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Image Processing and Classification Procedures for Analysis of Sub-decimeter Imagery Acquired with an Unmanned Aircraft over Arid Rangelands
- Source :
- GIScience & remote sensing; January 2011, Vol. 48 Issue: 1 p4-23, 20p
- Publication Year :
- 2011
-
Abstract
- Unmanned aerial systems (UAS) have great potential as a platform for acquiring very high resolution aerial imagery for vegetation mapping. However, image processing and classification techniques require adaptation to images obtained with low-cost digital cameras. We developed and evaluated an image processing workflow that included the integration of resolution-appropriate field sampling, feature selection, and object-based image analysis for the purpose of classifying rangeland vegetation from a five-centimeter-resolution UAS image mosaic. Classification tree analysis was used to determine the optimal spectral, spatial, and contextual features. Segmentation and classification rule sets were developed on a test plot and were applied to the remaining study area, resulting in an overall classification accuracy of 78% at the species level and 81% at the structure-group level. The image processing approach provides a roadmap for deriving quality vegetation classification products from UAS imagery with very high spatial, but low spectral resolution.
Details
- Language :
- English
- ISSN :
- 15481603 and 19437226
- Volume :
- 48
- Issue :
- 1
- Database :
- Supplemental Index
- Journal :
- GIScience & remote sensing
- Publication Type :
- Periodical
- Accession number :
- ejs30878440
- Full Text :
- https://doi.org/10.2747/1548-1603.48.1.4