scholarly journals Driving Forces of the Changes in Vegetation Phenology in the Qinghai–Tibet Plateau

2021 ◽  
Vol 13 (23) ◽  
pp. 4952
Author(s):  
Xigang Liu ◽  
Yaning Chen ◽  
Zhi Li ◽  
Yupeng Li ◽  
Qifei Zhang ◽  
...  
Keyword(s):  
Air Temperature ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
Growing Season ◽  
Tibet Plateau ◽  
Vegetation Phenology ◽  
Climate Change Research ◽  
Temperature And Precipitation ◽  
Qinghai Tibet Plateau

Phenological change is an emerging hot topic in ecology and climate change research. Existing phenological studies in the Qinghai–Tibet Plateau (QTP) have focused on overall changes, while ignoring the different characteristics of changes in different regions. Here, we use the Global Inventory Modeling and Mapping Studies (GIMMS3g) normalized difference vegetation index (NDVI) dataset as a basis to discuss the temporal and spatial changes in vegetation phenology in the Qinghai–Tibet Plateau from 1982 to 2015. We also analyze the response mechanisms of pre-season climate factor and vegetation phenology and reveal the driving forces of the changes in vegetation phenology. The results show that: (1) the start of the growing season (SOS) and the length of the growing season (LOS) in the QTP fluctuate greatly year by year; (2) in the study area, the change in pre-season precipitation significantly affects the SOS in the northeast (p < 0.05), while, the delay in the end of the growing season (EOS) in the northeast is determined by pre-season air temperature and precipitation; (3) pre-season precipitation in April or May is the main driving force of the SOS of different vegetation, while air temperature and precipitation in the pre-season jointly affect the EOS of different vegetation. The differences in and the diversity of vegetation types together lead to complex changes in vegetation phenology across different regions within the QTP. Therefore, addressing the characteristics and impacts of changes in vegetation phenology across different regions plays an important role in ecological protection in this region.

scholarly journals Effects of Air Temperature and Precipitation on Soil Moisture on the Qinghai-Tibet Plateau during the 2015 Growing Season

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Qingyan Xie ◽  
Jianping Li ◽  
Yufei Zhao
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Hydrological Cycle ◽  
Critical Role ◽  
Growing Season ◽  
Tibet Plateau ◽  
Ecosystem Stability ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
Qinghai Tibet Plateau

The Qinghai-Tibet Plateau (QTP) holds massive freshwater resources and is one of the most active regions in the world with respect to the hydrological cycle. Soil moisture (SM) plays a critical role in hydrological processes and is important for plant growth and ecosystem stability. To investigate the relationship between climatic factors (air temperature and precipitation) and SM during the growing season in various climate zones on the QTP, data from three observational stations were analyzed. The results showed that the daily average (Tave) and minimum air temperatures (Tmin) significantly influenced SM levels at all depths analyzed (i.e., 10, 20, 30, 40, and 50 cm deep) at the three stations, and Tmin had a stronger effect on SM than did Tave. However, the daily maximum air temperature (Tmax) generally had little effect on SM, although it had showed some effects on SM in the middle and deeper layers at the Jiali station. Precipitation was an important factor that significantly influenced the SM at all depths at the three stations, but the influence on SM in the middle and deep layers lagged the direct effect on near-surface SM by 5–7 days. These results suggest that environment characterized by lower temperatures and higher precipitation may promote SM conservation during the growing season and in turn support ecosystem stability on the QTP.

scholarly journals Revealing the Fingerprint of Climate Change in Interannual NDVI Variability among Biomes in Inner Mongolia, China

2020 ◽  
Vol 12 (8) ◽  
pp. 1332 ◽  
Author(s):  
Linghui Guo ◽  
Liyuan Zuo ◽  
Jiangbo Gao ◽  
Yuan Jiang ◽  
Yongling Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Lag ◽  
Growing Season ◽  
Climate Fluctuations ◽  
Temperature And Precipitation ◽  
Lag Effect

An understanding of the response of interannual vegetation variations to climate change is critical for the future projection of ecosystem processes and developing effective coping strategies. In this study, the spatial pattern of interannual variability in the growing season normalized difference vegetation index (NDVI) for different biomes and its relationships with climate variables were investigated in Inner Mongolia during 1982–2015 by jointly using linear regression, geographical detector, and geographically weighted regression methodologies. The result showed that the greatest variability of the growing season NDVI occurred in typical steppe and desert steppe, with forest and desert most stable. The interannual variability of NDVI differed monthly among biomes, showing a time gradient of the largest variation from northeast to southwest. NDVI interannual variability was significantly related to that of the corresponding temperature and precipitation for each biome, characterized by an obvious spatial heterogeneity and time lag effect marked in the later period of the growing season. Additionally, the large slope of NDVI variation to temperature for desert implied that desert tended to amplify temperature variations, whereas other biomes displayed a capacity to buffer climate fluctuations. These findings highlight the relationships between vegetation variability and climate variability, which could be used to support the adaptive management of vegetation resources in the context of climate change.

