Townscape character changes and visual analysis as determinants for shaping the spatial structure of the city - Kielce case study
Bibliographic record
Abstract
The article presents the results of the analysis carried out under the Environmental Study for Local Development Policy of Kielce. The main goal of the analysis was to identify the primary conditions which should be taken into consideration when preserving the visual values in urban planning. The analysis was focused on identification and description of the existing features within landscape (including their transformation) and on its ability to accommodate changes. The first step of the survey was focused on identification of changes in the townscape character, taking into account: extent of the urban fabric, character of the built-up areas and their origin. The analysis of changes in the townscape was based on archival cartographic materials. To determine the cultural stratigraphy of the town a three-time scale was used: areas formed before the middle of the twentieth century, areas created in the 3rd quarter of the twentieth century and areas created in the 4th quarter of the twentieth century and at the beginning of the twenty-first century. Analysis of changes in the landscape consisted mainly of changes in the land use structure, as well as the analysis of layout of individual elements forming the urban landscape (e.g. landmarks). The second part of the study was related to examining the visual exposure of identified townscape character areas. The exposure analysis was based on views from the scenic viewpoints as well as a sequence of points located along major transit roads and hiking trails. Totally more than 100 viewpoints were analyzed. This analysis aimed at presenting areas particularly exposed in the townscape. On the basis of townscape changes and visual exposure the authors of the study assessed the state of landscape values preservation and the visual absorption capacity. This assessment was a starting point to work out guidelines for future development. Special attention was paid to areas important for preservation of landscape exposition of objects of special cultural values (1) and areas dedicated to urban development with low visual absorption capacity (2). Recommendations for spatial development comprise: restrictions on location of high construction works as well as woodlands and other high vegetation (1), the need for adapting new buildings to the surrounding landscape and to the form and dimensions of existing objects (2). Identifications and assessment of the visual aspects as well as changes in the landscape became, together with the conditions resulting from the state and functioning of the environment, one of the major determinants for shaping the spatial structure of the city.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".