Comparative Analysis of Fire Detection Algorithms in North China

Guo, Chang; Liu, Ke; Li, Guohong; Liu, Yuanping; Wang, Yujing

doi:10.1007/978-3-030-56488-9_14

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…In recent years, it has been widely used in forest-fire analysis. Some studies have analyzed forest-fire characteristics and spatial-distribution patterns [23][24][25]. For example, a study using fire-spot statistics and MODIS products applied spatial-statistical methods to describe the spatial distribution and temporal variation of fires in different regions [26].…”

Section: Introductionmentioning

confidence: 99%

Study on Spatial-Distribution Characteristics Based on Fire-Spot Data in Northern China

Tian¹,

Wu²,

Bian³

et al. 2022

Sustainability

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Forest fires are an important disturbance in forest ecosystems and can affect the structure and function of forests. These must be mitigated, to eliminate the associated harmful impacts on forests and the environment as well as to have a healthy and sustainable environment for wildlife. The northern region of China (Heilongjiang, Jilin, Liaoning, and Hebei provinces) is one of the important deciduous broadleaf forests and boreal-forest ecosystems in China. Based on the monitoring of historical remote-sensing products, this study analyzes and explores the spatial- and temporal-distribution patterns of forest fires in Northern China in 2020 and 2021, providing a strong scientific basis for forest-fire prevention and management. The number of monthly forest fires in the northern region in 2020 and 2021 was counted, to obtain seasonal and interannual forest-fire variation. The results show that the number of forest fires occurring in Heilongjiang, Jilin, and Liaoning provinces in 2021 is smaller than that in 2020. The occurrence of forest fires is, mainly, concentrated in spring and autumn, especially in April and October. The number of forest fires that occurred in Hebei Province in 2020 and 2021 was almost the same, showing a slight increasing trend, especially with more growth in February. It is worth noting that Heilongjiang Province is the region with the highest number of forest fires, regardless of the comparison of the total number of forest fires in two years or the number of forest fires in a single year. Spatial-clustering analysis (Ripley’s K) was used to analyze the spatial-distribution pattern of forest fires, in each province of northern China, and the results showed that forest fires were significantly aggregated in all four provinces. The experimental analysis conducted in this paper can provide local forest managers and firefighting agencies with the opportunity to better plan for fighting fires and improve forest-management effectiveness. Based on mastering the characteristics of the spatial and temporal dynamics of forest fires, fire-prevention publicity and education should be strengthened, and scientific forest-fire-prevention measures should be applied to plan reasonable forest-protection policies. This will contribute towards a healthy and sustainable environment.

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