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Burned area forecasting using past burned area records and Southern Oscillation Index for tropical Africa (1981-1999)
Authors:D Riaño  JA Moreno Ruiz  J Barón Martínez
Affiliation:a Center for Spatial Technologies and Remote Sensing (CSTARS), University of California, 250-N, The Barn, One Shields Avenue, Davis, CA 95616-8617, USA
b Departamento de Geografía, Universidad de Alcalá, Colegios 2, E-28801 Alcalá de Henares, Madrid, Spain
c Departamento de Lenguajes y Computación, Universidad de Almería, 04120 Almería, Spain
Abstract:An 18-year time series of monthly NOAA-AVHRR Pathfinder Land burned area was analyzed for the region of tropical Africa, from July 1981 to June 1999. The transition period between NOAA-11 and NOAA-14 platforms from July 1993 to June 1995 was not included due to missing and outlier data. Stability of the time series was addressed for the input variables in the burned area algorithm, reflectance and temperature channels.A Seasonal AutoRegressive Integrated Moving-Average (SARIMA) model was developed for forecasting potential burned area. The SARIMA model identified an autoregressive regular term with 1-month lag and an autoregressive 12-month seasonal term with one season (12 months) component. A cross-correlation between Southern Oscillation Index (SOI) and burned area was statistically significant predictor variable in a time series with 20-month lag. Results show that the SARIMA model with this predictor improved both, fitting and forecasting, residual variance, by 4.1% and 5.6%, respectively, thereby, demonstrating potential relationship between SOI and burned area for the study region. Forecasting was estimated by considering only the first 16 years of the monthly burned area in the time series, from July 1981 to June 1997. The prediction for the following 24 months (from July 1997 to June 1999) was within the 95% confidence level indicating that the forecast was a valid characterization of the modeled process.
Keywords:Global burned area  Southern Oscillation Index  NOAA-AVHRR Pathfinder Land  Forecast  SARIMA
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