Responses of Xilingol Fractional Vegetation Cover to Climate Change and Human Activities

Based on the MODIS NDVI product data source of Xilingol from 2010 to 2019, we use the pixel dichotomous model to retrieve the vegetation coverage in our study. The spatiotemporal changes of the vegetation cover were analyzed in the model by using the meteorological data from researched sites or the vicinal meteorological stations for evaluating the meteorological influence on the vegetation cover changes. Based on this, an evaluation method was established to estimate the relative influences of the climate changes and anthropogenic activities. The main conclusions are as follows: (1) Fractional vegetation cover in Xilingol was decreased from the northeast to the southwest. (2) The overall trend in Xilingol fractional vegetation cover in the 10-year period shows a fluctuating increasing trend. (3) An opposite distribution pattern was detected between mean precipitation and mean temperature in the study site. (4) Compared with temperature, annual precipitation has a higher correlation with fractional vegetation cover in the study site and is the main climatic factor that affects vegetation growth in the study site. (5) During the 10-year period in the study site, anthropogenic human activities have slightly greater inhibitory effects on vegetation growth than promoting effects. (6) Climate change is a major factor to accelerate grassland degradation from 2010 to 2019 in vegetation degradation regions. The promotion effect of precipitation on vegetation coverage is obviously higher than the limitation of human activities, which leads to the increase of vegetation coverage in 2010–2019.

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STUDY OF MAOWUSU SANDY LAND VEGETATION COVERAGE CHANGE BASED ON MODIS NDVI

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-2127-2018 ◽

2018 ◽

Vol XLII-3 ◽

pp. 2127-2133

Author(s):

Q. Ye ◽

H. Liu ◽

Y. Lin ◽

R. Han

Keyword(s):

Vegetation Cover ◽

Meteorological Data ◽

Pearson Correlation ◽

Linear Regression Analysis ◽

Growth Period ◽

Vegetation Coverage ◽

Sandy Land ◽

Vegetation Growth ◽

Modis Ndvi ◽

Temperature And Precipitation

This paper selected 2006-2016 MODIS NDVI data with a spatial resolution of 500m and time resolution of 16d, got the 11 years’ time series NDVI data of Maowusu sandy land through mosaicking, projection transformation, cutting process in batch. Analysed the spatial and temporal distribution and variation characteristics of vegetation cover in year, season and month time scales by maximum value composite, and unary linear regression analysis. Then, we combined the meteorological data of 33 sites around the sandy area, analysed the response characteristics of vegetation cover change to temperature and precipitation through Pearson correlation coefficient. Studies have shown that: (1) The NDVI value has a stable increase trend, which rate is 0.0075&thinsp;/&thinsp;a. (2) The vegetation growth have significantly difference in four seasons, the NDVI value of summer&thinsp;&gt;&thinsp;autumn&thinsp;&gt;&thinsp;spring&thinsp;&gt;&thinsp;winter. (3) The NDVI value change trend is conformed to the gauss normal distribution in a year, and it comes to be largest in August, its green season is in April, and yellow season is in the middle of November, the growth period is about 220&thinsp;d. (4) The vegetation has a decreasing trend from the southeast to the northwest, most part is slightly improved, and Etuokeqianqi improved significantly. (5) The correlation indexes of annual NDVI with temperature and precipitation are &minus;0.2178 and 0.6309, the vegetation growth is mainly affected by precipitation. In this study, a complete vegetation cover analysis and evaluation model for sandy land is established. It has important guiding significance for the sand ecological environment protection.

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Quantifying the Impacts of Anthropogenic Activities and Climate Variations on Vegetation Productivity Changes in China from 1985 to 2015

Remote Sensing ◽

10.3390/rs12071113 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1113

Author(s):

Shahid Naeem ◽

Yongqiang Zhang ◽

Jing Tian ◽

Faisal Mueen Qamer ◽

Aamir Latif ◽

...

