Understanding global spatio-temporal trends and the relationship between vegetation greenness and climate factors by land cover during 1982–2014

Effects of climate variability and urbanization on spatiotemporal patterns of vegetation in the middle and lower Yangtze River Basin, China

Vegetation serves as a crucial indicator of ecological environment and plays a vital role in preserving ecosystem stability. However, as urbanization escalates rapidly, natural vegetation landscapes are undergoing continuous transformation. Paradoxically, vegetation is pivotal in mitigating the ecological and environmental challenges posed by urban sprawl. The middle and lower Yangtze River Basin (MLYRB) in China, particularly its economically thriving lower reaches, has witnessed a surge in urbanization. Consequently, this study explored the spatiotemporal variations of normalized difference vegetation index (NDVI) in the MLYRB, with an emphasis on elucidating the impact of climate change and urbanization on vegetation dynamics. The results indicate that a significant increasing trend in NDVI across the MLYRB from 2000 to 2020, a pattern that is expected to persist. An improvement in vegetation was observed in 94.12% of the prefecture-level cities in the study area, predominantly in the western and southern regions. Temperature and wind speed stand out as dominant contributors to this improvement. Nevertheless, significant vegetation degradation was detected in some highly urbanized cities in the central and eastern parts of the study area, mainly attributed to the negative effects of escalating urbanization. Interestingly, a positive correlation between NDVI and the urbanization rate was observed, which may be largely related to proactive ecological preservation policies. Additionally, global climatic oscillations were identified as a key force driving periodic NDVI variations. These findings hold significant importance in promoting harmonious urbanization and ecological preservation, thereby providing invaluable insights for future urban ecological planning efforts.

The Nonlinear Impact of Mobile Human Activities on Vegetation Change in the Guangdong-Hong Kong-Macao Greater Bay Area

Vegetation is essential for ecosystem function and sustainable urban development. In the context of urbanization, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), as the typical urban-dominated region, has experienced a remarkable increase in social and economic activities. Their impact on vegetation is of great significance but unclear, as interannual flow data and linear methods have limitations. Therefore, in this study, we used human and vehicle flow data to build and simulate the indices of mobile human activity. In addition, we used partial least squares regression (PLSR), random forest (RF), and geographical detector (GD) models to analyze the impact of mobile human activities on vegetation change. The results showed that indices of mobile human and vehicle flow increased by 1.43 and 7.68 times from 2000 to 2019 in the GBA, respectively. Simultaneously, vegetation increased by approximately 64%, whereas vegetation decreased mainly in the urban areas of the GBA. Vegetation change had no significant linear correlation with mobile human activities, exhibiting a regression coefficient below 0.1 and a weight of coefficients of PLSR less than 40 between vegetation change and all the factors of human activities. However, a more significant nonlinear relationship between vegetation change and driving factors were obtained. In the RF regression model, vegetation decrease was significantly affected by mobile human activity of vehicle flow, with an importance score of 108.11. From the GD method, vegetation decrease was found to mainly interact with indices of mobile human and vehicle inflow, and the highest interaction force was 0.82. These results may support the attainment of sustainable social-ecological systems and global environmental change.

Revealing the dominant factors of vegetation change in global ecosystems

In the context of climate change, revealing the causes of significant changes in ecosystems will help maintain ecosystem stability and achieve sustainability. However, the dominant influencing factors of different ecosystems in different months on a global scale are not clear. We used Ordinary Least Squares Model and Mann–Kendall test to detect the significant changes (p < 0.05) of ecosystem on a monthly scale from 1981 to 2015. And then multi-source data, residual analysis and partial correlation method was used to distinguish the impact of anthropogenic activities and dominant climate factors. The result showed that: (1) Not all significant green areas in all months were greater than the browning areas. Woodland had a larger greening area than farmland and grassland, except for January, May, and June, and a larger browning area except for September, November, and December. (2) Anthropogenic activities are the leading factors causing significant greening in ecosystems. However, their impact on significant ecosystem browning was not greater than that of climate change on significant ecosystem greening in all months. (3) The main cause of the ecosystem’s significant greening was temperature. Along with temperature, sunshine duration played a major role in the significant greening of the woodland. The main causes of significant farmland greening were precipitation and soil moisture. Temperature was the main factor that dominated the longest month of significant browning of grassland and woodland. Temperature and soil moisture were the main factors that dominated the longest month of significant browning of farmland. Our research reveals ecosystem changes and their dominant factors on a global scale, thereby supporting the sustainable ecosystem management.

