Predicting next-week VIIRS fire detections in Bolivia: a reproducible benchmark with temporal and geographic evaluation

Abstract

Weekly detection forecasts could help prioritize fire monitoring across Bolivia. We estimate the probability of at least one fire detection by the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite in each 0.05-degree cell during the following 7 days. Primary models were fixed before test scoring. Calibrated LightGBM, a gradient-boosted decision-tree model, reaches 2023-2025 temporal-test average precision (AP) of 0.323 (95% block-bootstrap interval 0.222-0.383), compared with 0.167 for climatology and 0.143 for persistence. Its paired AP gain over climatology is 0.1567 (0.0998-0.2179). A separately selected geographic model reaches AP 0.384 versus 0.181 for persistence in regions excluded from fitting. In the temporal-test population, reviewing the highest-ranked 5% and 10% of eligible area would have covered 38.4% and 55.8% of cell-weeks with detections. Probabilities still overestimate detection frequency in the highest-probability group. Retrospective rainfall provides no clear AP improvement; the primary validation comparisons for vegetation, land cover and their combination are inconclusive. Positive secondary or exploratory intervals do not change those decisions. Evaluation requires complete target and recent-history observations and measures satellite detections, not individual fires, causes or burned area. Prospective evaluation should archive inputs at each weekly issue and measure ranking, calibration and the usefulness of selected cells for monitoring decisions.