scholarly journals Seasonal normalized difference vegetation index responses to air temperature and precipitation in Baghdad

2020 ◽  
Vol 5 (1) ◽  
pp. 631-637
Author(s):  
Salwa S. Naif ◽  
Dalia A. Mahmood ◽  
Monim H. Al-Jiboori
Keyword(s):  
Air Temperature ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Ground Surface ◽  
Vital Role ◽  
Growth Patterns ◽  
Climate Indices ◽  
Climatic Data ◽  
Vegetation Growth ◽  
Temperature And Precipitation

AbstractThe spatial distribution of urban vegetation cover is strongly related to climatological conditions, which play a vital role in urban cooling via shading and reducing ground surface temperature and effective strategy in mitigation urban heat island. Based on the Landsat satellite images, the quantitative normalized difference vegetation index (NDVI) was spatially mapped at two times for each year during 2008, 2013, 2019 in Baghdad. The NDVI values ranged from −1 to +1 with considering values larger than 0.2 indicate the dense healthy vegetation. In this study, the fractional areas of NDVI >0.2 were computed with their percentage. The responses of the NDVI during the growing seasons to two climate indices (i.e., air temperature and precipitation) were investigated. These climatic data obtained from the Iraqi Meteorological Organization and Seismology for the aforementioned years were used to explore the potential correlations between seasonal NDVI and above climate variables. The result shows that NDVI-derived vegetation growth patterns were highly correlated with their recording during the current growth seasons.

scholarly journals NDVI Dynamics and Its Response to Climate Change and Reforestation in Northern China

2020 ◽  
Vol 12 (24) ◽  
pp. 4138
Author(s):  
Xingna Lin ◽  
Jianzhi Niu ◽  
Ronny Berndtsson ◽  
Xinxiao Yu ◽  
Linus Zhang ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Terrestrial Ecosystem ◽  
Northern China ◽  
Tibet Plateau ◽  
Modis Ndvi ◽  
Degraded Area ◽  
Temperate Desert ◽  
Vegetation Region ◽  
Qinghai Tibet Plateau

Vegetation is an important component of the terrestrial ecosystem that plays an essential role in the exchange of water and energy in climate and biogeochemical cycles. This study investigated the spatiotemporal variation of normalized difference vegetation index (NDVI) in northern China using the GIMMS-MODIS NDVI during 1982–2018. We explored the dominant drivers of NDVI change using regression analyses. Results show that the regional average NDVI for northern China increased at a rate of 0.001 year−1. NDVI improved and degraded area corresponded to 36.1% and 9.7% of the total investigated area, respectively. Climate drivers were responsible for NDVI change in 46.2% of the study area, and the regional average NDVI trend in the region where the dominant drivers were temperature (T), precipitation (P), and the combination of precipitation and temperature (P&T), increased at a rate of 0.0028, 0.0027, and 0.0056 year−1, respectively. We conclude that P has positive dominant effects on NDVI in the subregion VIAiia, VIAiic, VIAiib, VIAib of temperate grassland region, and VIIBiia of temperate desert region in northern China. T has positive dominant effects on NDVI in the alpine vegetation region of Qinghai Tibet Plateau. NDVI is negatively dominated by T in the subregion VIIBiib, VIIBib, VIIAi, and VIIBi of temperate desert regions. Human activities affect NDVI directly by reforestation, especially in Shaanxi, Shanxi, and Hebei provinces.

scholarly journals Drainage Density and Its Controlling Factors on the Eastern Margin of the Qinghai–Tibet Plateau

2022 ◽  
Vol 9 ◽  
Author(s):  
Hongshan Gao ◽  
Fenliang Liu ◽  
Tianqi Yan ◽  
Lin Qin ◽  
Zongmeng Li
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Arid Environment ◽  
Drainage Density ◽  
Tibet Plateau ◽  
Vegetation Coverage ◽  
Mean Annual Precipitation ◽  
Eastern Margin ◽  
Qinghai Tibet Plateau ◽  
Planation Surfaces

