TY - JOUR
T1 - Combining remote sensing techniques and field surveys for post-earthquake reconnaissance missions
AU - Giardina, Giorgia
AU - Macchiarulo, Valentina
AU - Foroughnia, Fatemeh
AU - Jones, Joshua N.
AU - Whitworth, Michael R.Z.
AU - Voelker, Brandon
AU - Milillo, Pietro
AU - Penney, Camilla
AU - Adams, Keith
AU - Kijewski-Correa, Tracy
PY - 2023
Y1 - 2023
N2 - Remote reconnaissance missions are promising solutions for the assessment of earthquake-induced structural damage and cascading geological hazards. Space-borne remote sensing can complement in-field missions when safety and accessibility concerns limit post-earthquake operations on the ground. However, the implementation of remote sensing techniques in post-disaster missions is limited by the lack of methods that combine different techniques and integrate them with field survey data. This paper presents a new approach for rapid post-earthquake building damage assessment and landslide mapping, based on Synthetic Aperture Radar (SAR) data. The proposed texture-based building damage classification approach exploits very high resolution post-earthquake SAR data integrated with building survey data. For landslide mapping, a backscatter intensity-based landslide detection approach, which also includes the separation between landslides and flooded areas, is combined with optical-based manual inventories. The approach was implemented during the joint Structural Extreme Event Reconnaissance, GeoHazards International and Earthquake Engineering Field Investigation Team mission that followed the 2021 Haiti Earthquake and Tropical Cyclone Grace.
AB - Remote reconnaissance missions are promising solutions for the assessment of earthquake-induced structural damage and cascading geological hazards. Space-borne remote sensing can complement in-field missions when safety and accessibility concerns limit post-earthquake operations on the ground. However, the implementation of remote sensing techniques in post-disaster missions is limited by the lack of methods that combine different techniques and integrate them with field survey data. This paper presents a new approach for rapid post-earthquake building damage assessment and landslide mapping, based on Synthetic Aperture Radar (SAR) data. The proposed texture-based building damage classification approach exploits very high resolution post-earthquake SAR data integrated with building survey data. For landslide mapping, a backscatter intensity-based landslide detection approach, which also includes the separation between landslides and flooded areas, is combined with optical-based manual inventories. The approach was implemented during the joint Structural Extreme Event Reconnaissance, GeoHazards International and Earthquake Engineering Field Investigation Team mission that followed the 2021 Haiti Earthquake and Tropical Cyclone Grace.
KW - Building damage
KW - Haiti
KW - Intensity ratio image
KW - Landslides classification
KW - Remote reconnaissance
KW - Remote sensing
KW - SAR
KW - Texture analysis
UR - http://www.scopus.com/inward/record.url?scp=85163661892&partnerID=8YFLogxK
U2 - 10.1007/s10518-023-01716-9
DO - 10.1007/s10518-023-01716-9
M3 - Article
AN - SCOPUS:85163661892
SN - 1570-761X
VL - 22
SP - 3415
EP - 3439
JO - Bulletin of Earthquake Engineering
JF - Bulletin of Earthquake Engineering
IS - 7
ER -