Lacunarity for Spatial Heterogeneity Measurement in GIS
Why this work is in the frame
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Bibliographic record
Abstract
Abstract As a scale dependent measure of heterogeneity, lacunarity has been applied to the analysis of structures in both fractals and non-fractals. In this paper, the lacunarity concept and some lacunarity estimation methods are briefly described, then a Lacunarity Analysis extension for ArcView GIS (ESRI) is introduced. Using binary and grayscale images, several examples are also given for lacunarity analysis of spatial heterogeneity. Experiments with gray-scale image textures show that a new lacunarity estimation method can provide more accurate heterogeneity measurement than some existing methods. The results suggest that lacunarity analysis is a promising tool for spatial heterogeneity measurement in a GIS environment.
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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