MétaCan
Menu
Back to cohort
Record W7128878745

Levantamiento tridimensional de la Ermita de San Isidro Labrador (Alcalá de Henares): integración de técnicas de láser, escáner, GNSS y topografía clásica

2025· article· es· W7128878745 on OpenAlexaboutno aff
Nicolás Gutiérrez Fidalgo

Bibliographic record

VenueArchivo Digital UPM (Universidad Politécnica de Madrid) · 2025
Typearticle
Languagees
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)TelmatologyBathymetryMetamorphic petrology
DOInot available

Abstract

fetched live from OpenAlex

Resumen: Este Trabajo Fin de Grado tiene como objetivo realizar un levantamiento tridimensional de la ermita de San Isidro Labrador, ubicada en Alcalá de Henares, mediante la integración de tres técnicas geomáticas: GNSS, topografía clásica y escáner láser terrestre (TLS). El proyecto surge con la finalidad de obtener un modelo 3D preciso y georreferenciado del exterior de la ermita que permita documentar, conservar y estudiar este bien patrimonial de alto valor histórico y cultural. El trabajo se estructura en varias fases: levantamiento GNSS de puntos para dotar de coordenadas a la zona de trabajo, levantamiento taquimétrico mediante estación total para dotar de coordenadas a las dianas que permitirán georreferenciar el modelo tridimensional, y escaneado exterior completo de la ermita con TLS. La combinación de las diferentes metodologías asegura una alta precisión y fiabilidad en el modelo tridimensional resultante. Los resultados muestran una nube de puntos densa y detallada, de millones de puntos y una precisión inferior al centímetro. El modelo generado es aplicable a entornos SIG, modelado BIM, análisis estructural o documentación del patrimonio. Pese a limitaciones en zonas elevadas por obstrucciones visuales, la calidad global del levantamiento es notable y respalda la utilidad de esta metodología en entornos urbanos complejos. El trabajo demuestra la necesidad de la combinación de técnicas geomáticas para la documentación del patrimonio construido preciso. Se propone además una serie de líneas futuras como el modelado HBIM, el seguimiento de deformaciones a lo largo del tiempo o su integración en plataformas de realidad aumentada. El proyecto no solo aporta un resultado técnico sólido, sino también una metodología replicable en intervenciones similares en el ámbito de la geomática y la conservación del patrimonio. Abstract: This Final Degree Project aims to carry out a 3D survey of the chapel of San Isidro Labrador, located in Alcalá de Henares, through the integration of three geomatic techniques: GNSS, classical topography, and terrestrial laser scanning (TLS). The project aims to create a 3D model of the outside of the chapel. This will help to document, preserve and study this important historical and cultural site. The work is structured in several phases: GNSS point observation, total station surveying for control targets, and complete scanning of the hermitage using TLS. This methodology ensures high precision and reliability in the final 3D model. The results show a dense and detailed cloud of points, with millions of points and an accuracy of less than one centimeter. The model can be used in GIS environments, BIM modelling, structural analysis and heritage documentation. Despite some limitations in elevated areas due to visual obstructions, the overall quality of the survey supports the usefulness of this methodology in complex urban environments. In conclusion, the project demonstrates the effectiveness of combining geomatics techniques for the documentation of built heritage. It also proposes future developments such as HBIM modeling, long-term deformation monitoring, and integration with augmented reality platforms. The project not only provides a solid technical outcome but also a replicable methodology for similar interventions in the field of geomatics and heritage conservation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.255
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueArchivo Digital UPM (Universidad Politécnica de Madrid)Same topic3D Surveying and Cultural HeritageFrench-language works237,207