The drainage density (Dd) is an important index to show fluvial geomorphology. The study on Dd is helpful to understand the evolution of the whole hydrological and geomorphic process. Based on the Shuttle Radar Topography Mission 90-m digital elevation model, the drainage network of basins along the eastern margin of the Qinghai–Tibet Plateau is extracted using a terrain morphology-based method in ArcGIS 10.3, and Dd is calculated. The spatial characteristics of Dd are analyzed, and the relationship between Dd and its influencing factors, e.g., the topography, precipitation, and vegetation coverage, is explored. Our results show that terrains with a plan curvature ≥3 can represent the channels in the study area. Dd ranges from 2.5 to 0.1 km/km2, increases first, and then decreases from north to south on the eastern margin of the Qinghai–Tibet Plateau. Dd decreases with increasing average slope and average local relief. On the low-relief planation surfaces, Dd increases with increasing altitude, while on the rugged mountainous above planation surfaces, Dd decreases rapidly with increasing altitude. Dd first increased and then decreased with increasing mean annual precipitation (MAP) and normalized difference vegetation index (NDVI), and Dd reaches a maximum in the West Qinling Mountains with a semi-arid environment, indicating that Dd in different climatic regions of the eastern margin of the Qinghai–Tibet Plateau was mainly controlled by precipitation and vegetation.

scholarly journals Growing Season Vegetation Dynamics Based on NDVI and the Driving Forces in Nepal during 1982-2015

2020 ◽  
Vol 17 ◽  
pp. 1-22
Author(s):  
Binod Baniya ◽  
Qiuhong Tang ◽  
Madan Koirala ◽  
Kedar Rijal ◽  
Giri Kattel
Keyword(s):  
Vegetation Dynamics ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
Pearson Correlation ◽  
Growing Season ◽  
Kendall Test ◽  
Warming Trend ◽  
Shuttle Radar Topography Mission

Monitoring and attributing growing season vegetation dynamics have become crucial for maintaining the structure and function of the ecosystem. The objective of this research was to examine the spatial and temporal vegetation changes and explore their driving forces during growing season in Nepal. It also explored the variation of Normalized Difference Vegetation Index (NDVI) in different altitudes at each 100m interval. The National Oceanic and Atmospheric Administration (NOAA) NDVI, monthly temperature, precipitation and Shuttle Radar Topography Mission (SRTM) 90m Digital Elevation Model (DEM) were used. The linear regression model, Sen’s slope, Mann Kendall test and Pearson correlation between NDVI and climate, i.e., temperature and precipitation were computed. The driving forces were identified based on threshold segmentation method. Our results showed positive intensity of vegetation change. The NDVI has significantly increased at the rate of 0.001yr-1, 0.0005yr-1 and 0.002yr-1 in growing season, spring and autumn but it has insignificantly increased at the rate of 0.0003yr-1 in summer. In the meantime, growing season temperature has significantly increased with an average warming trend of 0.03&deg;Cyr-1 but precipitation decreased at the rate of 2.76 mm yr-1 during 1982-2015. The NDVI increased in 84.20% (53.08% significant) of the area. The correlation between NDVI and temperature was found positive whereas correlation with precipitation was negative. Spatially, 84.05% of the study area found positive correlation between NDVI and temperature with 25.72% significance (p<0.05) which was very less with precipitation. Our results demonstrate that NDVI was strongly correlated with temperature compared with precipitation. Beyond the climate, NDVI changes were also attributed to multi-control environments and ecological restoration in Nepal.  

scholarly journals What Are the Driving Forces of Urban CO2 Emissions in China? A Refined Scale Analysis between National and Urban Agglomeration Levels

2019 ◽  
Vol 16 (19) ◽  
pp. 3692 ◽  
Author(s):  
Wang ◽  
Liu ◽  
Shi
Keyword(s):  
Population Density ◽  
Co2 Emissions ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
National Level ◽  
Probit Model ◽  
Environmental Problems ◽  
Urban Agglomeration ◽  
Temperature And Precipitation

With the advancement of society and the economy, environmental problems have increasingly emerged, in particular, problems with urban CO2 emissions. Exploring the driving forces of urban CO2 emissions is necessary to gain a better understanding of the spatial patterns, processes, and mechanisms of environmental problems. Thus, the purpose of this study was to quantify the driving forces of urban CO2 emissions from 2000 to 2015 in China, including explicit consideration of a comparative analysis between national and urban agglomeration levels. Urban CO2 emissions with a 1-km spatial resolution were extracted for built-up areas based on the anthropogenic carbon dioxide (ODIAC) fossil fuel emission dataset. Six factors, namely precipitation, slope, temperature, population density, normalized difference vegetation index (NDVI), and gross domestic product (GDP), were selected to investigate the driving forces of urban CO2 emissions in China. Then, a probit model was applied to examine the effects of potential factors on urban CO2 emissions. The results revealed that the population, GDP, and NDVI were all positive driving forces, but that temperature and precipitation had negative effects on urban CO2 emissions at the national level. In the middle and south Liaoning urban agglomeration (MSL), the slope, population density, NDVI, and GDP were significant influencing factors. In the Pearl River Delta urban agglomeration (PRD), six factors had significant impacts on urban CO2 emissions, all of which were positive except for slope, which was a negative factor. Due to China’s hierarchical administrative levels, the model results suggest that regardless of which level is adopted, the impacts of the driving factors on urban CO2 emissions are quite different at the national compared to the urban agglomeration level. The degrees of influence of most factors at the national level were lower than those of factors at the urban agglomeration level. Based on an analysis of the forces driving urban CO2 emissions, we propose that it is necessary that the environment play a guiding role while regions formulate policies which are suitable for emission reductions according to their distinct characteristics.

