Corrigendum to "Mann-Kendall Monotonic Trend Test and Correlation Analysis using Spatio-temporal Dataset: the case of Asia using vegetation greenness and climate factors" [MethodsX 5 (2018) 803-807].

[This corrects the article DOI: 10.1016/j.mex.

Long-term trend of and correlation between vegetation greenness and climate variables in Asia based on satellite data.

Satellite data has been used to ascertain trends and correlations between climate change and vegetation greenness in Asia. Our study utilized 33-year (1982-2014) AVHRR-GIMMS (Advanced Very High Resolution Radiometer-Global Inventory Modelling and Mapping Studies) NDVI3g and CRU TS (Climatic Research Unit Time Series) climate variable (temperature, rainfall, and potential evapotranspiration) time series. First, we estimated the overall trends for vegetation greenness and climate variables and analyzed trends during summer (April-October), winter (November-March), and the entire year.

Long-term trend and correlation between vegetation greenness and climate variables in Asia based on satellite data.

Satellite data has been used to ascertain trends and correlations between climate change and vegetation greenness in Asia. Our study utilized 33-year (1982-2014) AVHRR-GIMMS (Advanced Very High Resolution Radiometer - Global Inventory Modelling and Mapping Studies) NDVI3g and CRU TS (Climatic Research Unit Time Series) climate variable (temperature, rainfall, and potential evapotranspiration) time series. First, we estimated the overall trends for vegetation greenness, climate variables and analyzed trends during summer (April to October), winter (November to March), and the entire year.