Pixel-based image classification to map vegetation communities using SPOT5 and Landsat5 Thematic Mapper data in a tropical savanna, northern Australia
| Autor: | Kirrilly Pfitzner, Donna Lewis, Stuart R. Phinn |
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| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | Canadian Journal of Remote Sensing. 38:570-585 |
| ISSN: | 1712-7971 0703-8992 |
| DOI: | 10.5589/m12-047 |
| Popis: | Pixel-based image classification has been used to capture various components of vegetation for a number of applications and at a range of spatial scales across the world. The few studies that have attempted to capture the floristic composition of vegetation communities in tropical savanna environments, at fine spatial scales (1:25000 or less) using these methods, have found minimal success. To address this gap, we evaluated a supervised image classification process using the Maximum Likelihood Classifier and 50% of a floristic and structural (strata, cover, height, and growth form) field dataset applied to SPOT5 and Landsat5 Thematic Mapper multispectral data. Two approaches were conducted to evaluate the influence of ancillary data on classification results: (i) “image-only” (image and field data) and (ii) “integrated” (various combinations of ancillary data with the image and field data). Multivariate analysis and intuitive classification were employed to identify 22 vegetation communities within the 53... |
| Databáze: | OpenAIRE |
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