Growing Season Normalized Difference Vegetation Index Research Articles

Elevation dependence of drought legacy effects on vegetation greenness over the Tibetan Plateau

Extreme drought events exert both immediate and prolonged influences on terrestrial ecosystems, yet the patterns and mechanisms of the delayed effects of extreme drought on alpine ecosystems remain largely unknown. In this study, we use satellite-derived normalized difference vegetation index (NDVI) data to examine the legacy effect of severe drought events on vegetation greenness across the Tibetan Plateau (TP). A pervasive, negative drought legacy effect, lasting about one year, is detected for all plant functional types including forests, shrubs and grasslands on the TP. The magnitude of the identified legacy effect, namely, the reduced growing-season NDVI in the first year post-drought, is spatially heterogeneous and exhibits a clear altitude dependence, while divergent relationships between elevation and the legacy effect are observed between alpine meadow and steppe. For alpine meadow, more pronounced legacy effects occur at higher altitudes with lower precipitation and temperature, suggesting a weaker drought resilience of alpine meadow under dryer and colder conditions. Whereas for alpine steppe, the magnitude of the negative legacies reduces as precipitation decreases along the elevation, which might be due to a greater adaptability to drought under more arid conditions that enables plant communities to recover to their normal state faster in these very dry regions. Our results advance the understanding of drought legacy effects on TP alpine ecosystems and highlight future avenues for research into how different alpine ecosystem types will respond to drought stress.

Vegetation Change and Its Response to Climate Change between 2000 and 2016 in Marshes of the Songnen Plain, Northeast China

Songnen Plain is a representative semi-arid marshland in China. The Songnen Plain marshes have undergone obvious loss during the past decades. In order to protect and restore wetland vegetation, it is urgent to investigate the vegetation change and its response to climate change in the Songnen Plain marshes. Based on the normalized difference vegetation index (NDVI) and climate data, we investigated the spatiotemporal change of vegetation and its relationship with temperature and precipitation in the Songnen Plain marshes. During 2000–2016, the growing season mean NDVI of the Songnen Plain marshes significantly (p < 0.01) increased at a rate of 0.06/decade. For the climate change effects on vegetation, the growing season precipitation had a significant positive effect on the growing season NDVI of marshes. In addition, this study first found asymmetric effects of daytime maximum temperature (Tmax) and nighttime minimum temperature (Tmin) on NDVI of the Songnen Plain marshes: The growing season NDVI correlated negatively with Tmax but positively with Tmin. Considering the global asymmetric warming of Tmax and Tmin, more attention should be paid to these asymmetric effects of Tmax and Tmin on the vegetation of marshes.

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

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.

Effects of Climate and Land Use changes on Vegetation Dynamics in the Yangtze River Delta, China Based on Abrupt Change Analysis

Vegetation dynamics is thought to be affected by climate and land use changes. However, how the effects vary after abrupt vegetation changes remains unclear. Based on the Mann-Kendall trend and abrupt change analysis, we monitored vegetation dynamics and its abrupt change in the Yangtze River delta during 1982–2016. With the correlation analysis, we revealed the relationship of vegetation dynamics with climate changes (temperature and precipitation) pixel-by-pixel and then with land use changes analysis we studied the effects of land use changes (unchanged or changed land use) on their relationship. Results showed that: (1) the Normalized Vegetation Index (NDVI) during growing season that is represented as GSN (growing season NDVI) showed an overall increasing trend and had an abrupt change in 2000. After then, the area percentages with decreasing GSN trend increased in cropland and built-up land, mainly located in the eastern, while those with increasing GSN trend increased in woodland and grassland, mainly located in the southern. Changed land use, except the land conversions from/to built-up land, is more favor for vegetation greening than unchanged land use (2) after abrupt change, the significant positive correlation between precipitation and GSN increased in all unchanged land use types, especially for woodland and grassland (natural land use) and changed land use except built-up land conversion. Meanwhile, the insignificant positive correlation between temperature and GSN increased in woodland, while decreased in the cropland and built-up land in the northwest (3) after abrupt change, precipitation became more important and favor, especially for natural land use. However, temperature became less important and favor for all land use types, especially for built-up land. This research indicates that abrupt change analysis will help to effectively monitor vegetation trend and to accurately assess the relationship of vegetation dynamics with climate and land use changes.

