The aim of the project is the development of a global drought detection and monitoring system as support to WFP activities. Drought is a water-related natural hazard with some peculiar characteristics: it has a slow onset, can affect extensive regions and last even many years, with serious impacts on population, first of all reducing food production.
Figure 1 - Overall trends in vegetation greenness for the period 1982-2007: spatial distribution of the regression slopes for monthly NDVI values (June trends, West Africa area).
The method is based on the analysis of a series of drought-related variables and indices, such as NDVI and SPI, obtained mostly from satellite data, in order to define thresholds and triggers suitable for early warnings. Land cover, land use, soil moisture, soil type and other relevant information may be integrated in the system to improve its effectiveness.
The NDVI (Normalized Difference Vegetation Index) is a satellite-based vegetation index, and its monitoring over time allows to detect water stress vegetation conditions. Monthly historical time-series of NOAA AVHRR NDVI data (1982-2007) have been analyzed in order to identify long-term vegetation dynamics and to produce maps about the areas that were subject to increase or reduction in vegetation greenness (see an example in Figure 1). Moreover, the near real-time monitoring of NDVI data allows to detect deviations from identified trends, showing anomalous vegetation conditions, suitable for drought detection purposes (see an example of Vegetation Conditions Map in Figure 2).
Work is in progress for the extension of the treatment of NDVI time-series. In particular, extraction of phenological measures (for example, time of the start of season, time of the end of season, seasonal integral, etc.) from fortnightly NDVI time-series is taken into consideration, using proper open source tools. For this activity, NOAA AVHRR and MODIS NDVI data are used.
Figure 2 - January 2006, Horn of Africa, Vegetation Conditions Map: spatial distribution of the detected NDVI anomalies and deviations.
The SPI (Standardized Precipitation Index) is a meteorological drought index, which requires only precipitation input data. The SPI from one side gives a numerical value offering quantitative information related to the deviation from normal conditions, which can be interpreted as the intensity of a drought spell in case of negative values; on the other side, it allows considering different time scales, related to different drought conditions. Finally, a Web-GIS application will be implemented, devoted to the rapid distribution of the results (maps and graphs) obtained during the different monitoring phases. Moreover, this service will allow users to search, explore and analyse all recorded databases for the project, in order to visualize maps and graphs for customized reports generation.
