Spatiotemporal changes of NDVI and correlation with meteorological factors in northern china from 1985-2015

Pan, Shun; Zhao, Xia; Yue, Yaojie

doi:10.1051/e3sconf/201913101040

Cited by 13 publications

(11 citation statements)

References 9 publications

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“…Some studies have also concluded that there is a correlation between PWV and NDVI [45][46][47]. Some studies have also found that there is a correlation between precipitation and NDVI [48][49][50][51][52], which indirectly proves the correlation between PWV and NDVI. However, the specific change trend of the correlation between PWV and NDVI is different due Some studies have also concluded that there is a correlation between PWV and NDVI [45][46][47].…”

Section: Influence Of Extreme Climate On Vegetation Growthmentioning

confidence: 96%

“…However, the specific change trend of the correlation between PWV and NDVI is different due Some studies have also concluded that there is a correlation between PWV and NDVI [45][46][47]. Some studies have also found that there is a correlation between precipitation and NDVI [48][49][50][51][52], which indirectly proves the correlation between PWV and NDVI. How- The distribution of NDVI variation compared to the last year in August for the period of 2008 to 2015 is presented in Figure 13, from which it can be observed that the NDVI values in 2014 decreased in the northern part while increased in the southern part of Zhejiang province.…”

Section: Influence Of Extreme Climate On Vegetation Growthmentioning

confidence: 99%

See 1 more Smart Citation

An Investigation of Extreme Weather Impact on Precipitable Water Vapor and Vegetation Growth—A Case Study in Zhejiang China

et al. 2021

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Zhejiang province in China experienced an extreme climate phenomenon in August 2014 with temperature rises, sunshine duration decreases, and precipitation increases, particularly, the successive heavy rainfall events occurring from 16 to 20 August 2014 that contributed to this climate anomaly. This study investigates the spatial-temporal variation characteristics of precipitable water vapor (PWV) and the normalized difference vegetation index (NDVI) associated with this phenomenon. Multiple sources of PWV values derived from the Global Positioning System (GPS), Radiosonde (RS) and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim data are used with different spatiotemporal resolutions. The monthly averaged PWV in August 2014 exceeded the 95% percentiles of climatological value (53 mm) while the monthly averaged temperature was less than the 5% percentiles of climatological value (26.6 °C). Before the extreme precipitation, the PWV increased from the yearly averaged value of about 35 mm to more than 60 mm and gradually returned to the August climatological average of 50 mm after the precipitation ended. A large-scale atmospheric water vapor was partially conveyed by the warm wet air current of anticyclones which originated over the South China Sea (25° N, 130° E) and the Western Pacific Ocean. The monthly NDVI variation over the past 34 years (1982–2015) was investigated in this paper and the significant impact of extreme climate on vegetation growth in August 2014 was found. The extreme negative temperature anomaly and positive PWV anomaly are the major climate-driven factors affecting vegetation growth in the north and south of Zhejiang province with correlation coefficients of 0.83 and 0.72, respectively, while the extreme precipitation does not show any apparent impact on NDVI.

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Section: Influence Of Extreme Climate On Vegetation Growthmentioning

confidence: 96%

Section: Influence Of Extreme Climate On Vegetation Growthmentioning

confidence: 99%

An Investigation of Extreme Weather Impact on Precipitable Water Vapor and Vegetation Growth—A Case Study in Zhejiang China

et al. 2021

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“…The mean NDVI was calculated to detect the vegetation variation and its relation to climate change. Spatiotemporal changes of NDVI was studied by Pan et al [8]. Their result show that the annual average of NDVI has an upward trend in northern China.…”

Section: Introductionmentioning

confidence: 98%

“…With the development of remote sensing technology, many high resolution images were used for tea plantation extraction [6,7]. In previous studies, many scholars have studied surface vegetation coverage at different spatial and temporal scales [4] based on time series data and spatiotemporal changes of NDVI [8]. Ning et al [4] analyzed temporal and spatial changes of NDVI and explored the impacts of human activities on the observed NDVI changes on the northern Loess Plateau.…”

Section: Introductionmentioning

confidence: 99%

“…NDVI and its lag time to climatic were analyzed to examine their relation and show the spatial distribution of NDVI values in the growing season and the effects of different climatic factors on NDVI [20]. Pan et al [8] show a higher correlation between NDVI and air temperature in high altitude alpine and plateau areas, while NDVI has a higher correlation with precipitation in grassland and desert grassland areas. The impacts of human activities on the NDVI were investigated in existing studies [11,16].…”

Section: Introductionmentioning

confidence: 99%

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NDVI Variation and Yield Prediction in Growing Season: A Case Study with Tea in Tanuyen Vietnam

Phan

Chen

et al. 2021

Atmosphere

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Tea is one of the most significant cash crops and plays an important role in economic development and poverty reduction. On the other hand, tea is an optimal choice in the extreme weather conditions of Tanuyen Laichau, Vietnam. In our study, the NDVI variation of tea in the growing season from 2009 to 2018 was showed by calculating NDVI trend and the Mann-Kendall analysis to assess trends in the time series. Support Vector Machine (SVM) and Random Forest (RF) model were used for predicting tea yield. The NDVI of tea showed an increasing trend with a slope from −0.001–0.001 (88.9% of the total area), a slope from 0.001–0.002 (11.1% of the total area) and a growing rate of 0.00075/year. The response of tea NDVI to almost climatic factor in a one-month time lag is higher than the current month. The tea yield was estimated with higher accuracy in the RF model. Among the input variables, we detected that the role of Tmean and NDVI is stronger than other variables when squared with each of the independent variables into input data.

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Vegetation response to climate and climatic extremes in northwest Bangladesh: a quantile regression approach

Uddin

Kamal

Shahid

2022

Theor Appl Climatol

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The present study assessed the vegetation response to climate in the water-stressed northwest Bangladesh (NWB). The quantile regression analysis was employed to evaluate the effect of climate and climatic extremes on vegetation. The nonparametric correlation analysis was used to assess the climatic in uence on vegetation for various time lags. Besides, the modi ed Mann-Kendall (MMK) test was conducted to understand the changes in climate and vegetation to anticipate the climate change impacts on vegetation. Satellite estimation of Normalized Difference Vegetation Index (NDVI) and observed rainfall and temperature data collected from ve locations of the study area for the period 1982-2018 was used for this purpose. The results revealed a negative effect of rainfall, a positive impact of maximum temperature on vegetation in monsoon and a positive in uence on minimum temperature on vegetation in winter. Quantile regression analysis revealed a signi cant negative in uence of extreme rainfall and a positive impact of maximum temperature on vegetation for the whole NWB. Overall, the study revealed a greater in uence of temperature than rainfall on vegetation change in the region. The trend analysis revealed a reduction in rainfall (-2.56 mm/decade) and a rise in temperature (0.176ºC/decade), and thus, an increase in vegetation (0.014 per decade). The results indicate the positive effect of climate change on vegetation, positively impacting the environment and water resources in the study area.

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Spatiotemporal changes of NDVI and correlation with meteorological factors in northern china from 1985-2015

Cited by 13 publications

References 9 publications

An Investigation of Extreme Weather Impact on Precipitable Water Vapor and Vegetation Growth—A Case Study in Zhejiang China

An Investigation of Extreme Weather Impact on Precipitable Water Vapor and Vegetation Growth—A Case Study in Zhejiang China

NDVI Variation and Yield Prediction in Growing Season: A Case Study with Tea in Tanuyen Vietnam

Vegetation response to climate and climatic extremes in northwest Bangladesh: a quantile regression approach

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