The contrasting east–west pattern of vegetation restoration under the large‐scale ecological restoration programmes in southwest China

AbstractEcological restoration programmes (ERPs) play an important role in reversing degraded ecosystems and realizing environmental sustainability. However, few studies have given attention to the spatial heterogeneity in the effectiveness of large‐scale ERPs for restoring vegetation on a broad regional scale. Based on the GIMMS NDVI3g time‐series of southwest China, we determined the spatiotemporal trends of the peak growing season NDVI (PGS‐NDVI) in the pre‐ERP stage (1982–1998) and in the post‐ERP stage (1999–2015). Using the NDVI‐climate regression model developed during the pre‐ERP stage and the residual trend analysis method, we derived the anthropogenic PGS‐NDVI trends of the post‐ERP stage on a per‐pixel and spatial average basis. We found that there existed an east (greening)–west (browning) contrasting pattern in the anthropogenic vegetation change during the post‐ERP stage. The proportions of anthropogenic greening pixels were heterogeneous among provinces, ranging from 66.1% (Guangxi) to 8.6% (Xizang). The ERP effectiveness index and the ERP efficiency index for Guangxi were the highest among the provinces, whereas they were both negative for Yunnan and Xizang. Such contrasting restoration pattern was probably caused by multiple factors, including but not limited to the imbalanced implementation of large‐scale ERPs and the inappropriate afforestation that inadequately takes into account local conditions. Our analysis highlights the great heterogeneity in the effectiveness of large‐scale ERPs for vegetation restoration across a broad regional scale. Large‐scale ERPs should be implemented in a coordinated manner and be tailored to local conditions.

Extended growing season reduced river runoff in Luanhe River basin

Global warming has substantially altered vegetation growth and phenology in temperate biomes worldwide, whose impacts on river runoff have not been fully understood, especially at the watershed scale. Investigating the relationships among phenological shift, changes in vegetation growth, and river runoff is essential to improve our understanding of the ecosystem response to ongoing climate change. Using in-situ runoff records, phenological dates that were extracted from the normalized difference vegetation index (NDVI) over the period 1982–2015, and grey relational analysis, this study investigated the relationships between changes in river runoff and phenological variables in Luanhe River basin, China. It was found that the growing season in the Luanhe basin was significantly extended by 0.60 ± 0.08 d per year associated with climate warming over the period 1982–2015, which is mainly related to the earlier start of growing season (SOS, 0.40 ± 0.05 d per year), rather than the delayed end of growing season (EOS, 0.11 ± 0.01 d per year). The vegetation growth, defined as the average growing season NDVI (GS_NDVI), significantly increased in more than 88.4% of the study area, on average the GS_NDVI increased by 1.30 ± 0.03 × 10−3 d per year. On the other hand, runoff significantly reduced by 1.42 mm per year over the study period, but large differences were observed between upper and middle-lower reaches region of the Luanhe basin. The grey relational analysis confirmed the primary regulation of river runoff by precipitation, but the length of growing season and vegetation growth also played a key role in the changes of runoff. These results provide new insights into the interaction between vegetation dynamics and water balance at the watershed scale, and highlight to couple the phenological processes into eco-hydrological models to improve the modelling accuracy.

Vegetation dynamics and the relations with climate change at multiple time scales in the Yangtze River and Yellow River Basin, China

