NDVI Variation and Its Responses to Climate Change on the Northern Loess Plateau of China from 1998 to 2012

This study analyzed temporal and spatial changes of normalized difference vegetation index (NDVI) on the northern Loess Plateau and their correlation with climatic factors from 1998 to 2012. The possible impacts of human activities on the NDVI changes were also explored. The results showed that (1) the annual maximum NDVI showed an upward trend. The significantly increased NDVI and decreasing severe desertification areas demonstrate that the vegetation condition improved in this area. (2) Over the past decades, climate tended to be warmer and drier. However, the mean temperature significantly decreased and precipitation slightly increased from 1998 to 2012, especially in spring and summer, which was one of the major reasons for the increase in the annual maximum NDVI. Compared to temperature, vegetation was more sensitive to precipitation changes in this area. The NDVI and annual precipitation changes were highly synchronous over the first half of the year, while a 1-month time lag existed between the two variables during the second half of the year. (3) Positive human activities, including the “Grain for Green” program and successful environmental treatments at coal mining bases, were some of the other factors that improved the vegetation condition.

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Mapping Impacts of Human Activities from Nighttime Light on Vegetation Cover Changes in Southeast Asia

Land ◽

10.3390/land10020185 ◽

2021 ◽

Vol 10 (2) ◽

pp. 185

Author(s):

Nan Xia ◽

Manchun Li ◽

Liang Cheng

Keyword(s):

Southeast Asia ◽

Human Activities ◽

Vegetation Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Infrared Imaging ◽

Human Impacts ◽

Time Lag ◽

Temporal Segmentation ◽

Vegetation Growth

It is commonly believed that the impacts of human activities have decreased the natural vegetation cover, while some promotion of the vegetation growth has also been found. In this study, negative or positive correlations between human impacts and vegetation cover were tested in the Southeast Asia (SEA) region during 2012–2018. The Visible Infrared Imaging Radiometer Suite—Day/Night Band (VIIRS/DNB) nocturnal data were used as a measure of human activities and the moderate resolution imaging spectroradiometer (MODIS)/normalized difference vegetation index (NDVI) diurnal data were used as a measure of vegetation cover. The temporal segmentation method was introduced to calculate features of two sets of time series with spatial resolution of about 500 m, including the overall trend, maximum trend, start date, and change duration. The regions with large variation in human activities (V-change region) were first extracted by the Gaussian fitted method, and 8.64% of the entire SEA (VIIRS overall trend <−0.2 or >0.4) was set as the target analysis area. According to statistics, the average overall VIIRS trend for the V-change region in SEA was about 2.12, with a slight NDVI increment. The time lag effect was also found between vegetation cover and human impacts change, with an average of 10.26 months. Our results indicated a slight green overall trend in the SEA region over the most recent 7 years. The spatial pattern of our trend analysis results can be useful for vegetation management and regional planning.

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Factors Driving Changes in Vegetation in Mt. Qomolangma (Everest): Implications for the Management of Protected Areas

Remote Sensing ◽

10.3390/rs13224725 ◽

2021 ◽

Vol 13 (22) ◽

pp. 4725

Author(s):

Binghua Zhang ◽

Yili Zhang ◽

Zhaofeng Wang ◽

Mingjun Ding ◽

Linshan Liu ◽

...

Keyword(s):

Linear Regression ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Climatic Factors ◽

