dc.contributor.supervisor |
Hopkinson, Christopher |
|
dc.contributor.author |
Xi, Zhouxin |
|
dc.contributor.author |
University of Lethbridge. Faculty of Arts and Science |
|
dc.date.accessioned |
2019-06-26T17:08:01Z |
|
dc.date.available |
2019-06-26T17:08:01Z |
|
dc.date.issued |
2019 |
|
dc.identifier.uri |
https://hdl.handle.net/10133/5431 |
|
dc.description.abstract |
Biomass measurement provides a baseline for ecosystem valuation required by modern forest management. The advent of ground-based LiDAR technology, renowned for 3D sampling resolution, has been altering the routines of biomass inventory. The thesis develops a set of innovative approaches in support of fine-scale biomass inventory, including automatic extraction of stem statistics, robust delineation of plot biomass components, accurate classification of individual tree species, and repeatable scanning of plot trees using a lightweight scanning system. Main achievements in terms of accuracy are a relative root mean square error of 11% for stem volume extraction, a mean classification accuracy of 0.72 for plot wood components, and a classification accuracy of 92% among seven tree species. The results indicate the technical feasibility of biomass delineation and monitoring from plot-level and multi-species point cloud datasets, whereas point occlusion and lack of fine-scale validation dataset are current challenges for biomass 3D analysis from ground. |
en_US |
dc.description.sponsorship |
S.G.S. International Tuition Award from the University of Lethbridge
The Dean's Scholarship from the University of Lethbridge
Campus Alberta Innovates Program
NSERC Discovery Grants Program |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
Lethbridge, Alta. : University of Lethbridge, Dept. of Geography |
en_US |
dc.relation.ispartofseries |
Thesis (University of Lethbridge. Faculty of Arts and Science) |
en_US |
dc.subject |
3D |
en_US |
dc.subject |
Forest biomass |
en_US |
dc.subject |
Multisensor data fusion |
en_US |
dc.subject |
Optical radar |
en_US |
dc.subject |
Terrestrial Laser Scanning |
en_US |
dc.title |
Fine-scale Inventory of Forest Biomass with Ground-based LiDAR |
en_US |
dc.type |
Thesis |
en_US |
dc.publisher.faculty |
Arts and Science |
en_US |
dc.publisher.department |
Department of Geography |
en_US |
dc.degree.level |
Ph.D |
en_US |
dc.proquest.subject |
Remote sensing [0799] |
en_US |
dc.proquest.subject |
Physical geography [0368] |
en_US |
dc.proquest.subject |
Forestry [0478] |
en_US |
dc.proquestyes |
Yes |
en_US |