Predicting the future through observations of the past: Concretizing the role of Geosimulation for holistic geospatial knowledge
Bibliographic record
Abstract
Geomatics can be generally defined as the knowledge and ability of utilizing geospatial data for analyzing and forecasting the state of the environment to inform environmental management. However, current applications of Geomatics only span from data acquisition to spatial analysis and exclude the capabilities of Geosimulation. To concretize the role of Geosimulation in Geomatics for obtaining geospatial knowledge, we write this paper with two main objectives. First, we establish the Geomatics framework , a set of tasks utilizing geospatial data that aims to provide holistic geospatial knowledge of the environment. This set of tasks are specifically composed of data acquisition, spatial analysis, and Geosimulation. This proposed framework also brings forward our second objective which is to present Geomatics as an approach for holistically informing environmental management by predicting the future through observations of the past . To provide sample applications of the Geomatics framework for obtaining holistic geospatial knowledge, we provide three case studies of research projects that followed the Geomatics framework for informing environmental management actions. As Geomatics can play a major role in addressing the effects of climate change, we also presented a future template for the application of the Geomatics framework for mitigating and adapting to the effects of climate change. We anticipate three implications of adopting this Geomatics framework: the widening of the environmental application of Geomatics, the establishment of a methodological workflow for informing environmental management, and the enhancement of the collaboration between Geosimulation and other spatial science fields. We conclude the paper by advocating the adoption of this framework as we posit that this new perspective in Geomatics will also strengthen the teaching of the environmental applications of geospatial knowledge. ● The Geomatics framework provides holistic geospatial knowledge of the past and future. ● Presents Geomatics as an approach for informing environmental management. ● Three case studies that followed the Geomatics framework for informed decision-making. ● Provides a workflow for applying the Geomatics framework in addressing climate change. ● Enhances collaboration between Geosimulation and other geomatic science disciplines.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".