scholarly journals Detecting Spatiotemporal Changes in Vegetation with the BFAST Model in the Qilian Mountain Region during 2000–2017

2019 ◽  
Vol 11 (2) ◽  
pp. 103 ◽  
Author(s):  
Liying Geng ◽  
Tao Che ◽  
Xufeng Wang ◽  
Haibo Wang
Keyword(s):  
Large Scale ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Anthropogenic Activities ◽  
Western China ◽  
Qinghai Lake ◽  
Vegetation Changes ◽  
Qilian Mountain ◽  
Modis Ndvi ◽  
Positive Effects

The Qilian Mountain ecosystems play an irreplaceable role in maintaining ecological security in western China. Vegetation, as an important part of the ecosystem, has undergone considerable changes in recent decades in this area, but few studies have focused on the process of vegetation change. A long normalized difference vegetation index (NDVI) time series dataset based on remote sensing is an effective tool to investigate large-scale vegetation change dynamics. The MODerate resolution Imaging Spectroradiometer (MODIS) NDVI dataset has provided very detailed regional to global information on the state of vegetation since 2000. The aim of this study was to explore the spatial-temporal characteristics of abrupt vegetation changes and detect their potential drivers in the Qilian Mountain area using MODIS NDVI data with 1 km resolution from 2000 to 2017. The Breaks for Additive Season and Trend (BFAST) algorithm was adopted to detect vegetation breakpoint change times and magnitudes from satellite observations. Our results indicated that approximately 80.1% of vegetation areas experienced at least one abrupt change from 2000 to 2017, and most of these areas were distributed in the southern and northern parts of the study area, especially the area surrounding Qinghai Lake. The abrupt browning changes were much more widespread than the abrupt greening changes for most years of the study period. Environmental factors and anthropogenic activities mainly drove the abrupt vegetation changes. Long-term overgrazing is likely the main cause of the abrupt browning changes. In addition, our results indicate that national ecological protection policies have achieved positive effects in the study area.

scholarly journals Vegetation Dynamic Assessment by NDVI and Field Observations for Sustainability of China’s Wulagai River Basin

2021 ◽  
Vol 18 (5) ◽  
pp. 2528
Author(s):  
Panpan Chen ◽  
Huamin Liu ◽  
Zongming Wang ◽  
Dehua Mao ◽  
Cunzhu Liang ◽  
...  
Keyword(s):  
Species Diversity ◽  
River Basin ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Dynamic Assessment ◽  
Indicator System ◽  
Vegetation Changes ◽  
Vegetation Dynamic ◽  
Management Policies ◽  
The Impact

Accurate monitoring of grassland vegetation dynamics is essential for ecosystem restoration and the implementation of integrated management policies. A lack of information on vegetation changes in the Wulagai River Basin restricts regional development. Therefore, in this study, we integrated remote sensing, meteorological, and field plant community survey data in order to characterize vegetation and ecosystem changes from 1997 to 2018. The residual trend (RESTREND) method was utilized to detect vegetation changes caused by human factors, as well as to evaluate the impact of the management of pastures. Our results reveal that the normalized difference vegetation index (NDVI) of each examined ecosystem type showed an increasing trend, in which anthropogenic impact was the primary driving force of vegetation change. Our field survey confirmed that the meadow steppe ecosystem increased in species diversity and aboveground biomass; however, the typical steppe and riparian wet meadow ecosystems experienced species diversity and biomass degradation, therefore suggesting that an increase in NDVI may not directly reflect ecosystem improvement. Selecting an optimal indicator or indicator system is necessary in order to formulate reasonable grassland management policies for increasing the sustainability of grassland ecosystems.

scholarly journals Simulated climate variability in the region of Rapa Nui during the last millennium

2011 ◽  
Vol 7 (1) ◽  
pp. 381-395 ◽  
Author(s):  
C. Junk ◽  
M. Claussen
Keyword(s):  
Large Scale ◽  
Vegetation Change ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Easter Island ◽  
Ice Age ◽  
Vegetation Changes ◽  
Last Millennium ◽  
Climate Data ◽  
Climatic Fluctuations

