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

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.

Download Full-text

Coastal Mangrove Response to Marine Erosion: Evaluating the Impacts of Spatial Distribution and Vegetation Growth in Bangkok Bay from 1987 to 2017

Remote Sensing ◽

10.3390/rs12020220 ◽

2020 ◽

Vol 12 (2) ◽

pp. 220 ◽

Cited By ~ 2

Author(s):

Han Xiao ◽

Fenzhen Su ◽

Dongjie Fu ◽

Qi Wang ◽

Chong Huang

Keyword(s):

Spatial Distribution ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Mangrove Ecosystem ◽

Early Growth ◽

Growth Stages ◽

Human Disturbances ◽

Vegetation Growth ◽

Two Parameters ◽

The Impact

Long time-series monitoring of mangroves to marine erosion in the Bay of Bangkok, using Landsat data from 1987 to 2017, shows responses including landward retreat and seaward extension. Quantitative assessment of these responses with respect to spatial distribution and vegetation growth shows differing relationships depending on mangrove growth stage. Using transects perpendicular to the shoreline, we calculated the cross-shore mangrove extent (width) to represent spatial distribution, and the normalized difference vegetation index (NDVI) was used to represent vegetation growth. Correlations were then compared between mangrove seaside changes and the two parameters—mangrove width and NDVI—at yearly and 10-year scales. Both spatial distribution and vegetation growth display positive impacts on mangrove ecosystem stability: At early growth stages, mangrove stability is positively related to spatial distribution, whereas at mature growth the impact of vegetation growth is greater. Thus, we conclude that at early growth stages, planting width and area are more critical for stability, whereas for mature mangroves, management activities should focus on sustaining vegetation health and density. This study provides new rapid insights into monitoring and managing mangroves, based on analyses of parameters from historical satellite-derived information, which succinctly capture the net effect of complex environmental and human disturbances.

Download Full-text

Assessing the impact of seasonal precipitation and temperature on vegetation in a grass-dominated rangeland

The Rangeland Journal ◽

10.1071/rj13098 ◽

2014 ◽

Vol 36 (2) ◽

pp. 185 ◽

Cited By ~ 11

Author(s):

Fang Chen ◽

Keith T. Weber

Keyword(s):

Vegetation Index ◽

Climatic Factors ◽

Growing Season ◽

Vegetation Growth ◽

Factors Affecting ◽

Growing Seasons ◽

Normalised Difference Vegetation Index ◽

Moderate Resolution Imaging Spectroradiometer ◽

The Impact ◽

Precipitation And Temperature

Changes in vegetation are affected by many climatic factors and have been successfully monitored through satellite remote sensing over the past 20 years. In this study, the Normalised Difference Vegetation Index (NDVI), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, was selected as an indicator of change in vegetation. Monthly MODIS composite NDVI at a 1-km resolution was acquired throughout the 2004–09 growing seasons (i.e. April–September). Data describing daily precipitation and temperature, primary factors affecting vegetation growth in the semiarid rangelands of Idaho, were derived from the Surface Observation Gridding System and local weather station datasets. Inter-annual and seasonal fluctuations of precipitation and temperature were analysed and temporal relationships between monthly NDVI, precipitation and temperature were examined. Results indicated NDVI values observed in June and July were strongly correlated with accumulated precipitation (R2 >0.75), while NDVI values observed early in the growing season (May) as well as late in the growing season (August and September) were only moderately related with accumulated precipitation (R2 ≥0.45). The role of ambient temperature was also apparent, especially early in the growing season. Specifically, early growing-season temperatures appeared to significantly affect plant phenology and, consequently, correlations between NDVI and accumulated precipitation. It is concluded that precipitation during the growing season is a better predictor of NDVI than temperature but is interrelated with influences of temperature in parts of the growing season.

Download Full-text

Vegetation Dynamic Changes and Their Response to Ecological Engineering in the Sanjiangyuan Region of China

Remote Sensing ◽

10.3390/rs12244035 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4035

Author(s):

Xiaohui Zhai ◽

Xiaolei Liang ◽

Changzhen Yan ◽

Xuegang Xing ◽

Haowei Jia ◽

...

Keyword(s):

Climate Change ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Positive Impact ◽

Ecological Engineering ◽

Scientific Basis ◽

Vegetation Dynamic ◽

Vegetation Growth ◽

The Impact

In recent decades, the vegetation of the Sanjiangyuan region has undergone a series of changes under the influence of climate change, and ecological restoration projects have been implemented. In this paper, we analyze the spatiotemporal dynamics of vegetation in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from the global inventory modeling and mapping studies (GIMMS) and moderate resolution imaging and spectroradiometer (MODIS) datasets during the past 34 years. Specifically, the characteristics of vegetation changes were analyzed according to the stage of implementation of different ecological engineering programs. The results are as follows. (1) The vegetation in 65.6% of the study area exhibited an upward trend, and in 53.0% of the area, it displayed a large increase, which was mainly distributed in the eastern part of the study area. (2) The vegetation NDVI increased to differing degrees during stages of ecological engineering. (3) The NDVI in the western part of the Sanjiangyuan region is mainly affected by temperature, while in the northeastern part, the NDVI is affected more by precipitation. In the southern part, however, vegetation growth is affected neither by temperature nor by precipitation. On the whole region, vegetation growing is more affected by temperature than by precipitation. (4) The impacts of human activities on vegetation change are both positive and negative. In recent years, ecological engineering projects have had a positive impact on vegetation growth. This study can help us to correctly understand the impact of climate change on vegetation growth, so as to provide a scientific basis for the evaluation of regional ecological engineering effectiveness and the formulation of ecological protection policies.