Abstract Understanding the vegetation dynamics and their responses to natural and anthropogenic factors plays a key part in improving ecosystem structure and function in the context of global warming. In present study, the spatiotemporal heterogeneity of vegetation coverage and their relationships with climate change at different time scales in the Yangtze River and Yellow River Basin (YZYRB) were analyzed based on the Ensemble Empirical Mode Decomposition (EEMD). The results showed that the growing-season Normalized Difference Vegetation Index (GSN) increased by 0.011/decade (z = 4.09) during 1982–2015. The areas with significant improvement trend were mainly distributed in the central and eastern Yellow River Basin (YRB) and the central Yangtze River Basin (YZRB), while the east YZRB was significantly degraded. The correlation analysis based on multiple time scales illustrated that as the time scales increased, the response of vegetation to climate variations became more prominent. Especially under the long-term trend, the significance of the correlations between vegetation and precipitation/temperature increased with the area percentage increasing up to 81.5% and 93.62%, respectively. The relationship between GSN and precipitation was mainly driven by climatic conditions and vegetation types at 3-year time scale, altitude and vegetation types for the long-term trend. The relationship between GSN and temperature was mainly related to the climatic conditions and elevation at 3-year time scale, the vegetation types and climatic conditions at 6-year time scale and for the long-term trend. Multivariate regression analysis confirmed that the climate change had greater influences on vegetation than that of anthropogenic activities in 50.8% of the study area, which distributed in the central area of the YZYRB.

Detecting Patterns of Vegetation Gradual Changes (2001–2017) in Shiyang River Basin, Based on a Novel Framework

A lot of timeseries satellite products have been well documented in exploring changes in ecosystems. However, algorithms allowing for measuring the directions, magnitudes, and timing of vegetation change, evaluating the major driving factors, and eventually predicting the future trends are still insufficient. A novel framework focusing on addressing this problem was proposed in this study according to the temporal trajectory of Normalized Difference Vegetation Index (NDVI) timeseries of Moderate Resolution Imaging Spectroradiometer (MODIS). It divided the inter-annual changes in vegetation into four patterns: linear, exponential, logarithmic, and logistic. All the three non-linear patterns were differentiated automatically by fitting a logistic function with prolonged NDVI timeseries. Finally, features of vegetation changes including where, when and how, were evaluated by the parameters in the logistic function. Our results showed that 87.39% of vegetation covered areas (maximum mean growing season NDVI in the 17 years not less than 0.2) in the Shiyng River basin experienced significant changes during 2001–2017. The linear pattern, exponential pattern, logarithmic pattern, and logistic pattern accounted for 36.53%, 20.16%, 15.42%, and 15.27%, respectively. Increasing trends were dominant in all the patterns. The spatial distribution in both the patterns and the transition years at which vegetation gains/losses began or ended is of high consistency. The main years of transition for the exponential increasing pattern, the logarithmic increasing pattern, and the logarithmic increasing pattern were 2008–2011, 2003–2004, and 2009–2010, respectively. The period of 2006–2008 was the foremost period that NDVIs started to decline in Liangzhou Oasis and Minqin Oasis where almost all the decreasing patterns were concentrated. Potential disturbances of vegetation gradual changes in the basin are refer to as urbanization, expansion or reduction of agricultural oases, as well as measures in ecological projects, such as greenhouses building, afforestation, grazing prohibition, etc.

Crop Growth Condition Assessment at County Scale Based on Heat-Aligned Growth Stages

Remotely sensed data have been used in crop condition monitoring for decades. Traditionally, crop growth conditions were assessed by comparing Normalized Difference Vegetation Index (NDVI) of the current year and past years at a pixel scale on the same calendar day. The assumption of this comparison is that the different years’ crops were at the same growing stage on the same day. However, this assumption is often violated in reality. This paper proposes to combine remotely sensed data and meteorological data to assess corn growth conditions at the same growth stages at county level. The proposed approach uses the active accumulated temperature (AAT) computed from Daymet, a daily weather data product, to align different years of NDVI time series at the same growth stages estimated from AATs. The study area covers Carroll County, Iowa. The best index slope extraction (BISE) method and Savitzky–Golay filter are used to filter noise and to reconstruct 11 years of corn growing season NDVI time series from 250 m MODIS daily surface reflectance data product (MOD09GQ). The corn growth stages are identified every year with precise Julian dates from AAT time series. The corn growth conditions are assessed based on the aligned growth stages. The validation of the assessed crop conditions is performed based on National Agricultural Statistics Service (NASS) reports. The study indicates that the crop condition assessment results based on aligned growth stages are consistent with the NASS reported results and they are more reliable than the results based on the same calendar days. The proposed method provides not only crop growth condition information but also crop phenology information. Potentially, it can help improve crop yield prediction since it can effectively measure crop growth changes with NDVI and AAT data.

