WorldView-2 satellite imagery and airborne LiDAR data for object-based forest species classification in a cool temperate rainforest environment
Edited book (chapter)
Zhang, Zhenyu and Liu, Xiaoye. 2013. "WorldView-2 satellite imagery and airborne LiDAR data for object-based forest species classification in a cool temperate rainforest environment." Abdul Rahman, Alias, Boguslawski, Pawel, Gold, Christopher and Nor Said, Mohamad (ed.) Developments in multidimensional spatial data models. Heidelberg, Germany. Springer. pp. 103-122
| Chapter Title | WorldView-2 satellite imagery and airborne LiDAR data for object-based forest species classification in a cool temperate rainforest environment |
|---|---|
| Book Chapter Category | Edited book (chapter) |
| ERA Publisher ID | 3337 |
| Book Title | Developments in multidimensional spatial data models |
| Authors | Zhang, Zhenyu (Author) and Liu, Xiaoye (Author) |
| Editors | Abdul Rahman, Alias, Boguslawski, Pawel, Gold, Christopher and Nor Said, Mohamad |
| Page Range | 103-122 |
| Series | Lecture Notes in Geoinformation and Cartography |
| Chapter Number | 7 |
| Number of Pages | 20 |
| Year | 2013 |
| Publisher | Springer |
| Place of Publication | Heidelberg, Germany |
| ISBN | 9783642363788 |
| 9783642363795 | |
| ISSN | 1863-2246 |
| 1863-2351 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-642-36379-5_7 |
| Web Address (URL) | http://www.springer.com/earth+sciences+and+geography/geographical+information+systems/book/978-3-642-36378-8 |
| Abstract | High resolution spatial data including airborne LiDAR data and newly available WorldView-2 satellite imagery provide opportunities to develop new efficient ways of solving conventional problems in forestry. Those responsible for monitoring forest changes over time relevant to timber harvesting and native forest conservation realize the potential for improved documentation from using such data. Proper use of high spatial resolution data with object-based image analysis approach and nonparametric classification method such as decision trees offer an alternative to aerial photograph interpretation in support of forest classification and mapping. This study explored ways of processing airborne Li-DAR data and WorldView-2 satellite imagery for object-based forest species classification using decision trees in the Strzelecki Ranges, one of the four major Victorian areas of cool temperate rainforest in Australia. The effectiveness of variables derived from different data sets, in particular, the four new bands of WorldView-2 imagery was examined. The results showed that using LiDAR data alone or four conventional bands only, the overall accuracies achieved were 61.39% and 61.42% respectively, but the overall accuracy increased to 82.35% when all eight bands and the LiDAR data were used. This study demonstrated that the integration of airborne LiDAR and eight WorldView-2 bands significantly improved the classification accuracy. |
| Keywords | WorldView-2; LiDAR; object-based image analysis; forest classification; decision tree; cool temperate rainforest |
| ANZSRC Field of Research 2020 | 401304. Photogrammetry and remote sensing |
| 410404. Environmental management | |
| 460306. Image processing | |
| Public Notes | Copyright Springer-Verlag Berlin Heidelberg 2013. Permanent restricted access to published version due to publisher copyright policy. |
| Byline Affiliations | Australian Centre for Sustainable Catchments |
| Institution of Origin | University of Southern Queensland |
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