Download Full-text

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.

Download Full-text

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

Advances in Meteorology ◽

10.1155/2015/725427 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 23

Author(s):

Tingting Ning ◽

Wenzhao Liu ◽

Wen Lin ◽

Xiaoqiang Song

Keyword(s):

Loess Plateau ◽

Human Activities ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Climatic Factors ◽

Time Lag ◽

Annual Maximum ◽

Vegetation Condition ◽

Spatial Changes ◽

Precipitation Changes

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.

Download Full-text

Climate-forced changes of bio-productivity of Belorussian terrestrial ecosystems

Исследования Земли из космоса ◽

10.31857/s0205-96142019677-88 ◽

2019 ◽

pp. 77-88

Author(s):

S. A. Lysenko

Keyword(s):

Climate Change ◽

Carbon Dioxide ◽

Vegetation Index ◽

Precipitation Amount ◽

Terrestrial Ecosystems ◽

Vegetation Period ◽

Climatic Trend ◽

Vegetation Growth ◽

Current Century ◽

The Impact

The spatial and temporal particularities of Normalized Differential Vegetation Index (NDVI) changes over territory of Belarus in the current century and their relationship with climate change were investigated. The rise of NDVI is observed at approximately 84% of the Belarus area. The statistically significant growth of NDVI has exhibited at nearly 35% of the studied area (t-test at 95% confidence interval), which are mainly forests and undeveloped areas. Croplands vegetation index is largely descending. The main factor of croplands bio-productivity interannual variability is precipitation amount in vegetation period. This factor determines more than 60% of the croplands NDVI dispersion. The long-term changes of NDVI could be explained by combination of two factors: photosynthesis intensifying action of carbon dioxide and vegetation growth suppressing action of air warming with almost unchanged precipitation amount. If the observed climatic trend continues the croplands bio-productivity in many Belarus regions could be decreased at more than 20% in comparison with 2000 year. The impact of climate change on the bio-productivity of undeveloped lands is only slightly noticed on the background of its growth in conditions of rising level of carbon dioxide in the atmosphere.

Download Full-text

Urban Fire Severity and Vegetation Dynamics in Southern California

Remote Sensing ◽

10.3390/rs13010019 ◽

2020 ◽

Vol 13 (1) ◽

pp. 19

Author(s):

Lauren E. H. Mathews ◽

Alicia M. Kinoshita

Keyword(s):

Vegetation Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Current Knowledge ◽

Fire Severity ◽

Satellite Image ◽

Burn Severity ◽

Native Vegetation ◽

Riparian Areas ◽

The Impact

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems.

Download Full-text

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.

Download Full-text

Relationship between MODIS Derived NDVI and Yield of Cereals for Selected European Countries

Agronomy ◽

10.3390/agronomy11020340 ◽

2021 ◽

Vol 11 (2) ◽

pp. 340

Author(s):

Ewa Panek ◽

Dariusz Gozdowski

Keyword(s):

Linear Regression ◽

Grain Yield ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Arable Land ◽

Early Spring ◽

European Countries ◽

Yield Prediction ◽

Country Level ◽

Using Data

In this study, the relationships between normalized difference vegetation index (NDVI) obtained based on MODIS satellite data and grain yield of all cereals, wheat and barley at a country level were analyzed. The analysis was performed by using data from 2010–2018 for 20 European countries, where percentage of cereals is high (at least 35% of the arable land). The analysis was performed for each country separately and for all of the collected data together. The relationships between NDVI and cumulative NDVI (cNDVI) were analyzed by using linear regression. Relationships between NDVI in early spring and grain yield of cereals were very strong for Croatia, Czechia, Germany, Hungary, Latvia, Lithuania, Poland and Slovakia. This means that the yield prediction for these countries can be as far back as 4 months before the harvest. The increase of NDVI in early spring was related to the increase of grain yield by about 0.5–1.6 t/ha. The cumulative of averaged NDVI gives more stable prediction of grain yield per season. For France and Belgium, the relationships between NDVI and grain yield were very weak.

Download Full-text

Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

Remote Sensing ◽

10.3390/rs13020323 ◽

2021 ◽

Vol 13 (2) ◽

pp. 323

Author(s):

Liang Chen ◽

Xuelei Wang ◽

Xiaobin Cai ◽

Chao Yang ◽

Xiaorong Lu

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Maximum Temperature ◽

Maximum Temperature Difference ◽

Rapid Urbanization ◽

The Impact ◽

The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

Download Full-text