Global monitoring of interannual changes in vegetation activities using NDVI and its relationships to temperature and precipitation

Kawabata, Ayaka; Ichii, Kazuhito; Yamaguchi, Yasushi

doi:10.1080/01431160119381

Cited by 256 publications

(96 citation statements)

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“…This is consistent with results from previous studies undertaken in similar latitudes at global and regional scales. The reason for the higher change rates of forest vegetation activity in spring corresponds to general upward trends in winter and spring temperatures (Kawabata et al, 2001;Tucker et al, 2001;Xiao and Moody, 2004). Cropland, cropland mosaic, irrigated cropland, savanna and wetland, also showed high values of the trend in spring NDVI over 1982 to 2003, with a total increase of 14.…”

Section: Trends In Seasonal Ndvimentioning

confidence: 98%

Inter-Annual Changes in Vegetation Activities and Their Relationship to Temperature and Precipitation in Central Asia from 1982 to 2003

Propastin

Kappas²,

Muratova³

2008

J ENV INFORM

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ABSTRACT. We analyzed inter-annual trends in annual and seasonal vegetation activities in Central Asia from 1982 to 2003 and their correlation to climate variability using the NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) dataset and a gridded climate dataset. The results indicate a significant increase in NDVI with a value of 11.35% over the growing season during the 22-year period. Totalled over the entire vegetated area, about 35% of all pixels exhibited significant upward trend in growing season NDVI. We found that NDVI increase in spring was the main contributor to the general upward trend, the spring NDVI increased in more than 50% of all pixels and showed an average value of 13.58%. Correlation analysis indicated a gradual rise in temperature as the only factor controlling trend in spring NDVI. Significant increase in vegetation activity was also identified for summer season, but its amplitude (9.23%) and comprising area (25.13% of all vegetated pixels) were less than for spring. Downward trends in growing season NDVI occurred in 2.17% of the total vegetated area. The greening trends of spring, growing season and summer NDVI strongly related with the climatic parameters: for each land cover type, we found significant correlation with spring temperature and total precipitation; 75% of all upward trends in growing season NDVI were explained by the combination of these both variables. We found that the NDVI trends and their climatic correlates demonstrate great spatial variability at the scale of individual land cover types and at per-pixel scale and proofed that the land use change caused by the constitutional change in the 1991 has substantial control on the vegetation trends. Increased vegetation growth indicated through the analysis of NOAA AVHRR NDVI time-series suggests an increasing carbon stock in biomass of ecosystems in Central Asia.

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Section: Trends In Seasonal Ndvimentioning

confidence: 98%

Inter-Annual Changes in Vegetation Activities and Their Relationship to Temperature and Precipitation in Central Asia from 1982 to 2003

Propastin

Kappas²,

Muratova³

2008

J ENV INFORM

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“…La mayoría de los cambios han sido causados por actividad humana, particularmente por la deforestación (Achard et al, 2002;DeFries et al, 2002;Giglio et al, 2006) y los incendios forestales (Riaño et al, 2007), por otra parte, el abandono rural y la consiguiente marginalización de algunas regiones ha contribuido al proceso de recuperación vegetal (Vicente-Serrano et al, 2004;Vicente-Serrano et al, 2006a, b;Lasanta y Vicente-Serrano, 2007;Sluiter y de Jong, 2007;Alatorre et al, 2011;Lasanta y Vicente-Serrano, 2012). Además, diferentes estudios han mostrado como las actuales tendencias climáticas pueden favorecer el incremento en la actividad vegetal sobre distintos ecosistemas del mundo (Myneni et al, 1998;Kawabata et al, 2001;Lucht et al, 2002), o descenso (Maselli, 2004;Sarris et al, 2007;Vicente-Serrano et al, 2012) de la actividad vegetal. Por ejemplo, en la región mediterránea han surgido diversos patrones en la dinámica vegetal.…”

Section: Introductionunclassified

Evolución de la dinámica vegetal mediante una serie de imágenes Landsat TM(1986-2011): región central de Chihuahua, México

Cejudo

Miramontes-Beltrán²,

García-Peña³

et al. 2014

CIG

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“…Several studies have reported relationships between vegetation indices and precipitation and temperature [3,[9][10][11][12][13][14]. However, most of these studies focused solely on either precipitation or temperature for vegetation models, thereby resulting in low precision and low correlation coefficients between vegetation indices and climatic variables [14].…”

Section: Introductionmentioning

confidence: 99%

Modeling NDVI Using Joint Entropy Method considering Hydro-Meteorological Driving Factors in the Middle Reaches of Hei River Basin

Zhang¹,

Su²,

Singh³

et al. 2017

Preprint

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Terrestrial vegetation dynamics are closely influenced by a multitude of factors.This study investigated the relationships between vegetation patterns and their main influencing factors. The joint entropy method was employed to evaluate the dependence between normalized difference vegetation index (NDVI) and coupled variables in the middle reaches of Hei River basin. Based on the spatial distribution of mutual information, the whole study area was divided into five sub-regions. In each sub-region, nested statistical models were applied to model the NDVI on the grid and regional scales, respectively. Results showed that the annual average NDVI increased with a rate of 0.005/a in recent 11 years. In the desert regions, the NDVI increased significantly with an increase in precipitation and temperature, and high accuracy of retrieving NDVI model was obtained by coupling precipitation and temperature, especially in sub-region I. In the oasis regions, groundwater was also an important factor driving vegetation growth, and the rise of groundwater level contributed to the growth of vegetation. However, the relationship was weaker in artificial oasis regions (sub-region III and sub-region V) due to the influence of human activities, such as irrigation. The overall correlation coefficient between the observed NDVI and modeled NDVI was observed to be 0.97. Outcomes of this study are suitable for ecosystem monitoring, especially under the realm of climate change.Further studies are necessary and should consider more factors, such as runoff and irrigation.

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Global monitoring of interannual changes in vegetation activities using NDVI and its relationships to temperature and precipitation

Cited by 256 publications

References 0 publications

Inter-Annual Changes in Vegetation Activities and Their Relationship to Temperature and Precipitation in Central Asia from 1982 to 2003

Inter-Annual Changes in Vegetation Activities and Their Relationship to Temperature and Precipitation in Central Asia from 1982 to 2003

Evolución de la dinámica vegetal mediante una serie de imágenes Landsat TM(1986-2011): región central de Chihuahua, México

Modeling NDVI Using Joint Entropy Method considering Hydro-Meteorological Driving Factors in the Middle Reaches of Hei River Basin

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