Spatial Methods for Solution of Environmental and Hydrologic Problems—Science, Policy, and Standardization
Bibliographic record
Abstract
Description Get an international perspective on the latest issues relating to spatial analysis, accuracy in the location and special representation of data and real world features, and emerging standards for digital spatial methods and applications. Twelve peer-reviewed papers cover: Accuracy and Uncertainty in Spatial Data and Analysis • Application of krieging and other geostatistical techniques • Fractal analysis for spatial applications • Difficulty in defining the level of accuracy for environmental and hydrologic data • Spatial variability, uncertainty, and risk for use in decision support systems • Use and application of global positioning systems (GPS) Modeling and Spatial Analysis of Environmental and Hydrologic Systems in Spatial Data Environments • Spatial techniques to model environmental systems • Development of object models for hydrologic systems. • Development of a flood warning system for watersheds in Spain • Modeling the distribution of soil moisture with remote sensing and geographic information systems (GIS) • Data integration with GIS as a management tool for decision support • Efforts to model surface soil moisture from satellite microwave observations • Use of response units to assess erosion processes in semiarid areas in southern Africa Standardization and Standard Digital Data Sets • Methods, descriptions, and digital data products, such as the watershed boundary standards for the U.S. • Status of standards in use by the U.S. government related to GIS data • Role of other organizations in the development of standards for GIS • Development of standard merged products of satellite imagery and elevation data for natural resource mapping in Canada • Development of a series of standard digital databases, in which U.S. Geological Survey has been particularly active This publication is based on a symposium sponsored by ASTM International in cooperation with the International Commission on Remote Sensing of the International Association of Hydrologic Sciences, the Canada Centre for Remote Sensing, the U. S. Geological Survey, and the U.S. Bureau of Reclamation.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.010 |
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".