Name
Title | ||
|---|---|---|
Object-based random forest classification of Landsat ETM+ and WorldView-2 satellite imagery for mapping lowland native grassland communities in Tasmania, Australia. |
Abstract | ||
|---|---|---|
•A case study for mapping endangered lowland native grassland communities.•Repeat classification can detect sampling bias in training and validation datasets.•Statistical significance testing can be used to determine optimal datasets. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jag.2017.11.006 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | Field | DocType |
Native grasslands,Random forest,k-fold cross-validation,Object-based image analysis | Woodland,Themeda,Vegetation,Satellite imagery,Remote sensing,Grassland,Random forest,Themeda triandra,Geography | Journal |
Volume | ISSN | Citations |
66 | 0303-2434 | 2 |
PageRank | References | Authors |
0.40 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bethany Melville | 1 | 2 | 0.40 |
| Arko Lucieer | 2 | 455 | 46.51 |
| Jagannath Aryal | 3 | 55 | 12.31 |