On Mar. 22 last year, a fire that started on a low mountain in Uiseong, North Gyeongsang Province, raced northeast on gale-force winds of 10 meters per second. The fierce flames swept through five cities and counties in northern North Gyeongsang (Uiseong, Andong, Cheongsong, Yeongyang, Yeongdeok), as well as Sancheong and Hadong in South Gyeongsang, and Ulju in Ulsan within a week. The Korea Forest Service provisionally tallied about 104,788 hectares (1,047 square kilometers) burned in the massive wildfire. That is about 1.73 times the size of Seoul and more than four times the burn area of the 2000 East Coast wildfires (23,794 hectares). The blaze that swept across Yeongnam left 33 people dead and 45 injured. More than 4,000 buildings, including dwellings and factories, burned, and national heritage sites such as the millennium-old Gounsa Temple in Uiseong and Manhyujeong, a famed scenic spot in Andong, were destroyed or partially burned.
A false-color satellite image taken on Apr. 4, 2025, by Landsat 9, a NASA Earth observation satellite, laid bare the devastation. Brown and red burn scars stretching 80 kilometers from Uiseong through Andong, Cheongsong, Yeongyang, and Yeongdeok to the East Coast are visible at a glance. The government declared more than 20 locations in the area special disaster zones and began recovery efforts, but even now, a year later, more than 3,800 of the 5,545 displaced residents are still living in temporary housing.
To mark one year since the Yeongnam wildfires, Naraspace's Earth Paper team, a domestic satellite company, on the 20th released a three-dimensional analysis captured over the Korean Peninsula of the scars of the fires and the current state of recovery after a year.
An analysis of images from the European Space Agency (ESA) Copernicus Sentinel-2 satellite and NASA's Landsat 9 found that while some areas saw ecological recovery over the year after the fires were extinguished, most high-altitude burn areas have shown only minimal recovery to date. In particular, in Sancheong, Uiseong, and Yeongdeok, the loss of forests increased the risk of soil erosion on steep slopes, raising concerns about "secondary damage."
In the wake of the flames, pixels tell the speed of recovery
The pace of recovery in wildfire-damaged areas is not easily visible to the eye. Satellite cameras capture invisible light—infrared, ultraviolet, and visible light reflected or absorbed by the surface—and by using these properties of light, changes on the ground can be detected. Among these, the normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) provide precise numerical views of the ecosystem's self-regeneration capacity that the human eye cannot see. NDVI uses the principle that healthy vegetation absorbs red light during photosynthesis and strongly reflects near-infrared to quantify forest vigor and post-fire recovery speed. NBR provides wildfire damage levels by using the difference in reflectance between near-infrared and shortwave infrared. It draws on the principle that in burned areas, all trees and shrubs are destroyed and moisture is completely evaporated, dramatically altering shortwave infrared reflectance.
According to the analysis team, Ulju County in Ulsan, where the fire started on Mar. 22 last year and burned 379.3 hectares, showed the fastest recovery in satellite analysis data. In the damage assessment right after the fire, about 300 hectares, or roughly 79% of the total affected area, were classified as "low" intensity. In this analysis, vegetation around Daunsan and Bulgwangsan peaked in NDVI in Aug. of the same year, five months later, demonstrating explosive vitality. A higher value means vegetation is healthier. However, even in summer, when vegetation should be lush, areas near farmland showed lower-than-normal NDVI values. This suggests that in flatlands with more human activity, unlike mountainous areas, ecosystem recovery is progressing more slowly. This analysis showed clear signs that heavily affected areas in Ulju at the onset of the wildfire have entered a recovery phase.
Sancheong in South Gyeongsang showed a more complex recovery pattern than Ulju. During last year's wildfire, a total of 2,163.8 hectares in Sancheong were affected. While "low" intensity made up the largest share at 1,751.3 hectares, "high" intensity at 138 hectares and "medium" intensity at 274.5 hectares were widely distributed, creating differences in restoration conditions by area.
The satellite image analysis found that trees and grasses increased gradually across Sancheong County. But recovery speed varied by location. By Aug. last year, most vegetation around Gugoksan on the south side of Jirisan Mountain had returned to form. In contrast, the southern slope extending toward Hadong County continued to show low NDVI values, which indicate forest density. This is interpreted as a recovery process that is hard to explain, with both wildfire intensity and local growth conditions at play.
