that areas expected to show consistency accounting for a larger proportion when compared with the areas expected to show anti-consistency on annual scale, while an opposite phenomenon was found on seasonal scale. In terms of the future changing trend of vegetation cover, areas with certain vegetation degradation will be larger than areas with certain vegetation improvement for eastern China both on annual and seasonal scales in the future. Estimating the vegetation stability on the basis of variation of coefficient, we found that the vegetation cover is relatively stable in the south of the study area, but it fluctuated wildly in the north of the study area. Our calculation suggested that temperature can be considered as the dominant climate factor controlling the vegetation growth in eastern China. The relationship is more pronounced between NDVI and temperature than between NDVI and precipitation both on annual and seasonal scales in eastern China for the study period. Moreover, the relationship between NDVI and precipitation is higher in autumn than in spring and summer, while the response of NDVI to temperature is stronger in spring than in autumn, followed by in summer. In this study, we observed, spatially, the overall maximum correlation coefficients between NDVI and precipitation as well as NDVI and temperature are basically higher in the north and lower in the south of the study area both on annual and seasonal scales. Temporally, on annual scale, the NDVI shows no lag time to changes in temperature but a 1-month lag time to precipitation variation. On seasonal scale, the maximum responses of NDVI to changes in precipitation and temperature establish 1-month longer in summer than in spring and autumn. Spatially, the lag time for maximum NDVI response to precipitation and temperature gradually increase from the north to the south of the study area. Elevation is regarded to be a dominant factor affecting the vertical distribution of vegetation cover. Our findings indicated that both the vegetation cover and vegetation stability increase with the elevation increase and reach its peak at an elevation of about 500 m. The vegetation degradation is more serious at the elevation range of 0 to 100 m than at higher elevation ranges. It is worth noticing that, in this study, our result is against our initial assumptions that the vegetation growth on the north-facing slope is better than the vegetation growth on the south-facing slope. However, we found that the vegetation cover, vegetation cover change, and vegetation stability show no statistical difference on the south-facing slope and north-facing slope. Similar to the responding mechanisms between the elevation-vegetation cover and elevation-vegetation stability, the vegetation cover and vegetation stability show a gradient upward trend with slope range increase. Furthermore, the proportion of the areas with a greening trend shows a “humped” pattern with the slope range increase, and it reaches the peak at the slope range of 6° to 15°. Our findings indicated that vegetation degradation is generally attributed to socio-economic development, urban expansion, and population growth, particularly in Tianjin, Shanghai, Jiangsu, Zhejiang, Fujian, and Guangdong. However, implementing large-scale reforestation and afforestation programs such as the Natural Forest Conservation Program, Three-North Shelter Forest Program, Beijing and Tianjin Sandstorm Source Controlling Program, and Grain for Green Program contribute to the vegetation greening phenomenon since 1978, in Liaoning, Beijing, Shandong, and Hebei in particular. We further observed that, spatially, the dynamic change of vegetation cover is negatively coupled with socio-economic development, urban expansion, and population growth. Areas with a high-speed socio-economic development, rapid urban expansion, and sharp population growth are along with severe vegetation degradation and strong vegetation oscillation spatially.
Subject Headings: MODIS NDVI
Climate factors
Topographic factors
Socio-economic factors
Maximum correlation coefficient
Coefficient of variation
South-facing slope
Socio-economic development
Urban expansion
Population growth
Vegetation improvement
Vegetation degradation
Subject Headings (RSWK): Topografie
Issue Date: 2019
Appears in Collections:Raumbezogene Informationsverarbeitung und Modellbildung

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