Trends In Vegetation Greenness Research Articles

Long-term trend of and correlation between vegetation greenness and climate variables in Asia based on satellite data

Satellite data has been used to ascertain trends and correlations between climate change and vegetation greenness in Asia. Our study utilized 33-year (1982–2014) AVHRR-GIMMS (Advanced Very High Resolution Radiometer–Global Inventory Modelling and Mapping Studies) NDVI3g and CRU TS (Climatic Research Unit Time Series) climate variable (temperature, rainfall, and potential evapotranspiration) time series. First, we estimated the overall trends for vegetation greenness and climate variables and analyzed trends during summer (April–October), winter (November–March), and the entire year. Second, we carried out correlation and regression analyses to detect correlations between vegetation greenness and climate variables. Our study revealed an increasing trend (0.05–0.28) in temperature in northeastern India (bordering Bhutan), Southeast Bhutan, Yunnan Province of China, Northern Myanmar, Central Cambodia, northern Laos, southern Vietnam, eastern Iran, southern Afghanistan, and southern Pakistan. However, a decreasing trend in temperature (0.00 to -0.04) was noted for specific areas in southern Asia including Central Myanmar and northwestern Thailand and the Guangxi, Southern Gansu, and Shandong provinces of China. The results also indicated an increasing trend for evapotranspiration and air temperature accompanied by a decreasing trend for vegetation greenness and rainfall. Increases in both the mean annual signal and annual cycle occurred in the forest, herbaceous, and cropland areas of India, Northwest China, and eastern Kazakhstan. The temperature was found to be the main driver of the changing vegetation greenness in Kazakhstan, northern Mongolia, Northeast and Central China, North Korea, South Korea, and northern Japan, showing an indirect relationship (R?=?0.84–0.96).•Temperature is the main climatic variable affecting vegetation greenness.•A downward trend in vegetation greenness was observed during summer (April–October).•Temperature showed an upward trend across many areas of Asia during the study period.•In winter, rainfall showed downward and upward trends in different parts of Asia.

Examining Land Cover and Greenness Dynamics in Hangzhou Bay in 1985–2016 Using Landsat Time-Series Data

Land cover changes significantly influence vegetation greenness in different regions. Dense Landsat time series stacks provide unique opportunity to analyze land cover change and vegetation greenness trends at finer spatial scale. In the past three decades, large reclamation activities have greatly changed land cover and vegetation growth of coastal areas. However, rarely has research investigated these frequently changed coastal areas. In this study, Landsat Normalized Difference Vegetation Index time series (1984–2016) data and the Breaks For Additive Seasonal and Trend algorithm were used to detect the intensity and dates of abrupt changes in a typical coastal area—Hangzhou Bay, China. The prior and posterior land cover categories of each change were classified using phenology information through a Random Forest model. The impacts of land cover change on vegetation greenness trends of the inland and reclaimed areas were analyzed through distinguishing gradual and abrupt changes. The results showed that the intensity and date of land cover change were detected successfully with overall accuracies of 88.7% and 86.1%, respectively. The continuous land cover dynamics were retrieved accurately with an overall accuracy of 91.0% for ten land cover classifications. Coastal reclamation did not alleviate local cropland occupation, but prompted the vegetation greenness of the reclaimed area. Most of the inland area showed a browning trend. The main contributors to the greenness and browning trends were also quantified. These findings will help the natural resource management community generate better understanding of coastal reclamation and make better management decisions.

Vegetation Greening Trends at Two Sites in the Canadian Arctic: 1984–2015

ABSTRACTThis study examined vegetation greening at two arctic sites: the Apex River Watershed (ARW), Baffin Island, Nunavut (a Low Arctic site) and the Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, Nunavut (a High Arctic site). The vegetation at both study sites was characterized using a supervised land-cover classification approach using high spatial resolution satellite remote sensing data (i.e., IKONOS [4 m] and WorldView-2 [2 m]). Meanwhile, Normalized Difference Vegetation Index (NDVI) data spanning the past 30 years were derived from intermediate spatial resolution data (i.e., Landsat TM/ETM/OLI [30 m]). The land-cover classifications were used to partition the Landsat NDVI time series by vegetation type. Climate variables (i.e., temperature, precipitation, and growing season length [GSL]) were examined to explore potential relationships of NDVI to climate warming trends. The results of the land-cover classifications demonstrated inherent trends of vegetation types along elevation and moisture gradients. The NDVI time series for the CBAWO (1985–2015) demonstrated an overall significant increase in greening, specifically in the dry and mesic vegetation types. Conversely, similar greening (overall or by vegetation type) was not observed for the ARW (1984–2015). Based on climate data from the nearest permanent weather station (Mould Bay, Nunavut), the overall increase in NDVI at the CBAWO was largely attributed to a significant increase in July temperatures and GSL.

