Effectiveness of aerial and ISERV-ISS RGB photos for real-time urban floodwater mapping: case of Calgary 2013 flood
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High-resolution red-green-blue (RGB) images from remote sensors, such as those carried on aircrafts, UAVs, satellites, and the International Space Station (ISS), are cost-effective data sources for real-time emergency response applications. We describe an assessment undertaken on spectral behaviors to evaluate the effectiveness of two high-resolution RGB image datasets for mapping and monitoring of floodwater extent in dense urban areas. The assessment was as part of a case study of the Calgary 2013 flood event. The input imagery included very high-resolution aerial photos and imagery acquired with the SERVIR Environmental Research and Visualization System (ISERV) carried on the ISS. The results demonstrate the complementary nature of these two RGB image sets in providing effective urban floodwater mapping for real-time response. The aerial photos with higher spatial resolution and less atmospheric effect can provide the details about the floodwater distribution; the images from ISERV-ISS can provide the temporal variation of floodwater distribution.
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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 | 0.000 |
| 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 it