Time Lag ◽

Buffer Zone ◽

Rate Of Change ◽

Vegetation Growth ◽

Time Accumulation ◽

The Impact

The Mt. Qomolangma (Everest) National Nature Preserve (QNNP) is among the highest natural reserves in the world. Monitoring the spatiotemporal changes in the vegetation in this complex vertical ecosystem can provide references for decision makers to formulate and adapt strategies. Vegetation growth in the reserve and the factors driving it remains unclear, especially in the last decade. This study uses the normalized difference vegetation index (NDVI) in a linear regression model and the Breaks for Additive Seasonal and Trend (BFAST) algorithm to detect the spatiotemporal patterns of the variations in vegetation in the reserve since 2000. To identify the factors driving the variations in the NDVI, the partial correlation coefficient and multiple linear regression were used to quantify the impact of climatic factors, and the effects of time lag and time accumulation were also considered. We then calculated the NDVI variations in different zones of the reserve to examine the impact of conservation on the vegetation. The results show that in the past 19 years, the NDVI in the QNNP has exhibited a greening trend (slope = 0.0008/yr, p < 0.05), where the points reflecting the transition from browning to greening (17.61%) had a much higher ratio than those reflecting the transition from greening to browning (1.72%). Shift points were detected in 2010, following which the NDVI tendencies of all the vegetation types and the entire preserve increased. Considering the effects of time lag and time accumulation, climatic factors can explain 44.04% of the variation in vegetation. No climatic variable recorded a change around 2010. Considering the human impact, we found that vegetation in the core zone and the buffer zone had generally grown better than the vegetation in the test zone in terms of the tendency of growth, the rate of change, and the proportions of different types of variations and shifts. A policy-induced reduction in livestock after 2010 might explain the changes in vegetation in the QNNP.

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An Assessment of Human versus Climatic Impacts on Jing River Basin, Loess Plateau, China

Advances in Meteorology ◽

10.1155/2015/478739 ◽

2015 ◽

Vol 2015 ◽

pp. 1-13 ◽

Cited By ~ 7

Author(s):

Yi He ◽

Fei Wang ◽

Xingmin Mu ◽

Huiting Yan ◽

Guangju Zhao

Keyword(s):

Loess Plateau ◽

Human Activities ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Sediment Load ◽

Similar Process ◽

Monthly Data ◽

Climatic Impacts ◽

The Impact ◽

Linear Correlations

The impacts of climate change and human activities on runoff and sediment load are too integrated to distinguish their own contributions. We develop a new method to assess the impact of human activities based on paired years with similar precipitation and evapotranspiration (ET0) conditions (SPEC) using a 55-year monthly data of climate, runoff, and sediment load in 1958–2012 at Zhangjiashan Hydrologic Station of Jing River, Loess Plateau, China. The SPEC of paired periods is defined by similar annual amounts (difference less than 2.0%) and similar process (linear correlations of monthly data less than 0.05) which could set a precondition fixing the possible influence of climate factors. The runoff declined in all nine paired years, but the sediment load and concentration decreased in seven (78%) and six (67%) paired years, respectively. The further analysis with available data of land use and land cover (LUC), Normalized Difference Vegetation Index (NDVI), and soil and water measures in this basin and the results could explain impacts of human activities well. The method could be used combining with the traditional methods in hydrological research.

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Temporal and Spatial Changes and Driving Forces of NDVI From 1982 - 2015 in Qinba Mountains, China

10.21203/rs.3.rs-415051/v1 ◽

2021 ◽

Author(s):

Yaru Zhang ◽

Yi He ◽

Yanlin Li ◽

Liping Jia

Keyword(s):

Human Activities ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Slow Growth ◽

Driving Forces ◽

Vegetation Coverage ◽

Factors Affecting ◽

Spatial Changes ◽

Change Trend ◽

Temporal And Spatial

Abstract The spatiotemporal variation and driving force of Normalized Difference Vegetation Index (NDVI) is helpful to regional ecological environment protection and natural resource management. Using the Sen and Mann–Kendall methods, Hurt index, Space transfer matrix and Geodetector, this study investigated the temporal and spatial changes and driving forces of NDVI during 1982 - 2015. The results showed that:（1）For the period 1982 to 2015, the high vegetation coverage was mainly distributed in Qinling Mountains and Daba mountain, while the value of NDVI was low in high altitude area in the west, low altitude in the East and Hanjiang River valley.（2）The change trend of NDVI in Qinba Mountains is mainly to maintain stable and slow growth. And the slow growth changes significantly. NDVI increased slowly mainly in the East and northwest.（3）The future change trend of NDVI in Qinba Mountain is mainly slow growth and stability, which indicates that the ecological construction in Qinba Mountains is good. (4) Through the geographical detector, the main factors affecting NDVI in Qinba Mountains are natural factors mainly including rainfall, soil type and digital elevation model (DEM), while human activities mainly including population density have little influence on NDVI in Qinba Mountains. Natural environment factors and human activities make a great difference on the spatial distribution of NDVI. This study provides a help for the sustainable development of the naturel environment in Qinba Mountains.

