IB-CAS  > 植被与环境变化国家重点实验室
Forest fuel treatment detection using multi-temporal airborne lidar data and high-resolution aerial imagery: a case study in the Sierra Nevada Mountains, California
Su, Yanjun; Guo, Qinghua; Collins, Brandon M.; Fry, Danny L.; Hu, Tianyu4; Kelly, Maggi3
2016
发表期刊INTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN0143-1161
卷号37期号:14页码:3322-3345
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.
学科领域Remote Sensing ; Imaging Science & Photographic Technology
DOI10.1080/01431161.2016.1196842
收录类别SCI
语种英语
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)
WOS记录号WOS:000379952400008
出版者TAYLOR & FRANCIS LTD
文献子类Article
出版地ABINGDON
EISSN1366-5901
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]
作者邮箱qguo@ucmerced.edu
引用统计
被引频次:18[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ibcas.ac.cn/handle/2S10CLM1/25167
专题植被与环境变化国家重点实验室
作者单位1.Univ Calif Merced, Sch Engn, Sierra Nevada Res Inst, Merced, CA USA
2.Collins, Brandon M.] US Forest Serv, USDA, Pacific Southwest Res Stn, Davis, CA USA
3.Collins, Brandon M.] Univ Calif Berkeley, Ctr Fire Res & Outreach, Berkeley, CA USA
4.Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA USA
5.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China
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):3322-3345.
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),3322-3345.
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):3322-3345.
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