TY - JOUR
T1 - Evaluation of the Standardized Precipitation Index as an early predictor of seasonal vegetation production anomalies in the Sahel
AU - Meroni, Michele
AU - Rembold, Felix
AU - Fasbender, Dominique
AU - Vrieling, Anton
PY - 2017
Y1 - 2017
N2 - We analysed the performance and timeliness of the Standardized Precipitation Index (SPI) in anticipating deviations from mean seasonal vegetation productivity in the Sahel. Gridded rainfall estimates are used to compute the SPI for 1–6-month timescales, whereas the Z-score of the cumulative value of the Fraction of Absorbed Photosynthetically Active Radiation over the growing season (zCFAPAR) is used as a proxy of seasonal productivity. Results show that the strength of the link varies in space as a function of both the SPI timescale and the timing of the SPI calculation with respect to the vegetative season’s progress. For productivity forecasting, we propose an operational strategy to select per grid cell the SPI timescale and computation time with the highest correlation with zCFAPAR at different moments of the season. The linear relationship between SPI and zCFAPAR is significant for 32–66% of the study area, depending on the timing at which SPI is considered (at 0% and 75% of the seasonal progress, respectively). For these areas, the selected SPI explains on average about 40% of the variance of zCFAPAR and may thus assist in the earlier identification of agricultural drought.
AB - We analysed the performance and timeliness of the Standardized Precipitation Index (SPI) in anticipating deviations from mean seasonal vegetation productivity in the Sahel. Gridded rainfall estimates are used to compute the SPI for 1–6-month timescales, whereas the Z-score of the cumulative value of the Fraction of Absorbed Photosynthetically Active Radiation over the growing season (zCFAPAR) is used as a proxy of seasonal productivity. Results show that the strength of the link varies in space as a function of both the SPI timescale and the timing of the SPI calculation with respect to the vegetative season’s progress. For productivity forecasting, we propose an operational strategy to select per grid cell the SPI timescale and computation time with the highest correlation with zCFAPAR at different moments of the season. The linear relationship between SPI and zCFAPAR is significant for 32–66% of the study area, depending on the timing at which SPI is considered (at 0% and 75% of the seasonal progress, respectively). For these areas, the selected SPI explains on average about 40% of the variance of zCFAPAR and may thus assist in the earlier identification of agricultural drought.
KW - ITC-ISI-JOURNAL-ARTICLE
KW - ITC-HYBRID
U2 - 10.1080/2150704X.2016.1264020
DO - 10.1080/2150704X.2016.1264020
M3 - Article
SN - 2150-704X
VL - 8
SP - 301
EP - 310
JO - Remote sensing letters
JF - Remote sensing letters
IS - 4
ER -