Contrasts between healthy vegetation and scorched terrain produced regional differences in NBR values, which indicate fire severity. While forests around Gugoksan have mostly been recovering since the fires were extinguished, affected areas extending toward Hadong County have remained unable to reestablish trees and grasses. This suggests that at the time of the wildfire, intense heat either completely stripped moisture from the soil or destroyed vegetation substructures.
Data from Sancheong County revealed that vegetation recovery is determined not merely by seasonal patterns but by topographic conditions and burn intensity. Compared with the same period the previous year, NBR values followed a similar pattern over time, but NDVI showed greater volatility by area, indicating a recovery process that cannot be explained by simple seasonal patterns alone.
Uiseong and Yeongdeok, an 84,000-hectare gash
An analysis found that last year's Yeongnam wildfires burned a total of 84,404.3 hectares in Uiseong and Yeongdeok in North Gyeongsang. That is about 1.4 times the size of Seoul. The situation was even more severe, with "high" intensity damage covering 11,260.9 hectares and "medium" intensity reaching 17,275.9 hectares.
In Uiseong, vegetation growth activity increased and trended upward in Aug. compared with April, right after the wildfire. But the figures were markedly lower than in the same period the previous year. In Uiseong, high-intensity damage was not concentrated in specific zones but distributed relatively evenly, indicating the overall ecosystem came under simultaneous, widespread stress.
While "low" intensity areas showed increasing NBR values over time, indicating progress in restoration, "medium" and "high" intensity zones were widely dispersed, resulting in an overall vegetation recovery pace that was relatively slower than in other affected regions. This means reinsurers and national disaster management authorities will need to continue managing the area for years to come.
Landslide risk zones grow after the Sancheong wildfire
Satellite imagery captures not only the loss of forests but also the internal wounds suffered by human communities without embellishment. The analysis team overlaid 100-meter resolution dwelling grid data from the government's Statistical Geographic Information Service (SGIS) with satellite damage zones and found that last year's wildfire damage extended beyond forests to seriously encroach on people's homes.
During last year's wildfire, Ulju County in Ulsan saw flames spread mainly through mountainous areas, resulting in almost no damage to residential zones.
But in Sancheong County, 40 residences out of a total of 14,537 fell within the damage range. In particular, in the broad damage zone stretching from Uiseong County to Yeongyang County in North Gyeongsang, 4,436 out of a total of 117,071 houses and buildings were tallied as affected.
Satellite data thus serve as a powerful tool to proactively identify damage even in remote villages where on-site surveys are difficult. They are especially valuable in predicting secondary disasters and in post-event verification. On slopes stripped of trees and grasses by fire, rain robs soil of cohesion, turning them into masses of mud.
Using the difference in normalized burn ratio (dNBR) and terrain slope, the analysis team confirmed that landslide-prone areas emerged in the burn zones after the Yeongnam wildfires. The difference in NBR values before and after the fire reveals burn severity.
The Ulsan area had lower risk thanks to relatively gentle slopes. But Sancheong, with steep slopes and valleys, was classified as high risk. In fact, when a record 793 millimeters of rain fell in July last year, four months after the wildfire, landslides occurred in the vulnerable zones identified by this analysis.
This illustrates how denuded ground can turn into a time bomb when heavy rains come. In the region connecting Uiseong and Yeongdeok, potential risks are still being identified, especially on steep slopes adjacent to residential areas. Proactive preventive management is urgently needed.
Satellite imagery goes beyond simple labels like "under restoration" or "completed" for post-wildfire conditions, providing concrete spatial intelligence on where recovery is proceeding smoothly and where new risks are emerging. Such data give policymakers practical, specific grounds for setting restoration priorities and allocating budgets. For reinsurers, they enable a more realistic assessment of potential future losses by reflecting residual risks even after recovery.
References
Naraspace Earth Paper, https://ep.naraspace.com/
With advances in low-cost launch vehicles and small satellite technology, an era has arrived in which we can watch events on Earth in real time. Satellites are now used not only for defense but across diverse domains, including disaster and hazard monitoring, claims adjustment, and industry trend analysis. Economy Chosun, in step with the space economy era, is serializing Space Journalism series titled "The world seen by satellites" and "The economy seen by satellites," in collaboration with Naraspace, a domestic satellite service corporation, integrating satellite imagery data into coverage of defense, industry, economy, society, and international affairs.