- Title
- Airborne laser scanning: exploratory data analysis indicates potential variables for classification of individual trees or forest stands according to species
- Creator
- Moffiet, T.; Mengersen, K.; Witte, C.; King, R.; Denham, R.
- Relation
- ISPRS Journal of Photogrammetry and Remote Sensing Vol. 59, Issue 5, p. 289-309
- Publisher Link
- http://dx.doi.org/10.1016/j.isprsjprs.2005.05.002
- Publisher
- Elsevier BV
- Resource Type
- journal article
- Date
- 2005
- Description
- Understanding your data through exploratory data analysis is a necessary first stage of data analysis particularly for observational data. The checking of data integrity and understanding the distributions, correlations and relationships between potentially important variables is a fundamental part of the analysis process prior to model development and hypothesis testing. In this paper, exploratory data analysis is used to assess the potential of laser return type and return intensity as variables for classification of individual trees or forest stands according to species. For narrow footprint lidar instruments that record up to two return amplitudes for each output pulse, the usual pre-classification of return data into first and last intensity returns camouflages the fact that a number of the return signals have only “single amplitude” (singular) returns. The importance of singular returns for species discrimination has received little discussion in the remote sensing literature. A map view of the different types of returns overlaid on field species data indicated that it is possible to visually distinguish between vegetation types that produce a high proportion of singular returns, compared to vegetation types that produce a lower proportion of singular returns, at least when using a specific laser footprint size. Using lidar data and the corresponding field data derived from a subtropical woodland area of South East Queensland, Australia, map scatterplots of return types combined with field data enabled, in some cases, visual discrimination at the individual tree level between White Cypress Pine (Callitris glaucophylla) and Poplar Box (Eucalyptus populnea). While a clear distinction between these two species was not always visually obvious at the individual tree level, due to other extraneous sources of variation in the dataset, the observation was supported in general at the site level. Sites dominated by Poplar Box generally exhibited a lower proportion of singular returns compared to sites dominated by Cypress Pine. While return intensity statistics for this particular dataset were not found to be as useful for classification as the proportions of laser return types, an examination of the return intensity data leads to an explanation of how return intensity statistics are affected by forest structure. Exploratory data analysis indicated that a large component of variation in the intensity of the return signals from a forest canopy is associated with reflections of only part of the laser footprint. Consequently, intensity return statistics for the forest canopy, such as average and standard deviation, are related not only to the reflective properties of the vegetation, but also to the larger scale properties of the forest such as canopy openness and the spacing and type of foliage components within individual tree crowns.
- Subject
- lidar; intensity return; exploratory data analysis; species discrimination; data visualization
- Identifier
- http://hdl.handle.net/1959.13/27424
- Identifier
- uon:1657
- Identifier
- ISSN:0924-2716
- Language
- eng
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