Greening Implication Inferred from Vegetation Dynamics Interacted with Climate Change and Human Activities over the Southeast Qinghai–Tibet Plateau

Vegetation dynamics are sensitive to climate change and human activities, as vegetation interacts with the hydrosphere, atmosphere, and biosphere. The Yarlung Zangbo River (YZR) basin, with the vulnerable ecological environment, has experienced a series of natural disasters since the new millennium. Therefore, in this study, the vegetation dynamic variations and their associated responses to environmental changes in the YZR basin were investigated based on Normalized Difference Vegetation Index (NDVI) and Global Land Data Assimilation System (GLDAS) data from 2000 to 2016. Results showed that (1) the YZR basin showed an obvious vegetation greening process with a significant increase of the growing season NDVI (Zc = 2.31, p < 0.05), which was mainly attributed to the wide greening tendency of the downstream region that accounted for over 50% area of the YZR basin. (2) Regions with significant greening accounted for 25.4% of the basin and were mainly concentrated in the Nyang River and Parlung Tsangpo River sub-basins. On the contrary, the browning regions accounted for <25% of the basin and were mostly distributed in the urbanized cities of the midstream, implying a significant influence of human activities on vegetation greening. (3) The elevation dependency of the vegetation in the YZR basin was significant, showing that the vegetation of the low-altitude regions was better than that of the high-altitude regions. The greening rate exhibited a significantly more complicated relationship with the elevation, which increased with elevated altitude (above 3500 m) and decreased with elevated altitude (below 3500 m). (4) Significantly positive correlations between the growing season NDVI and surface air temperature were detected, which were mainly distributed in the snow-dominated sub-basins, indicating that glaciers and snow melting processes induced by global warming play an important role in vegetation growth. Although basin-wide non-significant negative correlations were found between precipitation and growing season NDVI, positive influences of precipitation on vegetation greening occurred in the arid and semi-arid upstream region. These findings could provide important information for ecological environment protection in the YZR basin and other high mountain regions.

Vegetation change in response to climate factors and human activities on the Mongolian Plateau.

BackgroundVegetation in the Mongolian Plateau is very sensitive to climate change, which has a significant impact on the regulation of terrestrial carbon cycle.MethodsWe analyzed spatio-temporal changes of both growing season and the seasonal Normalized Difference Vegetation Index (NDVI) using simple linear trend analysis. Besides, correlation analysis was applied to explore the climate factors’ effects on vegetation growth at temporal and spatial scale. Potential effects of human factors on vegetation growth were also explored by residual trend analysis.ResultsThe results indicated that vegetation growth showed a greening trend in the Mongolian Plateau over the past 30 years. At the temporal scale, the growing season NDVI showed an insignificant increasing trend (at a rate of 0.0003 yr−1). At the spatial scale, a large region (53.8% of the whole Mongolian Plateau) with an increasing growing season NDVI, was primarily located in the southern and northern parts of the plateau. The correlation analysis suggested that temperature and precipitation were the main limiting factors that affected vegetation growth in spring and the growing season, respectively. The residual trend analysis showed that human activities primarily stimulated the growth of grasslands and shrublands, while croplands displayed a decreasing trend due to human disturbances, implying that anthropogenic factors may lead to croplands abandonment in favor of grasslands restoration. Our results provided detailed spatial and temporal changes of vegetation growth, and explored how climate and human factors affected vegetation growth, which may offer baseline data and scientific suggestions for local land and resources management, and facilitate the sustainable development of the terrestrial ecosystems.

Long-Term Declining Trends in Chihuahuan Desert Forage Production in Relation to Precipitation and Ambient Temperature

