Advanced documentation technologies for a people-centred preparedness and re-construction in Bela, India
Notice bibliographique
Résumé
Purpose Despite the recurrence of earthquakes, responses are usually triggered afterwards, lacking mitigation strategies to diminish risks. Damaged dwellings cannot be immediately reinforced to continue inhabitation, generating disruption. Repairs are usually costly, as large numbers of affected constructions make damage assessment difficult, and post-earthquake reconstruction programmes often lack a heritage-specific approach. This research seeks to address these issues through a methodology based on high-end documentation technologies applied to built heritage and local community engagement. Design/methodology/approach The methodology proposed combines different recording tools to capture social and built environment data, such as interviews, mapping, drone capture, photography and 3D laser scanning, in the pilot case study of Bela, a historical settlement in the seismic region of Kutch in Gujarat, India, affected by the 2001 Bhuj earthquake. This paper particularly discusses aspects of community engagement around data capture and representation processes. Findings The introduction of advanced documentation technologies can help speed up the process of damage assessment, analyse social aspects that are key to a respectful re-construction, and enhance community engagement through visual representations, which are relevant to social acceptance and understanding towards a meaningful introduction and sustained use in earthquake risk management. Research limitations/implications The methodology proposed can inform similar cases in seismic areas and enhance engagement, helping to develop a sense of awareness in the community regarding the need for preparedness in the face of earthquakes. However, there are technical challenges in using advanced recording technologies in terms of equipment accessibility, skills, knowledge and future uses of the data. Social and cultural aspects, such as caste and gender divisions, also implied disparity in accessing the data and relating it to the research team, bringing forward the need to tailor public engagement to achieve inclusivity. Practical implications This study has practical implications. The most relevant one is how the process of carrying out the research served as a way to raise awareness for future seismic events. In this regard, local academic institutions and non-governmental organisations (NGOs) are critical mediators in reaching the community in greater depth, from which to bridge to external and/or governmental agencies based on existing links and trust. Social implications This study also shows social implications. As a case study-based research, the link developed with the local community will help coordinate actions in case an earthquake occurs and increase cohesion within the community towards a joint aim, in this case, to reduce the risk of disasters due to seismic events. Originality/value This paper accounts for a novel approach to documenting buildings in heritage settlements prone to earthquakes that uses the digital record as (1) a basis to assess and intervene in the built environment and better understand how it supports the local community’s ways of living and maintaining buildings; and (2) a platform for local engagement and agency in planning and re-construction as a post-disaster mitigation measure.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,054 | 0,014 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».