Elevation‐dependent effects of climate change on vegetation greenness in the high mountains of southwest China during 1982–2013

ABSTRACTEffects of climate change on vegetation greenness have attracted considerable attention in the context of global change; however, the dependence of such climatic effects on elevation remains poorly understood. In this study, we examine the relationship between vegetation greenness change and climate change and, in particular, characterize how this relationship changes with elevation in the high mountains of southwest China by using the remotely sensed normalized difference vegetation index (NDVI), and observed temperature and precipitation data sets for the period of 1982–2013. The results show that vegetation exhibited a greening trend (slope: 0.0008 year−1, p < 0.01) under climate warming (slope: 0.04 °C year−1, p < 0.01) and drying (slope: −2.47 mm year−1, p > 0.05). The vegetation greening and climate warming trends were stronger in the higher elevation plateaus than in the lower elevation mountains. Statistical analysis showed that temperature was the main driving factor on vegetation greening, and the driving effect was elevation‐dependent. A substantially more significant correlation between climate warming and vegetation greening was found in the higher elevation plateaus, which reveals a higher temperature sensitivity of these plateaus. In addition, a significant correlation between inter‐annual standard deviations of NDVI and precipitation during 1982–2013 was tracked over the entire study area.

Variation in vegetation greenness along China’s land border

Fourteen countries share about 22000 km land border with China, but not much is known about the variation in vegetation in such a large diverse area. By employing the remotely-sensed vegetation indices the vegetation greenness along the border was discussed. Our results show that since the early 21st century, similar trends in vegetation greenness have occurred along most of China’s border, but differences occurred on either side of the border. Along the border with North Korea and South Asian nations, greater increasing trend in vegetation greenness occurred inside China’s border, suggesting that China’s vegetation protection programs have been successful. Spatial and temporal variations in vegetation greenness trends were observed along China’s border with Russia, Mongolia, and Central Asian nations. Vegetation variation was lower inside China, along the Russian border, and China’s eastern border with Mongolia. Along most borders with Central Asian nations, rates of vegetation change inside China’s border during the growing season were higher than the rates outside the border. The results suggest that social customs, resource exploitation patterns, and national environmental conservation programs may profoundly affect vegetation greenness.

Inter-Annual Vegetation Changes in Response to Climate Variability in Rwanda

Comprehensive studies on how vegetative ecosystems respond to fluctuations in precipitation and temperature patterns are of great necessity for environmental risk assessment and land-use evaluations. The present study examined the annual trends in vegetation greenness in Rwanda from 2000-2015 and assessed the relationship between these dynamics and climate factors by means of MODIS NDVI, air temperature, SOI and precipitation datasets. Mann Kendal trend test has been utilized to determine the direction and the rates of changes, while Spearman’s rank correlation method has been used to determine the levels of associability between NDVI changes and climatic variables. The results indicate that approximately 11.9% of the country’s vegetation has significantly improved (р < 0.05) from slight to significant improvement while 10.4% of the vegetative cover degraded from slight to severe degradation and an estimated 77.6% of the country’s vegetation cover has remained relatively stable. Much of improvement has been detected in the lowlands of eastern province whereas much of degradation has been highlighted in the western highlands of the Congo Nile ridge and Kigali city. There was a weak correlation between NDVI anomalies and SOI anomalies (rs = 0.36) while near surface air temperature was moderately correlated (rs = 0.47) with changes in Mean NDVI. Precipitation was more significantly associated (r = 0.84) with changes in vegetation health in low plains of Eastern Province (Nyagatare District in particular) than in the high altitude regions of the Congo Nile ridge. A strong positive correlation with precipitation was found in rain fed croplands; mosaic vegetation; mosaic forest or shrubland, herbaceous vegetation/grass-land savannah and sparse vegetation. Identification of degradation hotspots could significantly help the government and local authorities galvanize efforts and foster results driven policies of environmental protection and regeneration countrywide.

