Characteristics of vegetation activity and its responses to climate change in desert/grassland biome transition zones in the last 30 years based on GIMMS3g

The ecological system of the desert/grassland biome transition zone is fragile and extremely sensitive to climate change and human activities. Analyzing the relationships between vegetation, climate factors (precipitation and temperature), and human activities in this zone can inform us about vegetation succession rules and driving mechanisms. Here, we used Landsat series images to study changes in the normalized difference vegetation index (NDVI) over this zone in the Sahel region of Africa. We selected 6315 sampling points for machine-learning training, across four types: desert, desert/grassland biome transition zone, grassland, and water bodies. We then extracted the range of the desert/grassland biome transition zone using the random forest method. We used Global Inventory Monitoring and Modelling Studies (GIMMS) data and the fifth-generation atmospheric reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5) meteorological assimilation data to explore the spatiotemporal characteristics of NDVI and climatic factors (temperature and precipitation). We used the multiple regression residual method to analyze the contributions of human activities and climate change to NDVI. The cellular automation (CA)-Markov model was used to predict the spatial position of the desert/grassland biome transition zone. From 1982 to 2015, the NDVI and temperature increased; no distinct trend was found for precipitation. The climate change and NDVI change trends both showed spatial stratified heterogeneity. Temperature and precipitation had a significant impact on NDVI in the desert/grassland biome transition zone; precipitation and NDVI were positively correlated, and temperature and NDVI were negatively correlated. Both human activities and climate factors influenced vegetation changes. The contribution rates of human activities and climate factors to the increase in vegetation were 97.7% and 48.1%, respectively. Human activities and climate factors together contributed 47.5% to this increase. The CA-Markov model predicted that the area of the desert/grassland biome transition zone in the Sahel region will expand northward and southward in the next 30 years.

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Land Cover/ Land Use Change and Climate Change in Dhofar Governorate, Oman

International Journal of Geoinformatics ◽

10.52939/ijg.v17i4.1949 ◽

2021 ◽

pp. 41-47

Author(s):

E. Ramadan ◽

T. Al-Awadhi ◽

Y. Charabi

Keyword(s):

Climate Change ◽

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Land Use Changes ◽

Spatial Differentiation ◽

Study Results ◽

Vegetation Activity ◽

The Status ◽

Landsat Satellite

The study of land cover/land use dynamics under climate change conditions is of great significance for improving sustainable ecological management. Understanding the relationships between land cover and land use changes and climate change is thus very important. Understanding the interactive and cumulative effects of climate and land-use changes are a priority for urban planners and policy makers. The present investigation is based on Landsat satellite imagery to explore changes in vegetation spatial distribution between the years from 2000 to2018 The methodology is focused on vegetation indexes tracking and algebraic overlay calculation to analyzed vegetation and their spatial differentiation, land cover change pattern, and the relationships between vegetation dynamics and land cover change in Dhofar Governorate. The study results have revealed that the vegetation vigor is lower in all years compared to 2000. The scene of 2010 shows the minimum vegetation vigor, overall. Besides, the investigation shows a statistical relationship between rainfall and the status of the health of vegetation. Monsoon rainfall has an impact of the growth of vegetation. Between 2012 and 2013, the vegetation activity shows a decreasing trend. The analysis diagnoses an area affected by the worst degree of aridity situated in the southeastern of Dhofar Mountains. Climate change is the main driving factor resulted from both human activities and rainfall fluctuation.

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Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

Scientific Data ◽

10.1038/sdata.2018.28 ◽

2018 ◽

Vol 5 (1) ◽

Cited By ~ 110

Author(s):

Andrew D. Richardson ◽

Koen Hufkens ◽

Tom Milliman ◽

Donald M. Aubrecht ◽

Min Chen ◽

...

Keyword(s):

Climate Change ◽

Vegetation Type ◽

Digital Camera ◽

Region Of Interest ◽

Remote Sensing Data ◽

Climate Change Impacts ◽

Terrestrial Ecosystems ◽

Vegetation Phenology ◽

Phenological Model ◽

Vegetation Activity

Abstract Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.

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Vegetation Changes and Their Response to Global Change Based on NDVI in the Koshi River Basin of Central Himalayas Since 2000

Sustainability ◽

10.3390/su12166644 ◽

2020 ◽

Vol 12 (16) ◽

pp. 6644

Author(s):

Xue Wu ◽

Xiaomin Sun ◽

Zhaofeng Wang ◽

Yili Zhang ◽

Qionghuan Liu ◽

...

Keyword(s):

Climate Change ◽

Land Cover ◽

River Basin ◽

Human Activities ◽

Vegetation Change ◽

Precipitation Trend ◽

Central Himalayas ◽

Annual Minimum Temperature ◽

Vegetation Activity ◽

Koshi River Basin

Vegetation forms a main component of the terrestrial biosphere owing to its crucial role in land cover and climate change, which has been of wide concern for experts and scholars. In this study, we used MODIS (moderate-resolution imaging spectroradiometer) NDVI (Normalized Difference Vegetation Index) data, land cover data, meteorological data, and DEM (Digital Elevation Model) data to do vegetation change and its relationship with climate change. First, we investigated the spatio-temporal patterns and variations of vegetation activity in the Koshi River Basin (KRB) in the central Himalayas from 2000 to 2018. Then, we combined NDVI change with climate factors using the linear method to examine their relationship, after that we used the literature review method to explore the influence of human activities to vegetation change. At the regional scale, the NDVIGS (Growth season NDVI) significantly increased in the KRB in 2000–2018, with significant greening over croplands in KRB in India. Further, the croplands and forest in the KRB in Nepal were mainly influenced by human interference. For example, improvements in agricultural fertilization and irrigation facilities as well as the success of the community forestry program in the KRB in Nepal increased the NDVIGS of the local forest. Climate also had a certain impact on the increase in NDVIGS. A significant negative correlation was observed between NDVIGS trend and the annual minimum temperature trend (TMN) in the KRB in India, but an insignificant positive correlation was noted between it and the total annual precipitation trend (PRE). NDVIGS significantly decreased over a small area, mainly around Kathmandu, due to urbanization. Increases in NDVIGS in the KRB have thus been mainly affected by human activities, and climate change has helped increase it to a certain extent.