Vegetation Greenness Trend in Dry Seasons and Its Responses to Temperature and Precipitation in Mara River Basin, Africa

The Mara River Basin of Africa has a world-famous ecosystem with vast vegetation, which is home to many wild animals. However, the basin is experiencing vegetation degradation and bad climate change, which has caused conflicts between people and wild animals, especially in dry seasons. This paper studied the vegetation greenness (VG), vegetation greenness trends (VGT), and their responses to climate change in dry seasons in the Mara River Basin, Africa. Firstly, based on Google Earth Engine (GEE) platform and Sentinel-2 images, the vegetation distribution map of the Mara River Basin was drawn. Then dry seasons MODIS NDVI data (January to February and June to September) were used to analyze the VGT. Finally, a random forest regression algorithm was used to evaluate the response of VG and VGT to temperature and precipitation derived from ERA5 from 2000 to 2019 at a resolution of 250 m. The results showed that the VGT was fluctuating in dry seasons, and the spatial differentiation was obvious. The greenness increasing trends both upstream and downstream were significantly larger than that of in the midstream. The responses of VG to precipitation were almost twice larger than temperature, and the responses of VGT to temperature were about 1.5 times larger than precipitation. The climate change trend of rising temperature and falling precipitation will lead to the degradation of vegetation and the reduction of crop production. There will be a vegetation degradation crisis in dry seasons in the Mara River Basin in the future. Identifying the spatiotemporal changes of VGT in dry seasons will be helpful to understand the response of VG and VGT to climate change and could also provide technical support to cope with climate-change-related issues for the basin.

Regional and Phased Vegetation Responses to Climate Change Are Different in Southwest China

Southwestern China (SW) is simultaneously affected by the East Asian monsoon, South Asian monsoon and westerly winds, forming a complex and diverse distribution pattern of climate types, resulting in a low interpretation rate of vegetation changes by climate factors in the region. This study explored the response characteristics of vegetation to climatic factors in the whole SW and the core area of typical climate type and the phased changes in response, adopting the form of “top-down”, using linear trend method, moving average method and correlation coefficient, and based on the climate data of CRU TS v. 4.02 for the period 1982–2017 and the annual maximum, 3/4 quantile, median, 1/4 quantile, minimum and average (abbreviated as P100, P75, P50, P25, P5 and Mean) of GIMMS NDVI, which were to characterize vegetation growth conditions. Coupling with the trend and variability of climate change, we identified four major types of climate change in the SW, including the significant increase in both temperature and precipitation (T+*-P+*), the only significant increase in temperature and decrease (T+*-P−) or increase (T+*-P+) of precipitation and no significant change (NSC). We then screened out nine typical areas of climate change types (i.e., core areas (CAs)), followed by one T+*-P+* area, which was located in the center of the lake basin of the Qiangtang Plateau. The response of vegetation to climatic factors in T+*-P+* area/T+*-P+ areas and T+*-P− areas/NSC areas were mainly manifested in an increase and a significant decrease, which makes the response characteristics of vegetation to climatic factors in the whole SW have different directionality at different growth stages. Our results may provide new ideas for clearly showing the complexity and heterogeneity of the vegetation response to climate change in the region under the background of global warming.

