Quantifying influences of natural factors on vegetation NDVI changes based on geographical detector in Sichuan, western China

Peng, Wenfu; Kuang, Tingting; Tao, Shuai

doi:10.1016/j.jclepro.2019.05.355

Cited by 240 publications

(136 citation statements)

References 18 publications

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“…The calculation of both the indicators is based on land use and is largely subject to land use change. In addition, in spatial terms, indicators of ecosystem health show significant differences, and global NDVI is significantly affected by climate factors (Munavar, Carsten, Christian, Dietrich, & Nicole, 2018; Peng, Kuang, & Tao, 2019; Yang et al, 2019; Zheng et al, 2018); as the climate changes, so does the global EV.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of temporal and spatial changes of global ecosystem health

et al. 2020

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Understanding the spatial distribution pattern and driving factors behind ecosystem health is beneficial to ecosystem management and restoration. However, the literature shows little in‐depth exploration of regional heterogeneity and the factors that influence ecosystem health on a global scale. This study assesses global ecosystem health for the period 2000–2015 based on the vigor, organization, resilience, and service (VORS) model, and it explores the factors that influence regional differences in ecosystem health. Our results show that: (a) regions with high levels of ecosystem health are distributed mainly near the Equator and within the north–south regression line (0°N–13°N, 0°S–18°S); (b) seven critical zones with high levels of ecosystem health are identified (13°N–18°S, 45°N–65°N, 35°S–56°S, 47°W–80°W, 120°W–130°W, 8°E–37°E, 92°E–157°E); and (c) average annual precipitation and soil moisture play a key role in ecosystem health globally, with correlations of 0.574 and 0.399, respectively. Socioeconomic factors act as bridges, linking and reinforcing the influence of other factors in areas with medium to low levels of ecosystem health. Our study contributes to better understanding of ecosystem health, fills gaps in global ecosystem health diagnosis, and provides reference points for management and recovery of ecosystems.

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Section: Resultsmentioning

confidence: 99%

Evaluation of temporal and spatial changes of global ecosystem health

et al. 2020

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“…However, using only linear relationships for very complex (and non-linear) processes is too simple for serious study. To clarify any correlation (including non-linear relationships) between impact factors, a geographical detector model has been developed to explore potential factors or explanatory variables from a spatial perspective [18], and accurately discern the compounding effect of various possible influences on vegetation change. In addition to climate, anthropogenic activity strongly affects the structure and function of terrestrial ecosystems, vegetation responses are a product of these effects.…”

Section: Introductionmentioning

confidence: 99%

NDVI Indicates Long-Term Dynamics of Vegetation and Its Driving Forces from Climatic and Anthropogenic Factors in Mongolian Plateau

Guo

Wang

et al. 2021

Remote Sensing

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In recent years, global warming and intense human activity have been responsible for significantly altering vegetation dynamics on the Mongolian Plateau. Understanding the long-term vegetation dynamics in this region is important to assess the impact of these changes on the local ecosystem. Long-term (1982–2015), satellite-derived normalized difference vegetation index (NDVI) datasets were used to analyse the spatio-temporal patterns of vegetation activities using linear regression and the breaks for additive season and trend methods. The links between these patterns and changes in temperature, precipitation (PRE), soil moisture (SM), and anthropogenic activity were determined using partial correlation analysis, the residual trends method, and a stepwise multiple regression model. The most significant results indicated that air temperature and potential evapotranspiration increased significantly, while the SM and PRE had markedly decreased over the past 34 years. The NDVI dataset included 71.16% of pixels showing an increase in temperature and evaporation during the growing season, particularly in eastern Mongolia and the southern border of the Inner Mongolia Autonomous region, China. The proportion indicating the breakpoint of vegetation dynamics was 71.34% of pixels, and the trend breakpoints mainly occurred in 1993, 2003, and 2010. The cumulative effects of PRE and SM in the middle period, coupled with the short-term effects of temperature and potential evapotranspiration, have had positive effects on vegetation greening. Anthropogenic factors appear to have positively impacted vegetation dynamics, as shown in 81.21% of pixels. We consider rapid economic growth, PRE, and SM to be the main driving factors in Inner Mongolia. PRE was the main climatic factor, and combined human and livestock populations were the primary anthropogenic factors influencing vegetation dynamics in Mongolia. This study is important in promoting the continued use of green projects to address environmental change in the Mongolian Plateau.

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“…As a major component of terrestrial ecosystems, vegetation plays an important role in material cycling and energy flows, and provides irreplaceable service functions that maintain the wellbeing of our planet and all the creatures that inhabit it. These function services include food provision, climate regulation, carbon sequestration, timber production, biodiversity preservation, and soil protection [1][2][3][4][5][6][7][8]. Vegetation growth affects the ecological balance, the terrestrial carbon cycle, water circulation, and other biochemical processes [2,9].…”

Section: Introductionmentioning

confidence: 99%

Spatial–Temporal Vegetation Dynamics and Their Relationships with Climatic, Anthropogenic, and Hydrological Factors in the Amur River Basin

et al. 2021

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Information about the growth, productivity, and distribution of vegetation, which are highly relied on and sensitive to natural and anthropogenic factors, is essential for agricultural production management and eco-environmental sustainability in the Amur River Basin (ARB). In this paper, the spatial–temporal trends of vegetation dynamics were analyzed at the pixel scale in the ARB for the period of 1982–2013 using remotely sensed data of long-term leaf area index (LAI), fractional vegetation cover (FVC), and terrestrial gross primary productivity (GPP). The spatial autocorrelation characteristics of the vegetation indexes were further explored with global and local Moran’s I techniques. The spatial–temporal relationships between vegetation and climatic factors, land use/cover types and hydrological variables in the ARB were determined using a geographical and temporal weighted regression (GTWR) model based on the observed meteorological data, remotely sensed vegetation information, while the simulated hydrological variables were determined with the soil and water assessment tool (SWAT) model. The results suggest that the variation in area-average annual FVC was significant with an increase rate of 0.0004/year, and LAI, FVC, and GPP all exhibited strong spatial heterogeneity trends in the ARB. For LAI and FVC, the most significant changes in local spatial autocorrelation were recognized over the Sanjiang Plain, and the low–low agglomeration in the Sanjiang Plain decreased continuously. The GTWR model results indicate that natural and anthropogenic factors jointly took effect and interacted with each other to affect the vegetated regime of the region. The decrease in the impact of precipitation to vegetation growth over the Songnen Plain was determined as having started around 1991, which was most likely attributed to dramatic changes in water use styles induced by local land use changes, and corresponded to the negative correlation between pasture areas and vegetation indexes during the same period. The analysis results presented in this paper can provide vital information to decision-makers for use in managing vegetation resources.

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Quantifying influences of natural factors on vegetation NDVI changes based on geographical detector in Sichuan, western China

Cited by 240 publications

References 18 publications

Evaluation of temporal and spatial changes of global ecosystem health

Evaluation of temporal and spatial changes of global ecosystem health

NDVI Indicates Long-Term Dynamics of Vegetation and Its Driving Forces from Climatic and Anthropogenic Factors in Mongolian Plateau

Spatial–Temporal Vegetation Dynamics and Their Relationships with Climatic, Anthropogenic, and Hydrological Factors in the Amur River Basin

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