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Notable shifting in the responses of vegetation activity to climate change in China

Physics and Chemistry of the Earth Parts A/B/C ◽

10.1016/j.pce.2015.08.008 ◽

2015 ◽

Vol 87-88 ◽

pp. 60-66 ◽

Cited By ~ 14

Author(s):

Aifang Chen ◽

Bin He ◽

Honglin Wang ◽

Ling Huang ◽

Yunhua Zhu ◽

...

Keyword(s):

Climate Change ◽

Vegetation Activity

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Spatial identification and scenario simulation of the ecological transition zones under the climate change in China

Journal of Geographical Sciences ◽

10.1007/s11442-021-1855-7 ◽

2021 ◽

Vol 31 (4) ◽

pp. 497-517

Author(s):

Zemeng Fan

Keyword(s):

Climate Change ◽

Scenario Simulation ◽

Transition Zones ◽

Ecological Transition ◽

Spatial Identification

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Shifts in Dry-Wet Climate Regions over China and Its Related Climate Factors between 1960–1989 and 1990–2019

Sustainability ◽

10.3390/su14020719 ◽

2022 ◽

Vol 14 (2) ◽

pp. 719

Author(s):

Jinqin Xu ◽

Xiaochen Zhu ◽

Mengxi Li ◽

Xinfa Qiu ◽

Dandan Wang ◽

...

Keyword(s):

Climate Change ◽

Agricultural Development ◽

Junggar Basin ◽

Water Shortage ◽

Western China ◽

Dominant Factor ◽

Climate Type ◽

Transition Zones ◽

Wet Climate ◽

Semi Arid

The shifts in dry-wet climate regions are a natural response to climate change and have a profound impact on the regional agriculture and ecosystems. In this paper, we divided China into four dry-wet climate regions, i.e., arid, semi-arid, semi-humid, and humid regions, based on the humidity index (HI). A comparison of the two 30-year periods, i.e., 1960–1989 and 1990–2019, revealed that there was a shift in climate type in each dry-wet climate region, with six newly formed transitions, and the total area of the shifts to wetter conditions was more than two times larger than that of the shifts to drier conditions. Interestingly, the shifts to drier types were basically distributed in the monsoon region (east of 100∘ E) and especially concentrated in the North China Plain where agricultural development relies heavily on irrigation, which would increase the challenges in dealing with water shortage and food production security under a warming climate. The transitions to wetter types were mainly distributed in western China (west of 100∘ E), and most areas of the Junggar Basin have changed from arid to semi-arid region, which should benefit the local agricultural production and ecological environment to some extent. Based on a contribution analysis method, we further quantified the impacts of each climate factor on HI changes. Our results demonstrated that the dominant factor controlling HI changes in the six newly formed transition regions was P, followed by air temperature (Ta). In the non-transition zones of the arid and semi-arid regions, an increase in P dominated the increase of HI. However, in the non-transition zones of the semi-humid and humid region with a more humid background climate, the thermal factors (e.g., Ta, and net radiation (Rn)) contributed more than or equivalent to the contribution of P to HI change. These findings can provide scientific reference for water resources management and sustainable agricultural development in the context of climate change.

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Satellite-Observed Effects from Ozone Pollution and Climate Change on Growing-Season Vegetation Activity over China during 1982–2020

Atmosphere ◽

10.3390/atmos12111390 ◽

2021 ◽

Vol 12 (11) ◽

pp. 1390

Author(s):

Zhaosheng Wang

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Large Scale ◽

Vegetation Index ◽

Growing Season ◽

Ozone Pollution ◽

Vegetation Growth ◽

Vegetation Activity ◽

The Impact

Remote sensing vegetation index data contain important information about the effects of ozone pollution, climate change and other factors on vegetation growth. However, the absence of long-term observational data on surface ozone pollution and neglected air pollution-induced effects on vegetation growth have made it difficult to conduct in-depth studies on the long-term, large-scale ozone pollution effects on vegetation health. In this study, a multiple linear regression model was developed, based on normalized difference vegetation index (NDVI) data, ozone mass mixing ratio (OMR) data at 1000 hPa, and temperature (T), precipitation (P) and surface net radiation (SSR) data during 1982–2020 to quantitatively assess the impact of ozone pollution and climate change on vegetation growth in China on growing season. The OMR data showed an increasing trend in 99.9% of regions in China over the last 39 years, and both NDVI values showed increasing trends on a spatial basis with different ozone pollution levels. Additionally, the significant correlations between NDVI and OMR, temperature and SSR indicate that vegetation activity is closely related to ozone pollution and climate change. Ozone pollution affected 12.5% of NDVI, and climate change affected 26.7% of NDVI. Furthermore, the effects from ozone pollution and climate change on forest, shrub, grass and crop vegetation were evaluated. Notably, the impact of ozone pollution on vegetation growth was 0.47 times that of climate change, indicating that the impact of ozone pollution on vegetation growth cannot be ignored. This study not only deepens the understanding of the effects of ozone pollution and climate change on vegetation growth but also provides a research framework for the large-scale monitoring of air pollution on vegetation health using remote sensing vegetation data.

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