Forest Fire Discrimination Based on Angle Slope Index and Himawari-8
In the background of high frequency and intensity forest fires driven by future warming and a drying climate, early detection and effective control of fires are extremely important to reduce losses. Meteorological satellite imagery is commonly used for near-real-time forest fire monitoring, thanks t...
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MDPI AG
2025-01-01
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| author | Pingbo Liu Gui Zhang |
| author_facet | Pingbo Liu Gui Zhang |
| author_sort | Pingbo Liu |
| collection | DOAJ |
| description | In the background of high frequency and intensity forest fires driven by future warming and a drying climate, early detection and effective control of fires are extremely important to reduce losses. Meteorological satellite imagery is commonly used for near-real-time forest fire monitoring, thanks to its high temporal resolution. To address the misjudgments and omissions caused by solely relying on changes in infrared band brightness values and a single image in forest fire early discrimination, this paper constructs the angle slope indexes ANIR, AMIR, AMNIR, ∆ANIR, and ∆AMIR based on the reflectance of the red band and near-infrared band, the brightness temperature of the mid-infrared and far-infrared band, the difference between the AMIR and ANIR, and the index difference between time-series images. These indexes integrate the strong inter-band correlations and the reflectance characteristics of visible and short-wave infrared bands to simultaneously monitor smoke and fuel biomass changes in forest fires. We also used the decomposed three-dimensional OTSU (maximum inter-class variance method) algorithm to calculate the segmentation threshold of the sub-regions constructed from the AMNIR data to address the different discrimination thresholds caused by different time and space backgrounds. In this paper, the Himawari-8 satellite imagery was used to detect forest fires based on the angle slope indices thresholds algorithm (ASITR), and the fusion of the decomposed three-dimensional OTSU and ASITR algorithm (FDOA). Results show that, compared with ASITR, the accuracy of FDOA decreased by 3.41% (0.88 vs. 0.85), the omission error decreased by 52.94% (0.17 vs. 0.08), and the overall evaluation increased by 3.53% (0.85 vs. 0.88). The ASITR has higher accuracy, and the fusion of decomposed three-dimensional OTSU and angle slope indexes can reduce forest fire omission error and improve the overall evaluation. |
| format | Article |
| id | doaj-art-5c7f4257f12349f3b539ae745fc90e8a |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-5c7f4257f12349f3b539ae745fc90e8a2025-01-10T13:20:22ZengMDPI AGRemote Sensing2072-42922025-01-0117114210.3390/rs17010142Forest Fire Discrimination Based on Angle Slope Index and Himawari-8Pingbo Liu0Gui Zhang1College of Forestry, Soil and Water Conservation, Central South University of Forestry and Technology, Changsha 410004, ChinaCollege of Forestry, Soil and Water Conservation, Central South University of Forestry and Technology, Changsha 410004, ChinaIn the background of high frequency and intensity forest fires driven by future warming and a drying climate, early detection and effective control of fires are extremely important to reduce losses. Meteorological satellite imagery is commonly used for near-real-time forest fire monitoring, thanks to its high temporal resolution. To address the misjudgments and omissions caused by solely relying on changes in infrared band brightness values and a single image in forest fire early discrimination, this paper constructs the angle slope indexes ANIR, AMIR, AMNIR, ∆ANIR, and ∆AMIR based on the reflectance of the red band and near-infrared band, the brightness temperature of the mid-infrared and far-infrared band, the difference between the AMIR and ANIR, and the index difference between time-series images. These indexes integrate the strong inter-band correlations and the reflectance characteristics of visible and short-wave infrared bands to simultaneously monitor smoke and fuel biomass changes in forest fires. We also used the decomposed three-dimensional OTSU (maximum inter-class variance method) algorithm to calculate the segmentation threshold of the sub-regions constructed from the AMNIR data to address the different discrimination thresholds caused by different time and space backgrounds. In this paper, the Himawari-8 satellite imagery was used to detect forest fires based on the angle slope indices thresholds algorithm (ASITR), and the fusion of the decomposed three-dimensional OTSU and ASITR algorithm (FDOA). Results show that, compared with ASITR, the accuracy of FDOA decreased by 3.41% (0.88 vs. 0.85), the omission error decreased by 52.94% (0.17 vs. 0.08), and the overall evaluation increased by 3.53% (0.85 vs. 0.88). The ASITR has higher accuracy, and the fusion of decomposed three-dimensional OTSU and angle slope indexes can reduce forest fire omission error and improve the overall evaluation.https://www.mdpi.com/2072-4292/17/1/142forest fire discriminationangle slope indexHimawari-8decomposed three-dimensional OTSU |
| spellingShingle | Pingbo Liu Gui Zhang Forest Fire Discrimination Based on Angle Slope Index and Himawari-8 Remote Sensing forest fire discrimination angle slope index Himawari-8 decomposed three-dimensional OTSU |
| title | Forest Fire Discrimination Based on Angle Slope Index and Himawari-8 |
| title_full | Forest Fire Discrimination Based on Angle Slope Index and Himawari-8 |
| title_fullStr | Forest Fire Discrimination Based on Angle Slope Index and Himawari-8 |
| title_full_unstemmed | Forest Fire Discrimination Based on Angle Slope Index and Himawari-8 |
| title_short | Forest Fire Discrimination Based on Angle Slope Index and Himawari-8 |
| title_sort | forest fire discrimination based on angle slope index and himawari 8 |
| topic | forest fire discrimination angle slope index Himawari-8 decomposed three-dimensional OTSU |
| url | https://www.mdpi.com/2072-4292/17/1/142 |
| work_keys_str_mv | AT pingboliu forestfirediscriminationbasedonangleslopeindexandhimawari8 AT guizhang forestfirediscriminationbasedonangleslopeindexandhimawari8 |