Research on visualization enhancement of FY-3B image for forest fire monitoring based on scale conversion and reconstruction

SU Wei, YIN Junyue, YE Jiangxia, ZHOU Ruliang, WEN Qingzhong, WANG Lei, LI Yuanjie, ZHAO Jun

Journal of Nanjing Forestry University (Natural Sciences Edition） ›› 2026, Vol. 50 ›› Issue (2) : 37-47.

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南京林业大学学报（自然科学版）
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Journal of Nanjing Forestry University (Natural Sciences Edition） ›› 2026, Vol. 50 ›› Issue (2) : 37-47. DOI: 10.12302/j.issn.1000-2006.202408006

Research on visualization enhancement of FY-3B image for forest fire monitoring based on scale conversion and reconstruction

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Abstract

【Objective】This study developed a processing method based on terrain scale conversion and image reconstruction to address the challenges of blurred kilometer-scale satellite imagery and the absence of micro-topography information in forest fire monitoring. Aiming to enhance the clarity and visualization effect of the fire environments in satellite images, thereby supporting rapid-fire information extraction and informed decision-making for fire prevention and suppression.【Method】The study focused on two forest fire events: the “5·17” fire in Ganhe Village, Shuanghe Yi Township, Jinning District, Kunming City, and the “5·18” fire in Yutaizi Mountain, Yongqing Village, Xiaobaihu Town, Luliang County, Qujing City, both occurring in 2019. Utilizing FY-3B satellite imagery and 30 m resolution Digital Elevation Model (DEM) data, terrain units at varying scales were constructed using the point spread function (PSF) and sub-pixel decomposition method. The optimal reconstruction scale was determined through information entropy theory. A weighted Hue, Saturation, Value (HSV) transformation was employed to fuse shaded relief model (SRM) data with FY-3B images. The reconstruction effects of the scaling up and scaling down methods were systematically compared.【Result】(1) The PSF-based scaling up method demonstrated superior performance to conventional interpolation techniques, exhibiting the minimum mean elevation error and RMSE and the highest alignment with original DEM contour lines. (2) Terrain information entropy analysis revealed that the optimal DEM reconstruction scale for the study area was ≤120 m. (3) Reconstructed images at multiple scales significantly improved the visualization of the original 1.1 km resolution FY-3B imagery, effectively correcting anti-stereo phenomena and enhancing the representation of terrain details in fire environments. (4) The 15 m scale fused image exhibited the best performance in quantitative metrics, including improved terrain feature contrast and the highest accuracy in forest fire area extraction.【Conclusion】Integrating multi-scale DEM data through terrain scale conversion and image reconstruction methods markedly enhanced the fire environment representation and visualization quality of FY-3B forest fire monitoring imagery. These advancements provide critical technical support for improving satellite-based forest fire monitoring efficacy and optimizing fire management strategies. Future research should explore the statistical characteristics of disaster-affected regions across varying scales to further refine the matching of terrain units for enhanced visualization outcomes.

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forest fire monitoring / satellite FY-3B / DEM scale conversion / image reconstruction / image visualization enhancement

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SU Wei , YIN Junyue , YE Jiangxia , et al . Research on visualization enhancement of FY-3B image for forest fire monitoring based on scale conversion and reconstruction[J]. Journal of Nanjing Forestry University (Natural Sciences Edition）. 2026, 50(2): 37-47 https://doi.org/10.12302/j.issn.1000-2006.202408006

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