Vegetation Dynamics in the Upper Guinean Forest Region of West Africa from 2001 to 2015

The Upper Guinea Forest (UGF) region of West Africa is one of the most climatically marginal and human-impacted tropical forest regions in the world. Research on the patterns and drivers of vegetation change is critical for developing strategies to sustain ecosystem services in the region and to understand how climate and land use change will affect other tropical forests around the globe. We compared six spectral indices calculated from the 2001–2015 MODIS optical-infrared reflectance data with manually-interpreted measurements of woody vegetation cover from high resolution imagery. The tasseled cap wetness (TCW) index was found to have the strongest association with woody vegetation cover, whereas greenness indices, such as the enhanced vegetation index (EVI), had relatively weak associations with woody cover. Trends in woody vegetation cover measured with the TCW index were analyzed using Mann–Kendall statistics and were contrasted with trends in vegetation greenness measured with EVI. In the drier West Sudanian Savanna and Guinean Forest-Savanna Mosaic ecoregions, EVI trends were primarily positive, and TCW trends were primarily negative, suggesting that woody vegetation cover was decreasing, while herbaceous vegetation cover is increasing. In the wettest tropical forests in the Western Guinean Lowland Forest ecoregion, declining trends in both TCW and EVI were indicative of widespread forest degradation resulting from human activities. Across all ecoregions, declines in woody cover were less prevalent in protected areas where human activities were restricted. Multiple lines of evidence suggested that human land use and resource extraction, rather than climate trends or short-term climatic anomalies, were the predominant drivers of recent vegetation change in the UGF region of West Africa.

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of increasing vegetation greenness particularly afforestation on the hydrological cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China’s land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation ‘greening’ and ‘browning’ on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield, while vegetation browning reduced ET and increased water yield. At the large river basin and national scales, the greening trends also had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the changes in vegetation greenness on the hydrological cycle varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrological cycle are needed to account for the feedbacks to the climate.

Impact of Climate Change on Vegetation Growth in Arid Northwest of China from 1982 to 2011

Previous studies have concluded that the increase in vegetation in the arid northwest of China is related to precipitation rather than temperature. However, these studies neglected the effects of climate warming on water availability that arise through changes in the melting characteristics of this snowy and glaciated region. Here, we characterized vegetation changes using the newly improved third-generation Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS-3g NDVI) from 1982 to 2011. We analyzed the temperature and precipitation trends based on data from 51 meteorological stations across Northwest China and investigated changes in the glaciers using Gravity Recovery and Climate Experiment (GRACE) data. Our results indicated an increasing trend in vegetation greenness in Northwest China, and this increasing trend was mostly associated with increasing winter precipitation and summer temperature. We found that the mean annual temperature increased at a rate of 0.04 °C per year over the past 30 years, which induced rapid glacial melting. The total water storage measured by GRACE decreased by up to 8 mm yr−1 and primarily corresponded to the disappearance of glaciers. Considering the absence of any observed increase in precipitation in the growing season, the vegetation growth may have benefited from the melting of glaciers in high-elevation mountains (i.e., the Tianshan Mountains). Multiple regression analysis showed that temperature was positively correlated with NDVI and that gravity was negatively correlated with NDVI; together, these variables explained 84% of the NDVI variation. Our findings suggest that both winter precipitation and warming-induced glacial melting increased water availability to the arid vegetation in this region, resulting in enhanced greenness.

Elevated CO₂ as a driver of global dryland greening.

While recent findings based on satellite records indicate a positive trend in vegetation greenness over global drylands, the reasons remain elusive. We hypothesize that enhanced levels of atmospheric CO2 play an important role in the observed greening through the CO2 effect on plant water savings and consequent available soil water increases. Meta-analytic techniques were used to compare soil water content under ambient and elevated CO2 treatments across a range of climate regimes, vegetation types, soil textures and land management practices. Based on 1705 field measurements from 21 distinct sites, a consistent and statistically significant increase in the availability of soil water (11%) was observed under elevated CO2 treatments in both drylands and non-drylands, with a statistically stronger response over drylands (17% vs. 9%). Given the inherent water limitation in drylands, it is suggested that the additional soil water availability is a likely driver of observed increases in vegetation greenness.