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Human Activities ◽

Vegetation Cover ◽

Net Primary Productivity ◽

Anthropogenic Activities ◽

Climate Factors ◽

Climate Variations ◽

Base Period ◽

Increasing Trends

Accurate assessment of vegetation dynamics provides important information for ecosystem management. Anthropogenic activities and climate variations are the major factors that primarily influence vegetation ecosystems. This study investigates the spatiotemporal impacts of climate factors and human activities on vegetation productivity changes in China from 1985 to 2015. Actual net primary productivity (ANPP) is used to reflect vegetation dynamics quantitatively. Climate-induced potential net primary productivity (PNPP) is used as an indicator of climate change, whereas the difference between PNPP and ANPP is considered as an indicator of human activities (HNPP). Overall, 91% of the total vegetation cover area shows declining trends for net primary productivity (NPP), while only 9% shows increasing trends before 2000 (base period). However, after 2000 (restoration period), 78.7% of the total vegetation cover area shows increasing trends, whereas 21.3% of the area shows decreasing trends. Moreover, during the base period, the quantitative contribution of climate change to NPP restoration is 0.21 grams carbon per meter square per year (gC m−2 yr−1) and to degradation is 2.41 gC m−2 yr−1, while during the restoration period, climate change contributes 0.56 and 0.29 gC m−2 yr−1 to NPP restoration and degradation, respectively. Human activities contribute 0.36 and 0.72 gC m−2 yr−1 during the base period, and 0.63 and 0.31 gC m−2 yr−1 during the restoration period to NPP restoration and degradation, respectively. The combined effects of climate and human activities restore 0.65 and 1.11 gC m−2 yr−1, and degrade 2.01 and 0.67 gC m−2 yr−1 during the base and restoration periods, respectively. Climate factors affect vegetation cover more than human activities, while precipitation is found to be more sensitive to NPP change than temperature. Unlike the base period, NPP per unit area increases with an increase in the human footprint pressure during the restoration period. Grassland has more variability than other vegetation classes, and the grassland changes are mainly observed in Tibet, Xinjiang, and Inner Mongolia regions. The results may help policy-makers by providing necessary guidelines for the management of forest, grassland, and agricultural activities.

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Monitoring Changes to Arctic Vegetation and Glaciers at Ny-Ålesund, Svalbard, Based on Time Series Remote Sensing

Remote Sensing ◽

10.3390/rs13193845 ◽

2021 ◽

Vol 13 (19) ◽

pp. 3845

Author(s):

Guangbo Ren ◽

Jianbu Wang ◽

Yunfei Lu ◽

Peiqiang Wu ◽

Xiaoqing Lu ◽

...

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Time Series ◽

High Latitude ◽

Global Climate ◽

Meteorological Data ◽

Remote Sensing Data ◽

Vegetation Coverage ◽

Coastal Regions ◽

Average Annual Temperature

Climate change has profoundly affected global ecological security. The most vulnerable region on Earth is the high-latitude Arctic. Identifying the changes in vegetation coverage and glaciers in high-latitude Arctic coastal regions is important for understanding the process and impact of global climate change. Ny-Ålesund, the northern-most human settlement, is typical of these coastal regions and was used as a study site. Vegetation and glacier changes over the past 35 years were studied using time series remote sensing data from Landsat 5/7/8 acquired in 1985, 1989, 2000, 2011, 2015 and 2019. Site survey data in 2019, a digital elevation model from 2009 and meteorological data observed from 1985 to 2019 were also used. The vegetation in the Ny-Ålesund coastal zone showed a trend of declining and then increasing, with a breaking point in 2000. However, the area of vegetation with coverage greater than 30% increased over the whole study period, and the wetland moss area also increased, which may be caused by the accelerated melting of glaciers. Human activities were responsible for the decline in vegetation cover around Ny-Ålesund owing to the construction of the town and airport. Even in areas with vegetation coverage of only 13%, there were at least five species of high-latitude plants. The melting rate of five major glaciers in the study area accelerated, and approximately 82% of the reduction in glacier area occurred after 2000. The elevation of the lowest boundary of the five glaciers increased by 50–70 m. The increase in precipitation and the average annual temperature after 2000 explains the changes in both vegetation coverage and glaciers in the study period.

