A saliency mapping approach to understanding the visual impact of wind and solar infrastructure in amenity landscapes
Bibliographic record
Abstract
Shifts from fossil fuels toward renewable energy (RE) introduce profound changes to landscapes, including visual impacts that are often investigated during environmental and social impact assessment. Moreover, RE transitions are among many visual changes happening in rural areas that are increasingly serving amenity functions and becoming destinations for wide ranges of users. This diversity introduces complexities during infrastructure siting discussions. Emerging grape and wine production landscapes in Canada serve amenity and production purposes, and this study was designed to understand the impacts of RE development using case studies of solar panels and wind turbines in two vineyard landscapes in Ontario (ON) and British Columbia (BC). We applied novel mixed methods, including content analysis and saliency-based visual impact analysis, to textual and image-based representations posted on Instagram of those vineyards. In this case, the addition of low-density RE infrastructures did not seem to disturb the vineyard experience. The technique presented can be applied in a wide range of infrastructure siting contexts, both before and after construction, but requires additional research and calibration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".