ITHACA Drought Monitoring
- we exploit:
Global 15-day NDVI time-series (5.6 km spatial resolution) derived from the MODIS MOD13C1 Terra CMG dataset. The freely distributed TIMESAT analysis software (Jönsson & Eklundh, 2004) both to correct residual noises in the base NDVI data and to extract phenological metrics (i.e. SSI, Start of Season, End of Season ) from the final fitted NDVI function. - we provide:
Percent deviation from the historical average value (2001 to present) of the integral of the NDVI function describing the vegetation growing season from its start to its end. Unit of measure: %. Date of the vegetation growing season Start and End (SoS, EoS). Reliability coefficient (RC) of SSID. Unit of measure: %. - aim and methodology in brief:
The SSID is an index describing the expected seasonal vegetation productivity, considering both agricultural production and available biomass in pastoral areas. The timely detection of critical conditions in vegetation health and productivity, during a vegetation growing season and before its end, helps to identify agricultural areas where crop failures are likely to occur. It is calculated as a simple percent deviation from the historical average value of the vegetation Seasonal Small Integral parameter (i.e. the baseline). An updated SSID value is added to the historical series every sixteen days, thus each time a new MODIS MOD13C1 becomes available. The SSID is supplied together with a reliability coefficient (RC) which is related to the temporal position of the current observation with respect to the total length of the examined season (i.e., RC reaches 100% once the vegetation growing season has ended). During the descending phase of the vegetation growing season (i.e., once the NDVI curve reach its maximum), the values of the SSID are normally subjected to minimal changes.
- we exploit:
Global precipitation time-series (0.25° spatial resolution) derived from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis estimation, computed at daily intervals (TRMM 3B42 daily data). - we provide:
3 months Standard Precipitation Index (SPI) datasets obtained considering the precipitation cumulated in the 3 months preceding the last day of each interval. - aim and methodology in brief:
The SPI is an index used to characterize meteorological drought: its calculation is based on well-known methodologies (McKee et al.,1993). The near real-time evaluation of precipitation deficits helps to improve the near real-time monitoring of vegetation conditions and the early detection of stress events. In particular, the near real-time SPI analysis permits to identify earlier warnings, by considering climatic conditions before the start of the vegetation growing season. SPI also supports the drought monitoring thanks to the possibility of detecting very critical events characterized by both vegetation productivity and rainfall anomalies.