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Inconsistency of Global Vegetation Dynamics Driven by Climate Change: Evidences from Spatial Regression

Remote Sensing ◽

10.3390/rs13173442 ◽

2021 ◽

Vol 13 (17) ◽

pp. 3442

Author(s):

Dou Zhang ◽

Xiaolei Geng ◽

Wanxu Chen ◽

Lei Fang ◽

Rui Yao ◽

...

Keyword(s):

Climate Change ◽

Vegetation Index ◽

Climatic Factors ◽

Potential Evapotranspiration ◽

Anthropogenic Activities ◽

Test Method ◽

Spatial Error ◽

Vegetation Growth ◽

Annual Peak ◽

Global Vegetation

Global greening over the past 30 years since 1980s has been confirmed by numerous studies. However, a single-dimensional indicator and non-spatial modelling approaches might exacerbate uncertainties in our understanding of global change. Thus, comprehensive monitoring for vegetation’s various properties and spatially explicit models are required. In this study, we used the newest enhanced vegetation index (EVI) products of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 to detect the inconsistency trend of annual peak and average global vegetation growth using the Mann–Kendall test method. We explored the climatic factors that affect vegetation growth change from 2001 to 2018 using the spatial lag model (SLM), spatial error model (SEM) and geographically weighted regression model (GWR). The results showed that EVImax and EVImean in global vegetated areas consistently showed linear increasing trends during 2001–2018, with the global averaged trend of 0.0022 yr−1 (p < 0.05) and 0.0030 yr−1 (p < 0.05). Greening mainly occurred in the croplands and forests of China, India, North America and Europe, while browning was almost in the grasslands of Brazil and Africa (18.16% vs. 3.08% and 40.73% vs. 2.45%). In addition, 32.47% of the global vegetated area experienced inconsistent trends in EVImax and EVImean. Overall, precipitation and mean temperature had positive impacts on vegetation variation, while potential evapotranspiration and vapour pressure had negative impacts. The GWR revealed that the responses of EVI to climate change were inconsistent in an arid or humid area, in cropland or grassland. Climate change could affect vegetation characteristics by changing plant phenology, consequently rendering the inconsistency between peak and mean greening. In addition, anthropogenic activities, including land cover change and land use management, also could lead to the differences between annual peak and mean vegetation variations.

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Recent responses of grassland net primary productivity to climatic and anthropogenic factors in Kyrgyzstan

10.31219/osf.io/3q6h8 ◽

2020 ◽

Author(s):

Yanwen Wang

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Human Activities ◽

Net Primary Productivity ◽

Anthropogenic Activities ◽

Dominant Factor ◽

Anthropogenic Factors ◽

Grassland Degradation ◽

Contributing Factors ◽

Spatial And Temporal Patterns

Net primary productivity (NPP) is an essential indicator of ecosystem function and sustainability and plays a vital role in the carbon cycle, especially in arid and semi-arid grassland ecosystems. Quantifying trends in NPP and identifying the contributing factors are important for understanding the relative impacts of climate change and human activities on grassland degradation. We quantified spatial and temporal patterns in potential NPP (NPPP) and actual NPP (NPPA) in Kyrgyzstan from 2000 to 2014 based on the Zhou Guangsheng model and MOD17A3 NPP data, respectively. By calculating the difference between NPPP and NPPA, we inferred human-induced NPP (NPPH) and thereby characterised changes in grassland NPP attributable to anthropogenic activities. We found that over the past two decades, both climatic variation and anthropogenic activities have significantly affected Kyrgyzstan’s grasslands. Grassland NPP decreased overall but patterns varied between provinces. Climate change, in particular changes in precipitation was the dominant factor driving grassland degradation in the north but human pressures also contributed. In the south however, human activities were associated with extensive areas of grassland recovery. The results provide important contextual understanding for supporting policy for grassland maintenance and restoration under climate change and intensifying human pressures.

