Dynamic and multiscale analysis of vegetation cover: Mexicali, B.C. Mexico
Bibliographic record
Abstract
Urban expansion patterns and the rapid, excessive growth of housing development have created a negative impact in city's vegetation or urban green areas (UGA).Traditional urban planning does not adopt a holistic approach at an urban-region level, nor considers ecological and environmental functions of UGA, for example, changes in structure, function and dynamics.Throughout the world a deficit in vegetation cover is present, finding UGA below the minimum range established to meet urban standards and to achieve the quality of life.The objective of this paper is to propose a methodology to analyse and evaluate the structure, dynamics and function of UGA at the urban-region level in time.This paper developed a regional and urban cover vegetation analysis for the period between 2004 and 2013 within city and peri-urban area of Mexicali, B.C. Mexico.It was conducted through land use and land cover analysis, and NDVI; using database of Mexicali urban development master plan, SPOT-6 and Landsat-L8 images, as well as ARGIS and MapInfo software.The results showed discontinuity in vegetation cover in the rural-urban transition; four zones within the city that have vegetation cover with a significant size, but their conditions are not in the most optimal state; poor UGA structure without connection between its elements; homogeneous urban fabric which highlights the constructed space and bare soil over the areas with vegetation; and that the arboreal vegetation occurs in lower quantity and quality compared to grass cover.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".