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 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.

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 Combined Effects of Warming and Grazing on Rangeland Vegetation on the Qinghai-Tibet Plateau

2021 ◽  
Vol 9 ◽  
Author(s):  
Chen Chen ◽  
Tiejian Li ◽  
Bellie Sivakumar ◽  
Ashish Sharma ◽  
John D. Albertson ◽  
...  
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Probability Model ◽  
Tibet Plateau ◽  
Combined Effects ◽  
Negative Effects ◽  
Positive Effects ◽  
Grazing Effects ◽  
Qinghai Tibet Plateau

Climate warming has increased grassland productivity on the Qinghai-Tibet Plateau, while intensified grazing has brought increasing direct negative effects. To understand the effects of climate change and make sustainable management decisions, it is crucial to identify the combined effects. Here, we separate the grazing effects with a climate-driven probability model and elaborate scenario comparison, using the Normalized Difference Vegetation Index (NDVI) of the grassland on the Qinghai-Tibet Plateau. We show that grazing has positive effects on NDVI in the beginning and end of the growing season, and negative effects in the middle. Because of the positive effects, studies tend to underestimate and even ignore the grazing pressure under a warming climate. Moreover, the seasonality of grazing effects changes the NDVI-biomass relationship, influencing the assessment of climate change impacts. Therefore, the seasonality of grazing effects should be an important determinant in the response of grassland to warming in sustainability analysis.

scholarly journals Start of the Green Season and Normalized Difference Vegetation Index in Alaska’s Arctic National Parks

2021 ◽  
Vol 13 (13) ◽  
pp. 2554
Author(s):  
David K. Swanson
Keyword(s):  
National Parks ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Free Surfaces ◽  
Modis Ndvi ◽  
Curve Fit ◽  
Winter Snow ◽  
Systematic Sample ◽  
Low Levels ◽  
Northern Alaska

Daily Normalized Difference Vegetation Index (NDVI) values from the MODIS Aqua and Terra satellites were compared with on-the-ground camera observations at five locations in northern Alaska. Over half of the spring rise in NDVI was due to the transition from the snow-covered landscape to the snow-free surface prior to the deciduous leaf-out. In the fall after the green season, NDVI fluctuated between an intermediate level representing senesced vegetation and lower values representing clouds and intermittent snow, and then dropped to constant low levels after establishment of the permanent winter snow cover. The NDVI value of snow-free surfaces after fall leaf senescence was estimated from multi-year data using a 90th percentile smoothing spline curve fit to a plot of daily NDVI values vs. ordinal date. This curve typically showed a flat region of intermediate NDVI values in the fall that represent cloud- and snow-free days with senesced vegetation. This “fall plateau” was readily identified in a large systematic sample of MODIS NDVI values across the study area, in typical tundra, shrub, and boreal forest environments. The NDVI level of the fall plateau can be extrapolated to the spring rising leg of the annual NDVI curve to approximate the true start of green season.

scholarly journals Phenology-Based Residual Trend Analysis of MODIS-NDVI Time Series for Assessing Human-Induced Land Degradation

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3676 ◽  
Author(s):  
Hao Chen ◽  
Xiangnan Liu ◽  
Chao Ding ◽  
Fang Huang
Keyword(s):  
Trend Analysis ◽  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Practical Method ◽  
Large Area ◽  
Modis Ndvi ◽  
Daily Precipitation Data ◽  
Improved Model

Land degradation is a widespread environmental issue and an important factor in limiting sustainability. In this study, we aimed to improve the accuracy of monitoring human-induced land degradation by using phenological signal detection and residual trend analysis (RESTREND). We proposed an improved model for assessing land degradation named phenology-based RESTREND (P-RESTREND). This method quantifies the influence of precipitation on normalized difference vegetation index (NDVI) variation by using the bivariate linear regression between NDVI and precipitation in pre-growing season and growing season. The performances of RESTREND and P-RESTREND for discriminating land degradation caused by climate and human activities were compared based on vegetation-precipitation relationship. The test area is in Western Songnen Plain, Northeast China. It is a typical region with a large area of degraded drylands. The MODIS 8-day composite reflectance product and daily precipitation data during 2000–2015 were used. Our results showed that P-RESTREND was more effective in distinguishing different drivers of land degradation than the RESTREND. Degraded areas in the Songnen grasslands can be effectively detected by P-RESTREND. Therefore, this modified model can be regarded as a practical method for assessing human-induced land degradation.

scholarly journals Using satellite data to improve the leaf phenology of a global terrestrial biosphere model

2015 ◽  
Vol 12 (23) ◽  
pp. 7185-7208 ◽  
Author(s):  
N. MacBean ◽  
F. Maignan ◽  
P. Peylin ◽  
C. Bacour ◽  
F.-M. Bréon ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Terrestrial Biosphere ◽  
Modis Ndvi ◽  
Growing Season Length ◽  
Median Correlation ◽  
Temperate Deciduous ◽  
Correct Representation ◽  
Biosphere Model ◽  
Deciduous Plant