Understanding the Long-Term Vegetation Dynamics of North Korea and Their Impact on the Thermal Environment

In response to widespread deforestation, North Korea has restored forests through national policy over the past 10 years. Here, the entire process of forest degradation and restoration was evaluated through satellite-based vegetation monitoring, and its effects were also investigated. The vegetation dynamics of North Korea were characterized from 1986 to 2021 using the Landsat satellite 5–7, after which we evaluated the effect of vegetation shifts through changes in surface temperature since the 2000s. Vegetation greenness decreased significantly from the 1980s to the 2000s but increased in recent decades due to forest restoration. During the deforestation period, vegetation in all areas of North Korea tended to decrease, which was particularly noticeable in the provinces of Pyongannam-do and Hamgyongnam-do. During the forest restoration period, increases in vegetation greenness were evident in most regions except for some high-mountainous and developing regions, and the most prominent increase was seen in Pyongyang and Pyongannam-do. According to satellite-based analyses, the land surface temperature exhibited a clear upward trend (average slope = 0.13). However, large regional differences were identified when the analysis was shortened to encompass only the last 10 years. Particularly, the correlation between the area where vegetation improved and the area where the surface temperature decreased was high (−0.32). Moreover, the observed atmospheric temperature increased due to global warming, but only the surface temperature exhibited a decreasing trend, which could be understood by the effect of vegetation restoration. Our results suggest that forest restoration can affect various sectors beyond the thermal environment due to its role as an enhancer of ecosystem services.

Spatial Variations in Vegetation Greening in 439 Chinese Cities From 2001 to 2020 Based on Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index Data

Vegetation is essential for maintaining urban ecosystems, climate regulation, and resident health. To explore the variations in city-level vegetation greening (VG) and its relationship to urban expansion, VG in 439 Chinese cities was extracted using the Theil–Sen and Mann–Kendall algorithms based on Moderate Resolution Imaging Spectroradiometer EVI (enhanced vegetation index) data from 2001 to 2020. The spatial variations in VG and its patterns, as well as its relationship with urban expansion, were then analyzed. The following results were obtained: (1) cities with larger greening areas were primarily located in the central and eastern provinces of China, followed by the southeastern, southwestern, and western provinces. The 48 cities with the largest greening areas accounted for 60.47% of the total greening area. (2) VG patches in northern China exhibited better integrity. (3) The centralization trend of VG was evident; the location of VG patterns was influenced by the form of urban expansion. (4) The intensity of artificial impervious area expansion had a weak negative correlation with the VG. Therefore, we must enhance vegetation in new urban areas to improve the spatial balance of VG. The present results of this study can provide a foundation for developing effective policies for the construction and management of urban greenery projects.

Quantitative Contributions of Climate Change and Human Activities to Vegetation Changes in the Upper White Nile River

Vegetation changes in the Upper White Nile River (UWNR) are of great significance to the maintenance of local livelihoods, the survival of wildlife, and the protection of species habitats. Based on the GIMMS NDVI3g and MODIS normalized difference vegetation index (NDVI) data, the temporal and spatial characteristics of vegetation changes in the UWNR from 1982 to 2020 were analyzed by a Theil-Sen median trend analysis and Mann-Kendall test. The future trend of vegetation was analyzed by the Hurst exponential method. A partial correlation analysis was used to analyze the relationship of the vegetation and climate factors, and a residual trend analysis was used to quantify the influence of climate change and human activities on vegetation change. The results indicated that the average NDVI value (0.75) of the UWNR from 1982 to 2020 was relatively high. The average coefficient of variation for the NDVI was 0.059, and the vegetation change was relatively stable. The vegetation in the UWNR increased 0.013/10 year on average, but the vegetation degradation in some areas was serious and mainly classified as agricultural land. The results of a future trend analysis showed that the vegetation in the UWNR is mainly negatively sustainable, and 62.54% of the vegetation will degrade in the future. The NDVI of the UWNR was more affected by temperature than by precipitation, especially on agricultural land and forestland, which were more negatively affected by warming. Climate change and human activities have an impact on vegetation changes, but the spatial distributions of the effects differ. The relative impact of human activities on vegetation change accounted for 64.5%, which was higher than that of climate change (35.5%). Human activities, such as the large proportion of agriculture, rapid population growth and the rapid development of urbanization were the main driving forces. Establishing a cross-border drought joint early warning mechanism, strengthening basic agricultural research, and changing traditional agricultural farming patterns may be effective measures to address food security and climate change and improve vegetation in the UWNR.