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Contributions of Vegetation Greening and Climate Change to Evapotranspiration Trend after Large-Scale Vegetation Restoration on the Loess Plateau, China

Water ◽

10.3390/w13131755 ◽

2021 ◽

Vol 13 (13) ◽

pp. 1755

Author(s):

Shuo Wang ◽

Chenfeng Cui ◽

Qin Dai

Keyword(s):

Climate Change ◽

Loess Plateau ◽

Large Scale ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Potential Evapotranspiration ◽

Development Trend ◽

Future Trend ◽

Natural Ecosystem ◽

The Loess Plateau

Since the early 2000s, the vegetation cover of the Loess Plateau (LP) has increased significantly, which has been fully recorded. However, the effects on relevant eco-hydrological processes are still unclear. Here, we made an investigation on the changes of actual evapotranspiration (ETa) during 2000–2018 and connected them with vegetation greening and climate change in the LP, based on the remote sensing data with correlation and attribution analysis. Results identified that the average annual ETa on the LP exhibited an obvious increasing trend with the value of 9.11 mm yr−1, and the annual ETa trend was dominated by the changes of ETa in the third quarter (July, August, and September). The future trend of ETa was predicted by the Hurst exponent. Partial correlation analysis indicated that annual ETa variations in 87.8% regions of the LP were controlled by vegetation greening. Multiple regression analysis suggested that the relative contributions of potential evapotranspiration (ETp), precipitation, and normalized difference vegetation index (NDVI), to the trend of ETa were 5.7%, −26.3%, and 61.4%, separately. Vegetation greening has a close relationship with the Grain for Green (GFG) project and acts as an essential driver for the long-term development trend of water consumption on the LP. In this research, the potential conflicts of water demanding between the natural ecosystem and social-economic system in the LP were highlighted, which were caused by the fast vegetation expansion.

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Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

Forest Ecosystems ◽

10.1186/s40663-021-00309-9 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Peixin Ren ◽

Zelin Liu ◽

Xiaolu Zhou ◽

Changhui Peng ◽

Jingfeng Xiao ◽

...

Keyword(s):

Climate Change ◽

Minimum Temperature ◽

Vegetation Index ◽

Climatic Factors ◽

Time Lag ◽

Evergreen Forest ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Study Region ◽

Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

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A Spatial and Temporal Assessment of Vegetation Greening and Precipitation Changes for Monitoring Vegetation Dynamics in Climate Zones over Africa

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10030129 ◽

2021 ◽

Vol 10 (3) ◽

pp. 129

Author(s):

Vincent Nzabarinda ◽

Anming Bao ◽

Wenqiang Xu ◽

Solange Uwamahoro ◽

Madeleine Udahogora ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Forest Type ◽

Pearson Correlation ◽

Correlation Coefficients ◽

Plant Health ◽

Tree Cover ◽

Climatic Zones ◽

Dramatic Decline ◽

Precipitation Changes

Vegetation is vital, and its greening depends on access to water. Thus, precipitation has a considerable influence on the health and condition of vegetation and its amount and timing depend on the climatic zone. Therefore, it is extremely important to monitor the state of vegetation according to the movements of precipitation in climatic zones. Although a lot of research has been conducted, most of it has not paid much attention to climatic zones in the study of plant health and precipitation. Thus, this paper aims to study the plant health in five African climatic zones. The linear regression model, the persistence index (PI), and the Pearson correlation coefficients were applied for the third generation Normalized Difference Vegetation Index (NDVI3g), with Climate Hazard Group infrared precipitation and Climate Change Initiative Land Cover for 34 years (1982 to 2015). This involves identifying plants in danger of extinction or in dramatic decline and the relationship between vegetation and rainfall by climate zone. The forest type classified as tree cover, broadleaved, deciduous, closed to open (>15%) has been degraded to 74% of its initial total area. The results also revealed that, during the study period, the vegetation of the tropical, polar, and warm temperate zones showed a higher rate of strong improvement. Although arid and boreal zones show a low rate of strong improvement, they are those that experience a low percentage of strong degradation. The continental vegetation is drastically decreasing, especially forests, and in areas with low vegetation, compared to more vegetated areas, there is more emphasis on the conservation of existing plants. The variability in precipitation is excessively hard to tolerate for more types of vegetation.

