An Examination of Relationships Between Vegetation and Rainfall Using Maximum Value Composite AVHRR-NDVI Data

Authors : Murat Karabulut

Pages : 93-101

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Publication Date : 9999-12-31

Article Type : Makaleler

Abstract :Global vegetation monitoring with remotely sensed data has the potential of improving our knowledge about the characteristics and spatial distribution of the earth's land cover. The purpose of this study was to assess vegetation response to different rainfall regimes using bi-weekly MVC (Maximum Value Composite) AVHRR (Advanced Very High Resolution Radiometer) data. The results from this research showed that the NDVI (Normalised Difference Vegetation Index) has the potential for evaluating vegetation state, which is related to seasonal variations in climatic conditions. Extreme climatic events such as droughts and abundant moisture conditions can have a strong impact on vegetation development and can be identified by utilising vegetation indices. Forested areas are less likely to reflect changes in their vegetation state than grassland cover types to different moisture conditions. The relationships between NDVI and rainfall showed that concurrent and the previous two months' rainfall totals have a stronger impact on vegetation state, which suggests that the total rainfall of the past two months still has an effect on vegetation development.
Keywords : remote sensing, AVHRR, NDVI, rainfall, vegetation, lag time