Object-based classification of Worldview-2 imagery for mapping invasive common reed, <i>Phragmites australis</i>
Bibliographic record
Abstract
Wetlands provide many environmental and societal benefits. Unfortunately, the importance of wetlands has only recently been acknowledged after centuries of drainage and conversion to other land uses. An emerging threat to North American wetlands is the introduction of invasive plant species such as Phragmites australis, a reed introduced from Europe. Previous high spatial resolution satellite imagery used for mapping Phragmites was limited spectrally to four bands (blue, green, red, and near-infrared). A recently launched satellite, Worldview-2, has four additional spectral bands that may allow for more accurate mapping of Phragmites. In this study, a single-date Worldview-2 image was used to map wetland vegetation at Walpole Island, Canada. Object-based and per-pixel maximum likelihood classifications were performed on a four-band subset simulating traditional multispectral imagery and the full eight-band set of Worldview-2. The overall classification accuracy of 94.0% achieved for the eight-band object-based method was the highest of the four classifications methods used. The accuracy achieved by the eight-band object-based classification shows that single-date Worldview-2 image is promising for distinguishing Phragmites from native wetland plant species late in the growing season in coastal Great Lakes wetlands.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".