Forest fuel treatment detection using multi-temporal airborne lidar data and high-resolution aerial imagery: a case study in the Sierra Nevada Mountains, California
文献类型：期刊论文
| 作者 | Su, Yanjun; Guo, Qinghua; Collins, Brandon M.; Fry, Danny L.; Hu, Tianyu2; Kelly, Maggi5 |
| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2016 |
| 卷号 | 37期号:14 |
| ISSN号 | 0143-1161 |
| DOI | 10.1080/01431161.2016.1196842 |
| 文献子类 | Article |
| 英文摘要 | Treatments to reduce forest fuels are often performed in forests to enhance forest health, regulate stand density, and reduce the risk of wildfires. Although commonly employed, there are concerns that these forest fuel treatments (FTs) may have negative impacts on certain wildlife species. Often FTs are planned across large landscapes, but the actual treatment extents can differ from the planned extents due to operational constraints and protection of resources (e.g. perennial streams, cultural resources, wildlife habitats). Identifying the actual extent of the treated areas is of primary importance to understand the environmental influence of FTs. Light detection and ranging (lidar) is a powerful remote-sensing tool that can provide accurate measurements of forest structures and has great potential for monitoring forest changes. This study used the canopy height model (CHM) and canopy cover (CC) products derived from multi-temporal airborne laser scanning (ALS) data to monitor forest changes following the implementation of landscape-scale FT projects. Our approach involved the combination of a pixel-wise thresholding method and an object-of-interest (OBI) segmentation method. We also investigated forest change using normalized difference vegetation index (NDVI) and standardized principal component analysis from multi-temporal high-resolution aerial imagery. The same FT detection routine was then applied to compare the capability of ALS data and aerial imagery for FT detection. Our results demonstrate that the FT detection using ALS-derived CC products produced both the highest total accuracy (93.5%) and kappa coefficient () (0.70), and was more robust in identifying areas with light FTs. The accuracy using ALS-derived CHM products (the total accuracy was 91.6%, and the was 0.59) was significantly lower than that using ALS-derived CC, but was still higher than using aerial imagery. Moreover, we also developed and tested a method to recognize the intensity of FTs directly from pre- and post-treatment ALS point clouds. |
| 学科主题 | Remote Sensing ; Imaging Science & Photographic Technology |
| 电子版国际标准刊号 | 1366-5901 |
| 出版地 | ABINGDON |
| WOS关键词 | UNSUPERVISED CHANGE DETECTION ; YOSEMITE-NATIONAL-PARK ; PEARL RIVER DELTA ; LEAF-AREA INDEX ; LANDSAT-TM DATA ; CANOPY COVER ; FIRE SEVERITY ; NDVI DATA ; BIOMASS ; LANDSCAPE |
| WOS研究方向 | Science Citation Index Expanded (SCI-EXPANDED) |
| 语种 | 英语 |
| 出版者 | TAYLOR & FRANCIS LTD |
| WOS记录号 | WOS:000379952400008 |
| 资助机构 | USDA Forest Service Region 5 ; USDA Forest Service Pacific Southwest Research StationUnited States Department of Agriculture (USDA)United States Forest Service ; US Fish and Wildlife ServiceUS Fish & Wildlife Service ; California Department of Water Resources ; California Department of Fish and Game ; California Department of Forestry and Fire Protection ; Sierra Nevada Conservancy ; National Science FoundationNational Science Foundation (NSF) [DBI 1356077] ; National Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41471363, 31270563] |
| 源URL | [http://ir.ibcas.ac.cn/handle/2S10CLM1/24519]  |
| 专题 | 植被与环境变化国家重点实验室 |
| 作者单位 | 1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China 2.Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA USA 3.Univ Calif Merced, Sch Engn, Sierra Nevada Res Inst, Merced, CA USA 4.Collins, Brandon M.] US Forest Serv, USDA, Pacific Southwest Res Stn, Davis, CA USA 5.Collins, Brandon M.] Univ Calif Berkeley, Ctr Fire Res & Outreach, Berkeley, CA USA |
| 推荐引用方式 GB/T 7714 | Su, Yanjun,Guo, Qinghua,Collins, Brandon M.,et al. Forest fuel treatment detection using multi-temporal airborne lidar data and high-resolution aerial imagery: a case study in the Sierra Nevada Mountains, California[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2016,37(14). |
| APA | Su, Yanjun,Guo, Qinghua,Collins, Brandon M.,Fry, Danny L.,Hu, Tianyu,&Kelly, Maggi.(2016).Forest fuel treatment detection using multi-temporal airborne lidar data and high-resolution aerial imagery: a case study in the Sierra Nevada Mountains, California.INTERNATIONAL JOURNAL OF REMOTE SENSING,37(14). |
| MLA | Su, Yanjun,et al."Forest fuel treatment detection using multi-temporal airborne lidar data and high-resolution aerial imagery: a case study in the Sierra Nevada Mountains, California".INTERNATIONAL JOURNAL OF REMOTE SENSING 37.14(2016). |
入库方式： OAI收割
来源：植物研究所
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