Trends and climatic sensitivities of vegetation phenology in semiarid and arid ecosystems in the US Great Basin during 1982–2011

Abstract. We quantified the temporal trend and climatic sensitivity of vegetation phenology in dryland ecosystems in the US Great Basin during 1982–2011. Our results indicated that vegetation greenness in the Great Basin increased significantly during the study period, and this positive trend occurred in autumn but not in spring and summer. Spatially, increases in vegetation greenness were more apparent in the northwestern, southeastern, and eastern Great Basin but less apparent in the central and southwestern Great Basin. In addition, the start of growing season (SOS) was not advanced while the end of growing season (EOS) was delayed significantly at a rate of 3.0 days per decade during the study period. The significant delay in EOS and lack of earlier leaf onset caused growing season length (GSL) to increase at a rate of 3.0 days per decade. Interestingly, we found that the interannual variation of mean vegetation greenness calculated for the period of March to November (spring, summer, and autumn – SSA) was not significantly correlated with mean surface air temperature in SSA but was strongly correlated with total precipitation. On a seasonal basis, the variation of mean vegetation greenness in spring, summer, and autumn was mainly attributable to changes in pre-season precipitation in winter and spring. Nevertheless, climate warming appeared to play a strong role in extending GSL that, in turn, resulted in the upward trend in mean vegetation greenness. Overall, our results suggest that changes in wintertime and springtime precipitation played a stronger role than temperature in affecting the interannual variability of vegetation greenness, while climate warming was mainly responsible for the upward trend in vegetation greenness we observed in Great Basin dryland ecosystems during the 30-year period from 1982 to 2011.

Evapotranspiration in the Nile Basin: Identifying Dynamics and Drivers, 2002–2011

Analysis of the relationship between evapotranspiration (ET) and its natural and anthropogenic drivers is critical in water-limited basins such as the Nile. The spatiotemporal relationships of ET with rainfall and vegetation dynamics in the Nile Basin during 2002–2011 were analyzed using satellite-derived data. Non-parametric statistics were used to quantify ET-rainfall interactions and trends across land cover types and subbasins. We found that 65% of the study area (2.5 million km2) showed significant (p &lt; 0.05) positive correlations between monthly ET and rainfall, whereas 7% showed significant negative correlations. As expected, positive ET-rainfall correlations were observed over natural vegetation, mixed croplands/natural vegetation, and croplands, with a few subbasin-specific exceptions. In particular, irrigated croplands, wetlands and some forests exhibited negative correlations. Trend tests revealed spatial clusters of statistically significant trends in ET (6% of study area was negative; 12% positive), vegetation greenness (24% negative; 12% positive) and rainfall (11% negative; 1% positive) during 2002–2011. The Nile Delta, Ethiopian highlands and central Uganda regions showed decline in ET while central parts of Sudan, South Sudan, southwestern Ethiopia and northeastern Uganda showed increases. Except for a decline in ET in central Uganda, the detected changes in ET (both positive and negative) were not associated with corresponding changes in rainfall. Detected declines in ET in the Nile delta and Ethiopian highlands were found to be attributable to anthropogenic land degradation, while the ET decline in central Uganda is likely caused by rainfall reduction.

MODIS derived vegetation greenness trends in African Savanna: Deconstructing and localizing the role of changing moisture availability, fire regime and anthropogenic impact