Rising temperatures and more frequent droughts are posing new challenges to range livestock producers in the southwestern United States and many other parts of the world. We analyzed a 52-yr time series (1967−2018) of precipitation, ambient temperature, and perennial grass production (PGP), as well as 14 yr (2001−2014) of Moderate Resolution Imaging Spectrometer (MODIS)-derived vegetation phenometrics at a site in the Chihuahuan Desert of New Mexico. PGP was positively associated with December through September precipitation (r = 0.69; P < 0.01) but negatively associated with spring and summer (May−September) maximum average ambient temperature (r = −0.47; P < 0.01). PGP decreased by 43% in the second (1993−2018) compared with the first half (1967−1992) of our study (165 vs. 94 kg dry matter • ha−1; P < 0.01). Precipitation was lower and more erratic in the second half of the time series, decreasing by 18.6% (265.2 ± 15.0 vs. 215.8 ± 15.8 mm; P = 0.01). Conversely, mean maximum and mean ambient temperatures were higher during the 1993−2018 period (max T: 24.5 ± 0.1 vs. 25.3 ± 0.1°C; P < 0.01; mean T:14.4 ± 0.1 vs. 15.3 ± 0.2°C; P < 0.01). MODIS-derived Normalized Difference Vegetation Index (NDVI) analysis showed that growing seasons began and ended later and became shorter (P < 0.05) over the 14 yr analyzed. During this period, increasing maximum spring and summer (May−September) ambient temperatures were associated with decreasing growing season NDVI values (P < 0.01). Over the 52-yr study period, Chihuahuan Desert rangelands at our research site lost 43% of grazing capacity based on PGP. Nine drought yr occurred in the second half of our study compared with 2 yr in the first half. Our research supports predictions by climate scientists that higher temperatures, more frequent droughts, and lower, as well as more erratic, precipitation will adversely impact grazing capacity of rangelands in the southwestern United States.

Changes in Vegetation Cover of Yellowstone National Park Estimated from MODIS Greenness Trends, 2000 to 2018

Trends and transitions in the MODerate resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series at 250-m resolution were analyzed for the period from 2000 to 2018 to understand recent patterns of vegetation change in Yellowstone National Park (USA). Statistical change in the NDVI time series was detected using the “Breaks for Additive Seasonal and Trend” (BFAST) method. This structural change analysis showed that around 30% of abrupt negative shifts in NDVI over the years 2000 to 2018 could be explained by the impacts of recent wildfires. At least one breakpoint could be detected at 12% of the 250-m MODIS pixel locations within the entire YNP study area since the year 2000, but that the majority (about 70%) of NDVI breakpoints detected in vegetation greenness could be not be explained by the impacts of recent wildfires. Positive growing season NDVI trends were detected across most young forests and regrowing (from recent fire disturbance) woodland cover. Evidence further suggested that the 1988 wildfire burns did not pre-dispose vegetation cover in YNP to a higher number of abrupt negative shifts in NDVI since the year 2000. The wildfires of 1988 were associated with significantly higher NDVI recovery trends over the recent 18-year MODIS time series, compared to areas unburned in 1988. Locations on the Northern Range that showed the highest greening trends since 2000 were commonly located in sagebrush steppe-dominated vegetation communities growing at lower than 2500 m elevation. Results from NDVI trend analysis supported the hypothesis that years with relatively high snowpack water content, such as 2007–2008 and 2010–2011, were most closely associated with abrupt negative shifts in NDVI, but no findings strongly supported the supposition that vegetation cover in YNP is changing in greenness in association solely with warming in surface air temperatures or with extreme drought periods across the study region over the past two decades.

Spatial heterogeneity of changes in vegetation growth and their driving forces based on satellite observations of the Yarlung Zangbo River Basin in the Tibetan Plateau

Changes in vegetation growth may influence the availability of water resources. Located on the Tibetan Plateau, the Yarlung Zangbo River Basin (YZRB) is a major freshwater source for Tibet, China and downstream South Asian countries, with high spatial heterogeneity in altitude and climate from the upstream to downstream regions. In this study, we combined satellite-based gridded datasets of the normalized difference vegetation index (NDVI), topography, precipitation, and temperature to investigate how vegetation growth has changed in the YZRB over recent decades (1982–2010), and to determine their driving mechanisms. Although a statistically significant trend in growing season NDVI was not detected at the basin scale, at the pixel scale 16.8% and 5.3% of the area of the YZRB was found to exhibit increasing and decreasing trends, respectively. The greatest increases occurred in the Nyang subbasin. Variations of NDVI values along elevation, precipitation, and temperature gradients revealed the greatest variation over the middle ranges of the three variables. Partial correlation analyses indicate that in both arid and semi-arid regions of the YZRB precipitation is positively correlated with NDVI. The relationship between NDVI and temperature varies with aridity, reflecting different effects of snow-melting processes on vegetation growth. Temperature positively correlates with NDVI in the arid region. In addition, a negative correlation between NDVI and temperature is detected in the semi-arid region. This is the first comprehensive study to explore climate–vegetation–hydrology relationships in the YZRB at a spatial resolution finer than those derived from sparse in-situ meteorological stations or low resolution global climate datasets. Our results are valuable for understanding ecohydrological processes in both arid and semi-arid regions of this internationally important river basin.

