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This study proposed Classification Tree Analysis (CTA) for automatic smoke detection using Himawari_8 Satellite data over the Maritime Continent of Sumatera and Borneo Islands in Indonesia. Two timestamps of the Region of Interest (ROI) sampling, including Cumulonimbus (Cb) top, low-middle cloud, smoke, bare soil, cirrus cloud, vegetation, and water classes, were used as the input to determine the best CTA models. The CTA model classification was supervised using a collection of 21 single and transformation bands. The study also employed and compared two impurity measures, the Gini Index, and Entropy. The responses of the output of 4 CTA models (Entropy-09, Gini-09, Entropy-10, and Gini-10) were spatially, temporally, and statistically analysed. Furthermore, the CTA models were validated using METAR data (weather airport observation), with results showing that Entropy-10 have the highest Overall Accuracy value of 0.79, and lowest False Alarm Rate Value of 0.11. The computing time shows that Entropy-9 is the fastest with a mean of 19.8 s, followed by entropy-10 with 20.7 s. The accuracy assessment, spatial and temporal analyses, and computing process revealed that the Entropy-10 was the best model. The results of the CTA Entropy-10 are implemented over a small area, such as an airport to justify the work of weather observers and forecasters. This is often based on the objective satellite-based smoke detection product. Furthermore, they serve as information for aviation users in improving their situational awareness of adverse weather conditions related to safety.

Smoke can reduce the airport’s visibility and is related to the aviation safety and efficiency. Low visibility has potential safety hazard, such GA-152 crashed in 1997, and thus there is a need to find out the visibility characteristics in airports over Sumatra and Borneo Island caused by 2015 forest fire. This research aims to analyse the spatiotemporal visibility characteristics over airports in Sumatera and Borneo Island using flight rule visibility below minima criteria and hazard probability. The analysis of smoke was characterized using visibility severity index (VSI) that is a function of visibility severity class and its probability level. Spatiotemporal analysis of severity index combined with hotspot and wind numerical weather model indicates that the worst impact visibility occurred in September and October 2015. The lowest visibility was occured over night until afternoon time period. The spread of VSI impact has a tendency to northward and northwestward. The very high VSI levels occurred at airports such: WIJJ (Jambi), WIBB (Pekanbaru), WAGG (Palangkaraya) which were impacted up to 70% of flight operations time with IFR visibility below minima; while the WIOS (Susilo-Sintang), which operates only on VFR, experienced about 92% of VFR visibility below minima at smoke climax period.