Abstract. Easter Island, an isolated island in the Southeast Pacific, was settled by the Polynesians probably between 600 and 1200 AD and discovered by the Europeans in 1722 AD. While the Polynesians presumably found a profuse palm woodland on Easter Island, the Europeans faced a landscape dominated by grassland. Scientists have examined potential anthropogenic, biological and climatic induced vegetation changes on Easter Island. Here, we analyze observational climate data for the last decades and climate model results for the period 800–1750 AD to explore potential causes for a climatic-induced vegetation change. A direct influence of the ENSO phenomenon on the climatic parameters of Easter Island could not be found in the model simulations. Furthermore, strong climatic trends from a warm Medieval Period to a Little Ice Age or rapid climatic fluctuations due to large volcanic eruptions were not verifiable for the Easter Island region, although they are detectable in the simulations for many regions world wide. Hence we tentatively conclude that large-scale climate changes in the oceanic region around Easter Island might be too small to explain strong vegetation changes on the island over the last millennium.

scholarly journals Detecting Vegetation Change in the Pearl River Delta Region Based on Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND) and MODIS NDVI

2020 ◽  
Vol 12 (24) ◽  
pp. 4049
Author(s):  
Zhu Ruan ◽  
Yaoqiu Kuang ◽  
Yeyu He ◽  
Wei Zhen ◽  
Song Ding
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Pearl River Delta ◽  
Vegetation Change ◽  
Vegetation Changes ◽  
Pearl River Delta Region ◽  
Modis Ndvi ◽  
Time Series Segmentation ◽  
The Pearl River ◽  
The City

Time Series Segmentation and Residual Trend analysis (TSS-RESTREND) can detect an abrupt change that was undetected by Residual Trend analysis (RESTREND), but it is usually combined with the Global Inventory for Mapping and Modeling Studies (GIMMS) Normalized Difference Vegetation Index (NDVI), which cannot detect detailed vegetation changes in small areas. Hence, we used Time Series Segmentation and Residual Trend analysis (TSS-RESTREND) and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI (MOD-TR) to analyze the vegetation dynamic of the Pearl River Delta region (PRD) in this study. To choose the most suitable MODIS NDVI from MOD13Q1 (250 m), MOD13A1 (500 m), and MOD13A2 (1 km), whole and local comparison of results of the break year and MOD-TR were used. Meanwhile, a comparison of vegetation change at the city-scale was also implemented. Moreover, to reduce insignificant trend pixels in TSS-RESTREND, a combination method of TSS-RESTREND and RESTREND (CTSS-RESTREND) was proposed. We found that: (1) MOD13Q1 and MOD13A1 two NDVI were suitable for combination with TSS-RESTREND to detect vegetation change in PRD, but MOD13Q1 was a better choice when considering the accuracy of local detailed vegetation change; (2) CTSS-RESTREND could detect more pixels with a significant change (i.e., significant increase and significant decrease) than those of TSS-RESTREND and RESTREND. Also, its effectiveness could be verified by Landsat data; (3) at the city-scale, the CTSS-RESTREND detected that only vegetation decreases in Shenzhen, Foshan, Dongguan, and Zhongshan were higher than vegetation increases, but, significant vegetation changes (i.e., decreases and increases) were mainly concentrated in Huizhou, Jiangmen, Zhaoqing, and Guangzhou.

scholarly journals Simulated climate variability in the region of Rapa Nui during the last millennium

2011 ◽  
Vol 7 (2) ◽  
pp. 579-586 ◽  
Author(s):  
C. Junk ◽  
M. Claussen
Keyword(s):  
Large Scale ◽  
Vegetation Change ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Ice Age ◽  
Vegetation Changes ◽  
Last Millennium ◽  
Climate Data ◽  
Rapa Nui ◽  
Climatic Fluctuations