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Assessment of soil erosion in the Dongting Lake Basin, China: Patterns, drivers, and implications

PLoS ONE ◽

10.1371/journal.pone.0261842 ◽

2021 ◽

Vol 16 (12) ◽

pp. e0261842

Author(s):

Jianyong Xiao ◽

Binggeng Xie ◽

Kaichun Zhou ◽

Shana Shi ◽

Junhan Li ◽

...

Keyword(s):

Climate Change ◽

Land Use ◽

Soil Erosion ◽

Human Activities ◽

Dongting Lake ◽

Vegetation Coverage ◽

Lake Basin ◽

Driving Mechanism ◽

Land Use Types ◽

Key Factor

Soil loss caused by erosion is a global problem. Therefore, the assessment of soil erosion and the its driving mechanism are of great significance to soil conservation. However, soil erosion is affected by both climate change and human activities, which have not been quantified, and few researchers studied the differences in the driving mechanisms of soil erosion depending on the land use type. Therefore, the spatiotemporal characteristics and changing trends of soil erosion in the Dongting Lake Basin were analyzed in this study. Geographic detectors were used to identify the dominant factors affecting soil erosion in different land use types. In this study, a sensitivity experiment was conducted to clarify the relative contributions of climate change and human activities to soil erosion changes. In addition, we studied the effects of different land use types and vegetation cover restoration on soil erosion. The results show that soil erosion in the Dongting Lake Basin decreased from 2000 to 2018. Human activities represented by land use types and vegetation coverage significantly contributed to the alleviation of soil erosion in the Dongting Lake Basin, whereas climate change represented by rainfall slightly aggravated soil erosion in the study area. The restoration of grassland vegetation and transfer of cultivated land to woodlands in the study area improved the soil erosion. The slope steepness is the key factor affecting the intensity of soil erosion in dry land, paddy fields, and unused land, whereas the vegetation coverage is the key factor affecting the intensity of soil erosion in woodland, garden land, and grassland. Detailed spatiotemporally mapping of soil erosion was used to determine the connections between soil erosion and potential drivers, which have important implications for vegetation restoration and the optimization of land use planning.

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Quantifying the Influences of Natural Factors and Human Activities on NDVI Changes in the Hanjiang River Basin, China

Remote Sensing ◽

10.3390/rs12223780 ◽

2020 ◽

Vol 12 (22) ◽

pp. 3780

Author(s):

Ting Chen ◽

Jun Xia ◽

Lei Zou ◽

Si Hong

Keyword(s):

River Basin ◽

Human Activities ◽

Urban Areas ◽

Vegetation Index ◽

Vegetation Coverage ◽

Vegetation Growth ◽

Natural Factors ◽

Range Type ◽

Hanjiang River ◽

The Impact

The Hanjiang River Basin (HJRB) is an important source area for drinking water in Hubei Province, China, and the vegetation coverage there is important to the ecological system. Due to the spatial heterogeneity and synergistic effect of various factors, it is very difficult to identify the main factors affecting vegetation growth in the HJRB. With the normalized difference vegetation index (NDVI) data from 2001 to 2018 in the HJRB, the spatiotemporal patterns of NDVI and the influences of natural factors and human activities on NDVI were investigated and quantified based on the Mann-Kendall (M-K) test, partial correlation analysis, and Geographical Detector. The individual factors and their interactions and the range/type of factor attributes suitable for vegetation growth were also examined. NDVI in the HJRB increased from 2001 to 2018, and the variation rate was 0.0046 year−1. NDVI was increasing in 81.17% of the area (p < 0.05). Elevation and slope can effectively explain the vegetation distribution. The interactions of factors on NDVI were significant, and the interactions of the elevation and precipitation can maximize the impact among all factors. The range of available landforms is thought to be highly conducive to vegetation growth. The rates of the annual precipitation and annual mean temperature changed from 2001 to 2018, which were 3.665 mm/year and 0.017 °C/year, and the regions where NDVI positively correlated with them were over 85%. Contrary to the general trend, NDVI has obviously decreased in urban areas since 2010. The quantitative findings of this study can help us better understand the effects of various factors on vegetation growth and provide appropriate suggestions for vegetation protection and restoration in the HJRB.

