152 Hotspots Detected in Indonesia in the Last 24 Hours (Sunday, December 21, 2025)

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Irfan Fadhlurrahman 21/12/2025 11:36 WIB
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10 Provinces with the Most Hotspots in Indonesia in the Last 24 Hours
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Based on the SiPongi forest and land fire monitoring system of the Ministry of Environment and Forestry (KLHK), monitoring in the last 24 hours showed 152 hotspots detected in Indonesia. This number of hotspots increased by 29 points compared to the previous period.

This data is the result of Terra/Aqua, SNPP, and NOAA satellite imagery accessed on Sunday (12/21/2025) at 11:36 AM WIB. Of the 152 hotspots detected, 1 point has a high hotspot confidence level, 149 points are at a medium scale, and 2 points are at a low scale.

Hotspot confidence levels are divided into 3 scales. Low scale has a range of 0 - 29, medium scale 30 - 79, and high scale 80 - 100. The higher the hotspot confidence level, the higher the likelihood of forest and land fires occurring in a particular area.

(Read: Number of Slightly Damaged Houses Due to Natural Disasters in Indonesia 2015-2024)

The highest number of hotspots were detected in North Maluku with 35 points. South Sulawesi ranks second with 14 hotspots. Central Sulawesi is in third position with 12 hotspots.

A total of 11 hotspots were detected in West Kalimantan, followed by Southeast Sulawesi with 10 hotspots, while West Java and South Kalimantan each had 7 and 7 hotspots detected.

A hotspot is a coordinate point of an area that has a higher surface temperature than its surroundings, and is not the number of forest and land fire incidents.

However, a large number of hotspots clustered in an area indicates the occurrence of forest and land fires. This means that hotspot data from remote sensing satellite detection is still the most effective in monitoring forest and land fires for large areas.

(Read: Number of Injuries Due to Natural Disasters in Indonesia 2015-2024)

"Disclosure: This is an AI-generated translation of the original article. We strive for accuracy, but please note that automated translations may contain errors or slight inconsistencies."

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