Abstract. Rapa Nui, an isolated island in the Southeast Pacific, was settled by the Polynesians most likely around 1200 AD and was discovered by the Europeans in 1722 AD. While the Polynesians presumably found a profuse palm woodland on Rapa Nui, the Europeans faced a landscape dominated by grassland. Scientists have examined potential anthropogenic, biological and climatic induced vegetation changes on Rapa Nui. Here, we analyse observational climate data for the last decades and climate model results for the period 800–1750 AD to explore the potential for a climatic-induced vegetation change. A direct influence of the ENSO phenomenon on the climatic parameters of Rapa Nui could not be found in the model simulations. Furthermore, strong climatic trends from a warm Medieval Period to a Little Ice Age or rapid climatic fluctuations due to large volcanic eruptions were not verifiable for the Rapa Nui region, although they are detectable in the simulations for many regions world wide. Hence, we tentatively conclude that large-scale climate changes in the oceanic region around Rapa Nui might be too small to explain strong vegetation changes on the island over the last millennium.

scholarly journals Topographic Controls on Vegetation Changes in Alpine Tundra of the Changbai Mountains

Forests ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 756 ◽  
Author(s):  
Miaomiao Wu ◽  
Hong He ◽  
Shengwei Zong ◽  
Xinyuan Tan ◽  
Haibo Du ◽  
...  
Keyword(s):  
High Altitude ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Scale Effects ◽  
Alpine Tundra ◽  
Changbai Mountains ◽  
Vegetation Changes ◽  
Tundra Vegetation ◽  
Topographic Controls ◽  
Low Altitude

The vegetation of alpine tundra is undergoing significant changes and topography has played a significant role in mediating such changes. The roles of topography varied at different scales. In this study, we intended to identify topographic controls on tundra vegetation changes within the Changbai Mountains of Northeast China and reveal the scale effects. We delineated the vegetation changes of the last three decades using the normalized difference vegetation index (NDVI) time series. We conducted a trend analysis for each pixel to reveal the spatial change and used binary logistic regression models to analyze the relationship between topographic controls at different scales and vegetation changes. Results showed that about 30% of tundra vegetation experienced a significant (p < 0.05) change in the NDVI, with 21.3% attributable to the encroachment of low-altitude plants resulting in a decrease in the NDVI, and 8.7% attributable to the expansion of tundra endemic plants resulting in an increase in the NDVI. Plant encroachment occurred more severely in low altitude than in high altitude, whereas plant expansion mostly occurred near volcanic ash fields at high altitude. We found that plant encroachment tended to occur in complex terrains and the broad-scale mountain aspect had a greater effect on plant encroachment than the fine-scale local aspect. Our results suggest that it is important to include the mountain aspect in mountain vegetation change studies, as most such studies only use the local aspect.

scholarly journals Quantifying Spatiotemporal Dynamics of Vegetation and Its Differentiation Mechanism Based on Geographical Detector

2021 ◽  
Author(s):  
Guangjie Wang ◽  
wenfu peng
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Synergistic Effects ◽  
Good Condition ◽  
Interactive Effects ◽  
Western China ◽  
Impact Factors ◽  
Vegetation Changes ◽  
Vegetation Growth ◽  
The Impact

Abstract Understanding of the influence of factors on vegetation changes in different is still largely unknown. We have applied the Geographic Detector, a new spatial statistical method to study the interactive effects of factors on the spatial patterns of normalized vegetation index (NDVI) changes and determine the optimal characteristics of key impact factors that are beneficial to vegetation growth. Our results show that the vegetation cover from 2000 to 2015 for the upper reaches of the Minjiang River, western China was in good condition, the areas of 0.6<NDVI>0.8 and NDVI>0.8 accounted for more than 80%, and the spatial-temporal changes of vegetation cover were significant. The changes of vegetation cover were showed a significant transformation in the regions of NDVI>0.6. Our study uniquely illustrated that the elevation, annual average temperature and soil type can relatively well explain the vegetation changes. We propose that there are interactive effects between impact factors on vegetation NDVI, and the synergistic effects of the impact factors show mutual enhancement and nonlinear enhancement. The interactions between impact factors significantly enhance the impact of a single factor on vegetation changes. The most suitable characteristics of the main impact factors that promote the vegetation growth revealed help a better understanding of the impact of factors on NDVI and its driving mechanisms. Our findings suggest that the determined a favourable value range or the most suitable characteristics of impact factors help to intervene and promote vegetation change for vegetation restoration and alleviate environmental degradation.