Abstract. Correct representation of seasonal leaf dynamics is crucial for terrestrial biosphere models (TBMs), but many such models cannot accurately reproduce observations of leaf onset and senescence. Here we optimised the phenology-related parameters of the ORCHIDEE TBM using satellite-derived Normalized Difference Vegetation Index data (MODIS NDVI v5) that are linearly related to the model fAPAR. We found the misfit between the observations and the model decreased after optimisation for all boreal and temperate deciduous plant functional types, primarily due to an earlier onset of leaf senescence. The model bias was only partially reduced for tropical deciduous trees and no improvement was seen for natural C4 grasses. Spatial validation demonstrated the generality of the posterior parameters for use in global simulations, with an increase in global median correlation of 0.56 to 0.67. The simulated global mean annual gross primary productivity (GPP) decreased by ~ 10 PgC yr−1 over the 1990–2010 period due to the substantially shortened growing season length (GSL – by up to 30 days in the Northern Hemisphere), thus reducing the positive bias and improving the seasonal dynamics of ORCHIDEE compared to independent data-based estimates. Finally, the optimisations led to changes in the strength and location of the trends in the simulated vegetation productivity as represented by the GSL and mean annual fraction of absorbed photosynthetically active radiation (fAPAR), suggesting care should be taken when using un-calibrated models in attribution studies. We suggest that the framework presented here can be applied for improving the phenology of all global TBMs.

scholarly journals Does EO NDVI seasonal metrics capture variations in species composition and biomass due to grazing in semi-arid grassland savannas?

2015 ◽  
Vol 12 (14) ◽  
pp. 4407-4419 ◽  
Author(s):  
J. L. Olsen ◽  
S. Miehe ◽  
P. Ceccato ◽  
R. Fensholt
Keyword(s):  
Time Series ◽  
Species Composition ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Grazing Intensity ◽  
Test Site ◽  
Grazing Pressure ◽  
Modis Ndvi ◽  
Coarse Resolution

Abstract. Most regional scale studies of vegetation in the Sahel have been based on Earth observation (EO) imagery due to the limited number of sites providing continuous and long term in situ meteorological and vegetation measurements. From a long time series of coarse resolution normalized difference vegetation index (NDVI) data a greening of the Sahel since the 1980s has been identified. However, it is poorly understood how commonly applied remote sensing techniques reflect the influence of extensive grazing (and changes in grazing pressure) on natural rangeland vegetation. This paper analyses the time series of Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI metrics by comparing it with data from the Widou Thiengoly test site in northern Senegal. Field data include grazing intensity, end of season standing biomass (ESSB) and species composition from sizeable areas suitable for comparison with moderate – coarse resolution satellite imagery. It is shown that sampling plots excluded from grazing have a different species composition characterized by a longer growth cycle as compared to plots under controlled grazing or communal grazing. Also substantially higher ESSB is observed for grazing exclosures as compared to grazed areas, substantially exceeding the amount of biomass expected to be ingested by livestock for this area. The seasonal integrated NDVI (NDVI small integral; capturing only the signal inherent to the growing season recurrent vegetation), derived using absolute thresholds to estimate start and end of growing seasons, is identified as the metric most strongly related to ESSB for all grazing regimes. However plot-pixel comparisons demonstrate how the NDVI/ESSB relationship changes due to grazing-induced variation in annual plant species composition and the NDVI values for grazed plots are only slightly lower than the values observed for the ungrazed plots. Hence, average ESSB in ungrazed plots since 2000 was 0.93 t ha−1, compared to 0.51 t ha−1 for plots subjected to controlled grazing and 0.49 t ha−1 for communally grazed plots, but the average integrated NDVI values for the same period were 1.56, 1.49, and 1.45 for ungrazed, controlled and communal, respectively, i.e. a much smaller difference. This indicates that a grazing-induced development towards less ESSB and shorter-cycled annual plants with reduced ability to turn additional water in wet years into biomass is not adequately captured by seasonal NDVI metrics.

scholarly journals Temporal and Spatial Variations in NDVI and Analysis of the Driving Factors in the Desertified Areas of Northern China From 1998 to 2015

2021 ◽  
Vol 9 ◽  
Author(s):  
Xuyang Wang ◽  
Yuqiang Li ◽  
XinYuan Wang ◽  
Yulin Li ◽  
Jie Lian ◽  
...  
Keyword(s):  
Ecological Restoration ◽  
Large Scale ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Northern China ◽  
Gobi Desert ◽  
Desert Grassland ◽  
Dune Stability ◽  
Mobile Dunes

China faces some of the most serious desertification in the world, leading to many problems. To solve them, large-scale ecological restoration projects were implemented. To assess their effectiveness, we analyzed normalized-difference vegetation index (NDVI) data derived from SPOT VEGETATION and gridded climate datasets from 1998 to 2015 to detect the degrees of desertification and the effects of human and climate drivers on vegetation dynamics. We found that NDVI of desertified areas generally decreased before 2000, then increased. The annual increase in NDVI was fixed dunes (0.0013) = semi-fixed dunes (0.0013) &gt; semi-mobile dunes (0.0012) &gt; gobi (gravel) desert (0.0011) &gt; mobile dunes (0.0003) &gt; saline–alkali land (0.0000). The proportions of the area of each desert type in which NDVI increased were fixed dunes (43.4%) &gt; semi-mobile dunes (39.7%) &gt; semi-fixed dunes (26.7%) &gt; saline–alkali land (23.1%) &gt; gobi desert (14.4%) &gt; mobile dunes (12.5%). Thus, the vegetation response to the restoration efforts increased as the initial dune stability increased. The proportion of the area where desertification was dominated by temperature (1.8%) was far less than the area dominated by precipitation (14.1%). However, 67.6% of the change was driven by non-climatic factors. The effectiveness of the ecological restoration projects was significant in the Loess Plateau and in the Mu Us, Horqin, and Hulunbuir sandy lands. In contrast, there was little effect in the Badain Jaran, Ulan Buh, and Tengger deserts; in particular, vegetation cover has declined seriously in the Hunshandake Sandy Land and Alkin Desert Grassland. Thus, more or different ecological restoration must be implemented in these areas.

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