Estimation of Forest Canopy Fuel Moisture Content in Dali Prefecture by Combining Vegetation Indices and Canopy Radiative Transfer Models from MODIS Data
文献类型：期刊论文
| 作者 | Yang, Kun2,3; Tang, Bo-Hui1,2,3; Fu, Wei2,3; Zhou, Wei2,3; Fu, Zhitao2,3; Fan, Dong2,3 |
| 刊名 | FORESTS
 |
| 出版日期 | 2024-04-01 |
| 卷号 | 15期号:4页码:18 |
| 关键词 | forest canopy fuel moisture content PROSAIL PROGeoSAIL enhanced vegetation index normalized difference moisture index |
| DOI | 10.3390/f15040614 |
| 英文摘要 | Forest canopy fuel moisture content (FMC) is a critical factor in assessing the vulnerability of a specific area to forest fires. The conventional FMC estimation method, which relies on look-up tables and loss functions, cannot to elucidate the relationship between FMC and simulated data from look-up tables. This study proposes a novel approach for estimating FMC by combining enhanced vegetation index (EVI) and normalized difference moisture index (NDMI). The method employs the PROSAIL + PROGeoSAIL two-layer coupled radiation transfer model to simulate the vegetation index, the water index, and the FMC value, targeting the prevalent double-layer structure in the study area's vegetation distribution. Additionally, a look-up table is constructed through numerical analysis to investigate the relationships among vegetation indices, water indices, and FMC. The results reveal that the polynomial equations incorporating vegetation and water indices as independent variables exhibit a strong correlation with FMC. Utilizing the EVI-NDMI joint FMC estimation method enables the direct estimation of FMC. The collected samples from Dali were compared with the estimated values, revealing that the proposed method exhibits superior accuracy (R2 = 0.79) in comparison with conventional FMC estimation methods. In addition, we applied this method to estimate the FMC in the Chongqing region one week before the 2022 forest fire event, revealing a significant decreasing trend in regional FMC leading up to the fire outbreak, highlighting its effectiveness in facilitating pre-disaster warnings. |
| WOS关键词 | WATER ; LOAD |
| 资助项目 | National Natural Science Foundation of China |
| WOS研究方向 | Forestry |
| 语种 | 英语 |
| WOS记录号 | WOS:001210609400001 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/204869]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Tang, Bo-Hui |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Dept Educ Yunnan Prov, Key Lab Plateau Remote Sensing, Kunming 650093, Peoples R China 3.Kunming Univ Sci & Technol, Fac Land Resources Engn, Kunming 650093, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Kun,Tang, Bo-Hui,Fu, Wei,et al. Estimation of Forest Canopy Fuel Moisture Content in Dali Prefecture by Combining Vegetation Indices and Canopy Radiative Transfer Models from MODIS Data[J]. FORESTS,2024,15(4):18. |
| APA | Yang, Kun,Tang, Bo-Hui,Fu, Wei,Zhou, Wei,Fu, Zhitao,&Fan, Dong.(2024).Estimation of Forest Canopy Fuel Moisture Content in Dali Prefecture by Combining Vegetation Indices and Canopy Radiative Transfer Models from MODIS Data.FORESTS,15(4),18. |
| MLA | Yang, Kun,et al."Estimation of Forest Canopy Fuel Moisture Content in Dali Prefecture by Combining Vegetation Indices and Canopy Radiative Transfer Models from MODIS Data".FORESTS 15.4(2024):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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