scholarly journals Digital Examination of Vegetation Changes in River Floodplain Wetlands Based on Remote Sensing Images: A Case Study Based on the Downstream Section of Hailar River

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1206
Author(s):  
Xi Dong ◽  
Zhibo Chen
Keyword(s):  
Remote Sensing ◽  
Water Supply ◽  
Plant Community ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Forest Vegetation ◽  
High Rate ◽  
Vegetation Changes ◽  
Herbaceous Plant ◽  
Sparse Vegetation

The Hailar River is an important river in the Inner Mongolia Autonomous Region, China. It plays an extremely important role in maintaining the ecological balance of the region. However, in recent decades, the Hailar River and its surrounding areas have been developed at a high rate and its wetland resources have faced various threats. In this study, vegetation changes in the Hailar River wetlands were analyzed using remote sensing data from the Landsat TM (1987, 2001, and 2010) and Landsat OLI-TIRS (2019) satellites. A vegetation change model was developed using Matlab software to assess vegetation changes in the area. There were significant changes in the wetland vegetation of the lower Hailar River study site between 1987 and 2019. There was an increase in open sand habitat with a sparse vegetation area of 1.08 km2, a decrease in grassland area of 13.17 km2, and an increase in the forest area of 15.91 km2. The spatial distribution of the normalized difference vegetation index (NDVI) varied across the study site and was high overall. The vegetation types varied with distance from the river. There are two possible explanations for positive and negative vegetation change trends. In areas where the water supply is sufficient and relatively stable, the cover of forest vegetation was gradually increasing and the herbaceous plant community is gradually evolving into a scrub woodland plant community. In areas where the water supply is lacking, there are changes in the sense of a decrease of forest vegetation and an increase of open sand habitat with sparse vegetation. Therefore, this study suggests that the existing wetlands should be protected, used wisely, and developed rationally to provide sustainable resources for the next generation.

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 Vegetation Change and Its Response to Climate Extremes in the Arid Region of Northwest China

2021 ◽  
Vol 13 (7) ◽  
pp. 1230
Author(s):  
Simeng Wang ◽  
Qihang Liu ◽  
Chang Huang
Keyword(s):  
Arid Region ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Time Lag ◽  
Climate Extremes ◽  
Northwest China ◽  
Precipitation Extremes ◽  
Temperature Extremes ◽  
Increasing Trend

Changes in climate extremes have a profound impact on vegetation growth. In this study, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS) and a recently published climate extremes dataset (HadEX3) to study the temporal and spatial evolution of vegetation cover, and its responses to climate extremes in the arid region of northwest China (ARNC). Mann-Kendall test, Anomaly analysis, Pearson correlation analysis, Time lag cross-correlation method, and Least absolute shrinkage and selection operator logistic regression (Lasso) were conducted to quantitatively analyze the response characteristics between Normalized Difference Vegetation Index (NDVI) and climate extremes from 2000 to 2018. The results showed that: (1) The vegetation in the ARNC had a fluctuating upward trend, with vegetation significantly increasing in Xinjiang Tianshan, Altai Mountain, and Tarim Basin, and decreasing in the central inland desert. (2) Temperature extremes showed an increasing trend, with extremely high-temperature events increasing and extremely low-temperature events decreasing. Precipitation extremes events also exhibited a slightly increasing trend. (3) NDVI was overall positively correlated with the climate extremes indices (CEIs), although both positive and negative correlations spatially coexisted. (4) The responses of NDVI and climate extremes showed time lag effects and spatial differences in the growing period. (5) Precipitation extremes were closely related to NDVI than temperature extremes according to Lasso modeling results. This study provides a reference for understanding vegetation variations and their response to climate extremes in arid regions.

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

Water ◽  
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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