Abstract In African savanna, spatio-temporal variability in moisture availability, fire regime and land transformation related to exploitative land uses are the main drivers of changing vegetation greenness patterns. Deconstructing the role of these drivers at local scale is critical for managing the impact of projected climate and land use changes on savanna ecosystems. Focusing on an area encompassing Africa's largest terrestrial protected area, this study utilized time-series MODIS NDVI (2000–2014) and employed a robust trend analysis technique to detect significant temporal trend in key greenness metrics including overall greenness, peak and timing of the peak of annual greenness and examined how spatial variability in vegetation morphology and land use impacted the distribution of these greenness parameters. To access causation of change, we linked detected greenness trends to precipitation trends derived from Tropical Rainfall Measurement Mission (TRMM), annual burnt area extent and fire frequency and compared multi-temporal imagery in Google Earth. Results show that distribution of both overall and peak annual greenness was vegetation morphology specific as with decreasing woody cover the proportion of pixels showing negative overall and peak annual greenness trend increased consistently. Majority of the area with significant trend in the timing of the peak of annual greenness showed late greenup, implying changing phenological patterns. Trend analysis of TRMM derived mean annual precipitation showed no significant change in precipitation over the study period. At local scale, increase in overall and peak annual greenness was associated with woody plant encroachment due to increased moisture availability and reduced fire frequency due to construction of fire breaks in areas under farm/ranch land use. In protected areas, negative overall and peak annual greenness was driven by unmanaged high intensity mega fire events and outside due to anthropogenic land clearing for pastoral agriculture. These results further our understanding of the complex interaction of multiple ecological factors and resultant spatial variability in savanna inter-annual vegetation greenness patterns and are useful for implementing local scale management strategies.

Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel.

After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal.

Detection and attribution of vegetation greening trend in China over the last 30years.

The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite-derived Leaf Area Index (LAI) datasets for detection as well as five different process-based ecosystem models for attribution. Rising atmospheric CO2 concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing-season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr(-1), ranging from 0.0035 yr(-1) to 0.0127 yr(-1)), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai-Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.

A conceptual model for assessing rainfall and vegetation trends in sub‐Saharan Africa from satellite data

Policymakers, governments and aid agencies require operational environmental monitoring in support of evidence-based policy-making and resource deployment in crisis situations. For Africa, this is only feasible at sub-continental scale with a large network of automated meteorological stations, a large number of highly coordinated field observers or with satellite remote sensing. The challenge with satellite data lies in the derivation of meaningful environmental indicators. This article describes a conceptual framework for understanding satellite-derived indicators of rainfall and vegetation greenness trends over Africa. It attributes observed vegetation changes to climatic (i.e. rainfall linked) and non-climatic drivers. A decade of annual rainfall and vegetation data over sub-Saharan Africa was analysed using satellite-based rainfall estimates [Famine Early Warning System Rainfall Estimation 2.0 (FEWSNET RFE 2.0)] from National Oceanic and Atmospheric Administration's (NOAA's) Climate Prediction Centre and the Normalized Difference Vegetation Index (NDVI) obtained from the Satellite Pour l'Observation de la Terre Vegetation (SPOT-VGT) sensor. Rainfall and vegetation greenness trends were analysed for 759 administrative regions of sub-Saharan Africa to identify those regions that have experienced a negative, positive or stable rainfall/vegetation trend over the period 2001–2010. The character of the relationship between the annual rainfall and max NDVI trends were examined to identify areas where the changes in greenness could be attributed to climatic (rainfall) and non-climatic (human land use or ecological disturbance) changes. Regions where increasing rainfall was associated with vegetation greening were found in West Africa, Central African Republic, West Cameroon and northeastern part of South Africa, whereas areas with evidence of ‘climatic vegetation degradation’ were located in Southern Madagascar, Nigeria, Kenya and the Garden Route region of South Africa.

Vegetation Greenness in Northeastern Brazil and Its Relation to ENSO Warm Events

The spatio-temporal variability of trends in vegetation greenness in dryland areas is a well-documented phenomenon in remote sensing studies at global to regional scales. The underlying causes differ, however, and are often not well understood. Here, we analyzed the trends in vegetation greenness for a semi-arid area in northeastern Brazil (NEB) and examined the relationships between those dynamics and climate anomalies, namely the El Nino Southern Oscillation (ENSO) for the period 1982 to 2010, based on annual Normalized Difference Vegetation Index (NDVI) values from the latest version of the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI dataset (NDVI3g) dataset. Against the ample assumption of ecological and socio-economic research, the results of our inter-annual trend analysis of NDVI and precipitation indicate large areas of significant greening in the observation period. The spatial extent and strength of greening is a function of the prevalent land-cover type or biome in the study area. The regression analysis of ENSO indicators and NDVI anomalies reveals a close relation of ENSO warm events and periods of reduced vegetation greenness, with a temporal lag of 12 months. The spatial patterns of this relation vary in space and time. Thus, not every ENSO warm event is reflected in negative NDVI anomalies. Xeric shrublands (Caatinga) are more sensitive to ENSO teleconnections than other biomes in the study area.