Changes in Vegetation Cover of the Arctic National Wildlife Refuge Estimated from MODIS Greenness Trends, 2000–18

Abstract Trends and transitions in the growing-season normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor at 250-m resolution were analyzed for the period from 2000 to 2018 to understand recent patterns of vegetation change in ecosystems of the Arctic National Wildlife Refuge (ANWR) in Alaska. Statistical analysis of changes in the NDVI time series was conducted using the breaks for additive seasonal and trend method (BFAST). This structural change analysis indicated that NDVI breakpoints and negative 18-yr trends in vegetation greenness over the years since 2000 could be explained in large part by the impacts of severe wildfires. At least one NDVI breakpoint was detected in around 20% of the MODIS pixels within both the Porcupine River and Coleen River basins of the study area. The vast majority of vegetation cover in the ANWR Brooks Range and coastal plain ecoregions was detected with no (positive or negative) growing-season NDVI trends since the year 2000. Results suggested that most negative NDVI anomalies in the 18-yr MODIS record have been associated with early spring thawing and elevated levels of surface moisture in low-elevation drainages of the northern ANWR ecoregions.

Spatio-Temporal Analysis of Vegetation Dynamics as a Response to Climate Variability and Drought Patterns in the Semiarid Region, Eritrea

There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p &lt; 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services.

NDVI anomaly for drought monitoring and its correlation with climate factors over Mongolia from 2000 to 2016

Drought is a frequent phenomenon of Mongolia in the last 17 years. The imbalance between the potential evaporation and precipitation amount during the growing season usually causes drought condition which may pose a threat to the environment and human activities. Therefore, gathering a frequent information about the drought severity and its spatial and temporal distribution is required for drought effects mitigation. In this study, the drought severity and its spatial distribution over Mongolia have been mapped, based on the normalized difference vegetation index (NDVI) anomaly during the growing season for 2000 to 2016. The results indicated that Mongolia experienced mild to severe drought during the 17 years and the extremely affected years were 2001, 2007, 2002, 2005, 2004, 2009 and 2006 respectively when 41%–57% of the country was under mild to severe drought conditions. The temporal correlation analysis indicated that growing season NDVI anomaly variation was correlated with both climatic variables, but slightly more significantly correlated with precipitation anomaly (r = 0.46, p < 0.005) than temperature anomaly (r = −0.40, p < 0.005). Meanwhile, the analysis of the spatial correlation between NDVI anomaly and two climatic variables varied according to the land cover type and plants growth environments.

Impacts of Chinese Grain for Green program and climate change on vegetation in the Loess Plateau during 1982–2015

Remote sensing based vegetation index provides a practical method for the monitoring of vegetation dynamics at regional and global scales. Here, using a long-term remotely sensed normalized difference vegetation index (NDVI) dataset, we quantified the vegetation changes in the Loess Plateau (LP) over the last three decades (1982–2015), which includes the period before the Chinese“Grain for Green Program”(GGP) was launched (1982–1999), and the period after the GGP (1999–2015). The correlations between the NDVI and four climate related variables, i.e., precipitation, temperature, root-soil moisture (RSM), and a drought proxy-standardized evapotranspiration deficit index (SEDI), were also examined. The results indicated that, (i) the GGP strongly changed the vegetation in the LP. The growing-season mean NDVI (GSM-NDVI) and the annual mean NDVI (AM-NDVI) decreased slightly before the GGP launched in 1999, with slopes of −3.38×10−3 and−8.00×10−4year−1, respectively. However, they showed slight and significant (p<0.05) increases after the GGP, with slopes of 4.75×10−3 and 2.32×10−3year−1, respectively. (ii) Climate change (i.e., warming and drying) resulted in adverse effects on vegetation in the LP during the period before the GGP. However, the observed changes (i.e., wetting and reduced drought) exerted positive effects on the vegetation during the period after the GGP. (iii) Inter-annual variations of spatially averaged NDVI over the LP were primarily determined by RSM rather than any other climate related variables. In the southeastern LP, the inter-annual variation of GSM-NDVI was mainly determined by precipitation and SEDI, while the inter-annual variation of AM-NDVI was mainly caused by SEDI and RSM. Inter-annual variations of both GSM-NDVI and AM-NDVI were mainly determined by SEDI and RSM in the northwestern LP, and by temperature in the southwestern LP.

