Supporting Files for Radwin et al., "Shrinking Salt Crusts of the Bonneville Basin, Utah: Observations from Multispectral Remote Sensing"
Bibliographic record
Abstract
Supporting Files for Radwin et al., "Shrinking Salt Crusts of the Bonneville Basin, Utah: Observations from Multispectral Remote Sensing" For any questions regarding the data or methodology, or desire to utilize the data, please contact the corresponding author, Mark Radwin, at markradwin@gmail.com NOTE: As of time of uplaod, this manuscript is currently UNPUBLISHED - Please refer to the manuscript for more information (which will be posted here once available) Abstract: Halite crusts in Utah’s Bonneville basin, including the Bonneville Salt Flats, Newfoundland basin, and Pilot Valley saline pans, show rapid spatiotemporal variations and significant declines in surface area over the past century. Using multispectral satellite imagery from 1984 to 2024 (585 dates), aerial imagery from 1946 to 1978, and a 1925 map, we analyze long-term changes in halite and water surface areas to understand these salt crust systems' evolution and hydrological/climatic influences. Data are processed into Normalized Difference Water Index and Halite Index rasters and classified with static and dynamic thresholds, respectively. Results indicate that the Bonneville Salt Flats has shrunk by 75% since 1925, with a decline rate of 0.75-1.45 km²/year, projecting a potential disappearance between 2072 and 2126. The Newfoundland basin crust, an anthropogenic feature, has been declining at 2.6-6 km²/year and may vanish between 2154 and 2353. When normalized to initial area, decline rates are comparable between the Bonneville Salt Flats and Newfoundland basin. In contrast, the ephemeral Pilot Valley crust shows no clear long-term reduction in area but considerable intra-annual variability. Flooding events are observed to be significant drivers of halite area changes, with post-flood halite growth 30-90 days after peak water area. These findings underscore the dynamic nature of salt crust systems, reveal links between hydrological cycles and crust dynamics, and provide a framework for future research, monitoring, and management of salt flats in arid regions. This is a repository dataset containing: 1) Code, 2) Data, 3) Shapefiles, and 4) Supplemental Figures from this study. With this dataset, our workflow can be replicated and data reproduced. This repository hosts a downloadable zipped folder containing four subfolders: Code Contains Jupyter Notebook files (Python) used to acquire and process Landsat and Sentinel-2 satellite data The code utilizes Google Earth Engine Datasets Contains datasets for: All unfiltered area measurements Filtered area measurements for each saline pan Variability data for each saline pan Regional PDSI data Regional precipitation data Shapefiles Files used to delineate saline pan boundaries for surface area measurements Supplemental Figures Figure A1 and it's associated figure caption
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.670 | 0.192 |
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 source (direct Gemma or distilled Codex), 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".