Conceptualization of territorial resilience potential indicators to coastal hazards through the use of unmanned aerial vehicles

Major natural hazards in recent decades have led to a revisiting of the concept of resilience, particularly in order to analyze traditional models of response to an unforeseen event and post-crisis management mechanisms. For resilience to be an applicable/operational concept to guide management and inform decisions, it must ultimately be characterized for its assessment. This assessment can be done through the identification of indicators specifically contextualized to the study site and object of study. However, today, operationalizing of the concept of resilience tends to draw on annual censuses or aggregated data, providing a generalized large scale view of the territorial resilience potential. The objective of this study is to identify a table of Territorial Resilience Potential (TRP) indicators to coastal hazards applied to coastal island territories, supplied by data from Unmanned Aerial Vehicles (UAVs) to allow for rapid and site specific data acquisition for repetitive surveys. This acquisition method makes it possible to calculate a number of relevant indicators for assessing the resilience potential of coastal areas. In particular, it allows rapid updating of data following major meteorological events and identification of hot and cold spots of resilience potential of a specific study site. To demonstrate the applicability of this method to island territories, the island of Bora Bora in French Polynesia was used as a case study. Finally, these kinds of results can be fed through a spatial decision support system to help decision-makers choose an adaptation and protection strategy in order to move towards resilient territories, over a long period of time. • UAVs can act as a complementary data acquisition when operationalizing the concept of resilience. • Unmanned aerial vehicles will allow for rapid and site specific data acquisition for repetitive surveys. • Creation of a table of territorial resilience potential indicators for coastal island territories in the face of natural hazards. • Fed through a spatial decision support system, this data can help decision-makers choose efficient climate strategies.

Authors

Institutions

Publication Details

Journal
Ocean & Coastal Management
Published
2024-09-06
DOI
https://doi.org/10.1016/j.ocecoaman.2024.107350
Citations
2
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
2.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Conceptualization of territorial resilience potential indicators to coastal hazards through the use of unmanned aerial vehicles

Jérémy Jessin, Charlotte Heinzlef, Nathalie Long, Damien Serre
2 citations
Ocean & Coastal Management
Disaster Management and Resilience
2.26
article

Conceptualization of territorial resilience potential indicators to coastal hazards through the use of unmanned aerial vehicles

Jérémy Jessin, Charlotte Heinzlef, Nathalie Long, Damien Serre
article en
2 citations

Abstract

Major natural hazards in recent decades have led to a revisiting of the concept of resilience, particularly in order to analyze traditional models of response to an unforeseen event and post-crisis management mechanisms. For resilience to be an applicable/operational concept to guide management and inform decisions, it must ultimately be characterized for its assessment. This assessment can be done through the identification of indicators specifically contextualized to the study site and object of study. However, today, operationalizing of the concept of resilience tends to draw on annual censuses or aggregated data, providing a generalized large scale view of the territorial resilience potential. The objective of this study is to identify a table of Territorial Resilience Potential (TRP) indicators to coastal hazards applied to coastal island territories, supplied by data from Unmanned Aerial Vehicles (UAVs) to allow for rapid and site specific data acquisition for repetitive surveys. This acquisition method makes it possible to calculate a number of relevant indicators for assessing the resilience potential of coastal areas. In particular, it allows rapid updating of data following major meteorological events and identification of hot and cold spots of resilience potential of a specific study site. To demonstrate the applicability of this method to island territories, the island of Bora Bora in French Polynesia was used as a case study. Finally, these kinds of results can be fed through a spatial decision support system to help decision-makers choose an adaptation and protection strategy in order to move towards resilient territories, over a long period of time. • UAVs can act as a complementary data acquisition when operationalizing the concept of resilience. • Unmanned aerial vehicles will allow for rapid and site specific data acquisition for repetitive surveys. • Creation of a table of territorial resilience potential indicators for coastal island territories in the face of natural hazards. • Fed through a spatial decision support system, this data can help decision-makers choose efficient climate strategies.

Ocean & Coastal ManagementVol. 257
Centre National de la Recherche Scientifique (FR), Université de Versailles Saint-Quentin-en-Yvelines (FR), LIttoral ENvironnement et Sociétés (FR), Hyperion Technologies (Canada) (CA), Santé et Services des Ecosytèmes Polynésiens (PF), La Rochelle Université (FR), University of French Polynesia (PF)
Climate action
Openalex Percentile: Top 10%
Disaster Management and Resilience
2.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.