Pan-Arctic Climate and Land Cover Trends Derived from Multi-Variate and Multi-Scale Analyses (1981–2012)

Arctic ecosystems have been afflicted by vast changes in recent decades. Changes in temperature, as well as precipitation, are having an impact on snow cover, vegetation productivity and coverage, vegetation seasonality, surface albedo, and permafrost dynamics. The coupled climate-vegetation change in the arctic is thought to be a positive feedback in the Earth system, which can potentially further accelerate global warming. This study focuses on the co-occurrence of temperature, precipitation, snow cover, and vegetation greenness trends between 1981 and 2012 in the pan-arctic region based on coarse resolution climate and remote sensing data, as well as ground stations. Precipitation significantly increased during summer and fall. Temperature had the strongest increase during the winter months (twice than during the summer months). The snow water equivalent had the highest trends during the transition seasons of the year. Vegetation greenness trends are characterized by a constant increase during the vegetation-growing period. High spatial resolution remote sensing data were utilized to map structural vegetation changes between 1973 and 2012 for a selected test region in Northern Siberia. An intensification of woody vegetation cover at the taiga-tundra transition area was found. The observed co-occurrence of climatic and ecosystem changes is an example of the multi-scale feedbacks in the arctic ecosystems.

Application of piecewise linear regression in the detection of vegetation greenness trends on the Tibetan Plateau

Vegetation plays an important role in regulating the climate system and terrestrial carbon cycle. In recent decades, numerous studies have focused on monitoring vegetation greenness changes at different scales with long-term remote-sensing data. Most previous studies adopted a monotonic linear regression approach (one-piece linear regression) to detect vegetation greenness trends at global and regional scales. However, the monotonic linear regression approach is limited in its ability to detect abrupt changes in vegetation greenness trends because non-monotonic phenomena may exist in these trends. This study applied a piecewise linear regression (PLR) method to detect the non-monotonic trends of vegetation greenness in the Tibetan Plateau from 1982 to 2006. The vegetation greenness was indicated by the normalized difference vegetation index (NDVI) data derived from Global Inventory Modelling and Mapping Studies (GIMMS) Advanced Very High Resolution Radiometer (AVHRR) data. The results implied that the PLR method could detect an abrupt change in the trend with a break point (i.e. the year when the vegetation greenness trend changed abruptly) mainly concentrated in 1989. We chose three typical regions to compare the PLR and monotonic linear regression approach for vegetation trend detection to verify the effectiveness of the PLR method. The PLR method can detect different trends during different periods, but the one-piece linear regression method can only detect monotonic trends. After comparing the results of the two methods for three climatic zones, we found that the greenness trend detected by PLR can be better explained by temperature and precipitation variations. Our results illustrate that the PLR method is superior to the one-piece linear regression method due to its ability to detect non-monotonic trends. It can, therefore, delineate vegetation greenness trends in detail and be applied to other, similar studies.

The long-term trends (1982–2006) in vegetation greenness of the alpine ecosystem in the Qinghai-Tibetan Plateau

The increased rate of annual temperature in the Qinghai-Tibetan Plateau exceeded all other areas of the same latitude in recent decades. The influence of the warming climate on the alpine ecosystem of the plateau was distinct. An analysis of alpine vegetation under changes in climatic conditions was conducted in this study. This was done through an examination of vegetation greenness and its relationship with climate variability using the Advanced Very High Resolution Radiometer satellite imagery and climate datasets. Vegetation in the plateau experienced a positive trend in greenness, with 18.0 % of the vegetated areas exhibiting significantly positive trends, which were primarily located in the eastern and southwestern parts of the plateau. In grasslands, 25.8 % of meadows and 14.1 % of steppes exhibited significant upward trends. In contrast, the broadleaf forests experienced a trend of degradation. Temperature, particularly summer temperature, was the primary factor promoting the vegetation growth in the plateau. The wetter and warmer climate in the east contributed to the favorable conditions for vegetation. The alpine meadow was mostly sensitive to temperature, while the steppes were sensitive to both temperature and precipitation. Although a warming climate was expected to be beneficial to vegetation growth in the alpine region, the rising temperature coupled with reduced precipitation in the south did not favor vegetation growth due to low humidity and poor soil moisture conditions.