Effects of multi-time scales drought on vegetation dynamics in Qaidam River Basin, Qinghai-Tibet Plateau from 1998 to 2015

2020 ◽  
Author(s):  
Yongxiu Sun ◽  
Shiliang Liu ◽  
Yuhong Dong ◽  
Shikui Dong ◽  
Fangning Shi
Keyword(s):  
River Basin ◽  
Time Scales ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Terrestrial Ecosystems ◽  
Tibet Plateau ◽  
Desert Grassland ◽  
Qinghai Tibet Plateau ◽  
Different Time Scales

&lt;p&gt;Quantifying drought variations at multi-time scales is important to assess the potential impacts of climate change on terrestrial ecosystems, especially vulnerable desert grassland. Based on the Normalized Difference Vegetation Index (NDVI) and Standardized Precipitation Evapotranspiration Index (SPEI), we assessed the influences of different time-scales drought (SPEI-3, SPEI-6, SPEI-12, SPEI-24, and SPEI-48 with 3, 6, 12, 24 and 48 months, respectively) on vegetation dynamics in the Qaidam River Basin, Qinghai-Tibet Plateau. Results showed that: (1) Temporally, annual and summer NDVI increased, while spring and autumn NDVI decreased from 1998 to 2015. Annual, spring and summer SPEI increased and autumn SPEI decreased. (2) Spatially, annual, spring, summer, and autumn NDVI increased in the periphery of the Basin, with 45.98%, 22.68%, 43.90%&amp;#160; and 30.80% of the study area, respectively. SPEI showed a reverse variation pattern with NDVI, with an obvious decreasing trend from southeast to northwest. (3) Annual vegetation growth in most areas (69.53%, 77.33%, 86.36%, 90.19% and 85.44%) was correlated with drought at all time-scales during 1998-2015. However, high spatial and seasonal differences occurred among different time-scales, with the maximum influence in summer under SPEI24. (4) From month to annual scales, NDVI of all land cover types showed higher correlation to long-term drought of SPEI24 or SPEI48. Vegetation condition index (VCI) and SPEI were positively correlated at all time-scales and had a more obvious response in summer. The highest correlation was VCI of grassland (June-July) or forest (April-May, August-October) and SPEI48. This study contributes to exploring the effect of drought on vegetation dynamics at different time scales, further providing credible guidance for regional water resources management.&lt;/p&gt;

scholarly journals ANN Model-Based Simulation of the Runoff Variation in Response to Climate Change on the Qinghai-Tibet Plateau, China

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Chang Juan ◽  
Wang Genxu ◽  
Mao Tianxu ◽  
Sun Xiangyang
Keyword(s):  
Climate Change ◽  
Climatic Change ◽  
Air Temperature ◽  
Practical Significance ◽  
Tibet Plateau ◽  
Ann Model ◽  
Temperature And Precipitation ◽  
Runoff Variation ◽  
Input Variables ◽  
Qinghai Tibet Plateau

Precisely quantitative assessments of stream flow response to climatic change and permafrost thawing are highly challenging and urgent in cold regions. However, due to the notably harsh environmental conditions, there is little field monitoring data of runoff in permafrost regions, which has limited the development of physically based models in these regions. To identify the impacts of climate change in the runoff process in the Three-River Headwater Region (TRHR) on the Qinghai-Tibet Plateau, two artificial neural network (ANN) models, one with three input variables (previous runoff, air temperature, and precipitation) and another with two input variables (air temperature and precipitation only), were developed to simulate and predict the runoff variation in the TRHR. The results show that the three-input variable ANN model has a superior real-time prediction capability and performs well in the simulation and forecasting of the runoff variation in the TRHR. Under the different scenarios conditions, the forecasting results of ANN model indicated that climate change has a great effect on the runoff processes in the TRHR. The results of this study are of practical significance for water resources management and the evaluation of the impacts of climatic change on the hydrological regime in long-term considerations.

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