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Modelling vegetation greenness responses to climate variability in a Mediterranean terrestrial ecosystem
Nazzareno Diodato1, Gianni Bellocchi
1Monte Pino Met Research Observatory, TEMS Network-Terrestrial Ecosystem Monitoring Sites (FAO-United Nations), via Contrada Monte Pino, 82100 Benevento, Italy. scodalabdiodato@gmail.com
Environmental Monitoring and Assessment
|November 7, 2007
Summary
This study models vegetation greenness using climate data, linking rainfall and temperature to the Normalized Difference Vegetation Index (NDVI). The findings reveal a positive NDVI trend over time, correlating with rising air temperatures.
Area of Science:
- Environmental Science
- Climate Science
- Remote Sensing
Background:
- Vegetation greenness is crucial for ecosystem health and is often monitored using the Normalized Difference Vegetation Index (NDVI).
- Understanding the relationship between climate variables and NDVI is essential for ecological and agricultural management.
- Previous studies have established links between climate and vegetation, but localized modeling with long-term data is valuable.
Purpose of the Study:
- To develop and validate a model linking monthly climate data (rainfall, temperature) to satellite-derived NDVI.
- To reconstruct historical NDVI data for a specific region in Southern Italy.
- To analyze long-term NDVI trends and their correlation with climate change indicators.
Main Methods:
- A statistical model was created using multi-year climate and NDVI data (1996-2004) from Monte Pino hill, Southern Italy.
- The model was validated by comparing simulated NDVI with satellite-derived NDVI, achieving high accuracy (modeling efficiency ~0.80).
- The validated model was used to extend the NDVI data series backward to 1972.
Main Results:
- The model successfully linked vegetation greenness (NDVI) to climate patterns, demonstrating resilience despite agricultural disturbances.
- A significant positive trend in NDVI was observed over the long term (1972-1995).
- This positive NDVI trend was found to be consistent with the recorded increase in local air temperature.
Conclusions:
- Climate variables, particularly temperature and rainfall, are strong predictors of vegetation greenness (NDVI) at a local scale.
- The developed model provides a reliable method for reconstructing historical vegetation data.
- The study suggests that rising temperatures may be contributing to increased vegetation greenness in the studied region.
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