Spatiotemporal Patterns of Vegetation Greenness Change and Associated Climatic and Anthropogenic Drivers on the Tibetan Plateau during 2000–2015

Alpine vegetation on the Tibetan Plateau (TP) is known to be sensitive to both climate change and anthropogenic disturbance. However, the magnitude and patterns of alpine vegetation dynamics and the driving mechanisms behind their variation on the TP remains under debate. In this study, we used updated MODIS Collection 6 Normalized Difference Vegetation Index (NDVI) from the Terra satellite combined with linear regression and the Break for Additive Season and Trend model to reanalyze the spatiotemporal patterns of vegetation change on the TP during 2000–2015. We then quantified the responses of vegetation variation to climatic and anthropogenic factors by coupling climatic and human footprint datasets. Results show that growing season NDVI (GNDVI) values increased significantly overall (0.0011 year−1, p &lt; 0.01) during 2000–2015 and that 70.37% of vegetated area on the TP (23.47% significantly with p &lt; 0.05) exhibited greening trends with the exception of the southwest TP. However, vegetation greenness experienced trend shifts from greening to browning in half of the ecosystem zones occurred around 2010, likely induced by spatially heterogeneous temporal trends of climate variables. The vegetation changes in the northeastern and southwestern TP were water limited, the mid-eastern TP exhibited strong temperature responses, and the south of TP was driven by a combination of temperature and solar radiation. Furthermore, we found that, to some extent, anthropogenic disturbances offset climate-driven vegetation greening and aggravated vegetation browning induced by water deficit. These findings suggest that the impact of anthropogenic activities on vegetation change might not overwhelm that of climate change at the region scale.

NDVI-based vegetation dynamics and its response to climate changes at Amur-Heilongjiang River Basin from 1982 to 2015

Vegetation in Northern Hemisphere, being sensitive to climate change, plays an important role in the carbon cycles between land and the atmosphere. The response of vegetation to climate change was analyzed at pixel, biome and regional scale in Amur-Heilongjiang River Basin (AHRB) for growing season, spring, summer and autumn using Normalized Difference Vegetation Index and gridded climate data for the period 1982–2015. NDVI and climate variables trend detection methods and correlation analysis were applied. The potential impacts of human activities on growing season NDVI dynamics were investigated further using residual trend analysis. Results showed that at river basin scale, growing season vegetation experienced a discontinuous greening trend with two reversals, demonstrating that NDVI initially increased to mid-1990s, then declined to mid-2000s, and finally rebounded to 2015. This may be attributed to the shifting between drought and wet trends, indicating growing season NDVI was mainly regulated by precipitation. Temperature was the dominant factor on affecting spring vegetation growth while autumn NDVI showed negative correlation with precipitation due to the relation of precipitation with sunshine hours available for photosynthesis. The response of vegetation growth to climatic variations varied among vegetation types. Grassland NDVI exhibited positive correlation with precipitation in all time ranges. NDVI of needleleaved forest, broadleaved forest, mixed forest and woodland were positively correlated with temperature in all seasons, while showing significant negative correlation with autumn precipitation. Residual trend analysis revealed that human activities might lead to the vegetation degradation in China farming zone of AHRB. Fires also play an important role in regulating vegetation dynamics in the region. Results of our analysis can be used by national governments from three countries of AHRB in managing and negotiating vegetation resources of the region.