Item Infomation
Title: | Feature Relevance Assessment Of Multispectral Airborne Lidar Data For Tree Species Classification |
Authors: | Amiri N. |
Participants: | Heurich M. Krzystek P. Skidmore A.K. |
Issue Date: | 2018 |
Publisher: | null |
Citation: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. XLII-3, pp.31-34 |
Abstract: | Our study is conducted using 586 ground measured single trees from 20 sample plots in the Bavarian Forest National Park, in Germany. Due to lack of reference data for some rare species, we focused on four classes of species. The results show an improvement between 4-10 pp for the tree species classification by using MLS data in comparison to a single wavelength based approach. A cross validated (15-fold) accuracy of 0.75 can be achieved when all feature sets from three different spectral channels are used. Our results cleary indicates that the use of MLS point clouds has great potential to improve detailed forest species mapping. |
URI: | http://tailieuso.tlu.edu.vn/handle/DHTL/8495 |
Source: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3/31/2018/isprs-archives-XLII-3-31-2018.pdf |
Appears in Collections: | Tài liệu mở |
ABSTRACTS VIEWS
25
VIEWS & DOWNLOAD
0
Files in This Item:
There are no files associated with this item.
Bạn đọc là cán bộ, giáo viên, sinh viên của Trường Đại học Thuỷ Lợi cần đăng nhập để Xem trực tuyến/Tải về
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.