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A Semi-Parametric Geographically Weighted Regression Approach to Exploring Driving Factors of Fractional Vegetation Cover: A Case Study of Guangdong

Sustainability ◽

10.3390/su12187512 ◽

2020 ◽

Vol 12 (18) ◽

pp. 7512

Author(s):

Yuhao Jin ◽

Han Zhang ◽

Yuchao Yan ◽

Peitong Cong

Keyword(s):

Geographically Weighted Regression ◽

Vegetation Cover ◽

Southern China ◽

Ordinary Least Squares ◽

Driving Factors ◽

Weighted Regression ◽

Impact Factors ◽

Negative Effects ◽

Vegetation Growth ◽

Fractional Vegetation Cover

Ecological degradation caused by rapid urbanisation has presented great challenges in southern China. Fractional vegetation cover (FVC) has long been the most common and sensitive index to describe vegetation growth and to monitor vegetation degradation. However, most of the studies have failed to adequately explore the complexity of the relationship between fractional vegetation cover (FVC) and impact factors. In this research, we first constructed a Semi-parametric Geographically Weighted Regression (SGWR) model to analyse both the stationary and nonstationary spatial relationships between FVC and driving factors in Guangdong province in southern China on a county level. Then, climate, topographic, land cover, and socio-economic factors were introduced into the model to distinguish impacts on FVC from 2000–2015. Results suggest that the positive and negative effects of rainfall and elevation coefficients alternated, and local urban land and population estimates indicated a negative association between FVC and the modelled factors in each period. The SGWR FVC make significantly improves performance of the geographically weighted regression and ordinary least squares models, with adjusted R2 higher than 0.78. The findings of this research demonstrated that, although urbanisation in the Pearl River Delta in Guangdong has encroached on the regional vegetation cover, the total vegetation area remained unchanged with the implementation of protection policies and regulations.

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Does Climate Change or Human Activity Lead to the Degradation in the Grassland Ecosystem in a Mountain-Basin System in an Arid Region of China?

Sustainability ◽

10.3390/su11092618 ◽

2019 ◽

Vol 11 (9) ◽

pp. 2618 ◽

Cited By ~ 2

Author(s):

Junjie Yan ◽

Guangpeng Zhang ◽

Xiaoya Deng ◽

Hongbo Ling ◽

Hailiang Xu ◽

...

Keyword(s):

Climate Change ◽

Human Activities ◽

Arid Region ◽

Vegetation Coverage ◽

Soil Drought ◽

Grassland Ecosystem ◽

Grassland Vegetation ◽

Irrigated Area ◽

The Impact ◽

Basin System

In mountain-basin systems in the arid region, grasslands are sensitive to the impacts of climate change and human activities. In this study, we aimed to resolve two key scientific issues: (1) distinguish and explain the laws of grassland ecosystem deterioration in a mountain-basin system and identify the key factors related; and (2) evaluate whether damaged grasslands ecosystem have the potential for natural revegetation. Hence, by combining spatial analysis with statistical methods, we studied the trends of the deterioration of the grassland ecosystem and its spatial characteristics in Kulusitai, a mountain-basin system in the arid region of Northwest China. According to our results, vegetation coverage and productivity exhibited significant decreasing trends, while the temperature vegetation drought index (TVDI) exhibited a significant increasing trend. Drainage of groundwater, because of increase in irrigation for the expanded irrigated area around Kulusitai, and climate warming were the critical triggers that leaded to the soil drought. Soil drought and overgrazing, resulting from the impact of human activities, were the main factors responsible for the deterioration of the grassland ecosystems. However, limiting the number of livestock to a reasonable scale and reducing the irrigated area may help to increase the soil moisture, thus promoting the germination of soil seed banks and facilitating the normal growth of grassland vegetation. Furthermore, based on analysis of the phenology of the grassland vegetation, the reasonable period for harvesting and storage is from July 29 to August 5. The results of this study provide a scientific basis and practical guide for restoring mountain-basin grassland systems in arid regions.

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