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| DOI | 10.3390/rs16081389 |
| Detection of Typical Forest Degradation Patterns: Characteristics and Drivers of Forest Degradation in Northeast China | |
| 发表日期 | 2024 |
| EISSN | 2072-4292 |
| 起始页码 | 16 |
| 结束页码 | 8 |
| 卷号 | 16期号:8 |
| 英文摘要 | The accurate identification of forest degradation and its driving factors is a prerequisite for implementing high-quality forest management. However, distinguishing degradation patterns is often neglected in large-scale forest quality assessments. The indicators were constructed to identify typical forest degradation patterns using remote sensing indexes, followed by an analysis of the spatiotemporal dynamics of forest degradation and quantification of the contributions from various driving factors. The results indicated that the constructed indicators could effectively distinguish typical forest degradation patterns, with a fire degradation identification accuracy of 90.0% and a fitting accuracy of drought and pest degradation higher than 0.7. The cold temperate conifer forest zone had the largest proportion of fire degradation, accounting for 67.7% of the area, and totals of 99.0% of the subtropical evergreen broadleaf forest zone and 92.8% of the temperate conifer and broadleaf mixed forest zone were moderately to severely affected by drought, with long-term stability. Additionally, 0.1% of the temperate grassland region and 0.1% of the cold temperate conifer forest zone underwent severe pest infestations, with a long-term stable trend. Meteorological factors were the primary contributors to all typical degradation patterns, accounting for 81.35%, 58.70%, and 82.29%, respectively. The research developed an index for assessing forest degradation and explained the importance of natural and anthropogenic factors in forest degradation. The results are beneficial for the scientific management of forest degradation and for improving forest management efficiency. |
| 英文关键词 | forest degradation; degradation indicator; remote sensing; forest management; boreal |
| 语种 | 英语 |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:001210491000001 |
| 来源期刊 | REMOTE SENSING
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/300993 |
| 作者单位 | Chinese Academy of Sciences; Research Center for Eco-Environmental Sciences (RCEES); Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Yunnan University; Inner Mongolia University of Science & Technology; Baotou Teachers College |
| 推荐引用方式 GB/T 7714 | . Detection of Typical Forest Degradation Patterns: Characteristics and Drivers of Forest Degradation in Northeast China[J],2024,16(8). |
| APA | (2024).Detection of Typical Forest Degradation Patterns: Characteristics and Drivers of Forest Degradation in Northeast China.REMOTE SENSING,16(8). |
| MLA | "Detection of Typical Forest Degradation Patterns: Characteristics and Drivers of Forest Degradation in Northeast China".REMOTE SENSING 16.8(2024). |
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