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

Frontiers in Environmental Science ◽

10.3389/fenvs.2021.633020 ◽

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) > semi-mobile dunes (0.0012) > gobi (gravel) desert (0.0011) > mobile dunes (0.0003) > saline–alkali land (0.0000). The proportions of the area of each desert type in which NDVI increased were fixed dunes (43.4%) > semi-mobile dunes (39.7%) > semi-fixed dunes (26.7%) > saline–alkali land (23.1%) > gobi desert (14.4%) > 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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THE NORMALIZED DIFFERENCE VEGETATION INDEX AS AN INDICATOR OF DYNAMICS

10.32008/geolinks2021/b2/v3/27 ◽

2021 ◽

Author(s):

Haddad Amar ◽

Beldjazia Amina ◽

Kadi Zahia ◽

Redjaimia Lilia ◽

Rached-Kanouni Malika

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Climatic Factors ◽

Mediterranean Ecosystems ◽

Point Of View ◽

Aleppo Pine ◽

Landsat 8 ◽

North East ◽

The North ◽

Pine Trees

Mediterranean ecosystems are considered particularly sensitive to climate change. Any change in climatic factors affects the structure and functioning of these ecosystems and has an influence on plant productivity. The main objective of this work is to characterize one of the Mediterranean ecosystems; the Chettaba forest massif (located in the North-East of Algeria) from a vegetation point of view and their link with monthly variations using Landsat 8 satellite images from five different dates (June 25, 2017, July 27, 2017, August 28, 2017, October 15, 2017). The comparison of NDVI values in Aleppo pine trees was performed using analysis of variance and the use of Friedman's non-parametric test. The Mann-Kendall statistical method was applied to the monthly distribution of NDVI values to detect any trends in the data over the study period. The statistical results of NDVI of Aleppo pine trees indicate that the maximum value is recorded in the month of June, while the lowest values are observed in the month of August where the species studied is exposed to periods of thermal stress.

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Explicitly Identifying the Desertification Change in CMREC Area Based on Multisource Remote Data

Remote Sensing ◽

10.3390/rs12193170 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3170

Author(s):

Zemeng Fan ◽

Saibo Li ◽

Haiyan Fang

Keyword(s):

Climate Change ◽

Human Activities ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Net Primary Productivity ◽

Regression Tree ◽

Google Earth ◽

Classification And Regression Tree ◽

Support Vector ◽

Driving Mechanisms

Explicitly identifying the desertification changes and causes has been a hot issue of eco-environment sustainable development in the China–Mongolia–Russia Economic Corridor (CMREC) area. In this paper, the desertification change patterns between 2000 and 2015 were identified by operating the classification and regression tree (CART) method with multisource remote sensing datasets on Google Earth Engine (GEE), which has the higher overall accuracy (85%) than three other methods, namely support vector machine (SVM), random forest (RF) and Albedo-normalized difference vegetation index (NDVI) models. A contribution index of climate change and human activities on desertification was introduced to quantitatively explicate the driving mechanisms of desertification change based on the temporal datasets and net primary productivity (NPP). The results show that the area of slight desertification land had increased from 719,700 km2 to 948,000 km2 between 2000 and 2015. The area of severe desertification land decreased from 82,400 km2 to 71,200 km2. The area of desertification increased by 9.68%, in which 69.68% was mainly caused by human activities. Climate change and human activities accounted for 68.8% and 27.36%, respectively, in the area of desertification restoration. In general, the degree of desertification showed a decreasing trend, and climate change was the major driving factor in the CMREC area between 2000 and 2015.

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