Contributing to the United Nations 2030 Sustainable Development Goals (SDGs) within Target 11.4 “Strengthen efforts to protect and safeguard the world’s cultural and natural heritage”, it is critical to monitor the spatial and temporal stabilities of cultural heritages. The study of the interactive relationship between earthquakes and the protection of cultural heritages needs to be strengthened. On 27 September 2021, the destructive Mw 5.9 Arkalochori earthquake occurred ~25 km away from the city of Heraklion (Greece) where the Heraklion City Wall (HCW), a representative cultural heritage of Greece and Europe, was located. This offered a proper case to investigate the shortcomings aforementioned. Here, we intend to set up and answer the following three questions (Whether, Where and What, 3Ws): Whether there were impacts on the HCW caused by the Arkalochori earthquake? Where did the maximum deformation occur? What was the relationship between seismic deformation between the epicenter and the HCW over time? We performed two-dimensional (2D) InSAR measurements for both co-seismic and post-seismic deformations using the ascending and descending Sentinel-1A SAR images. The spatial-temporal characteristics of Up–Down (UD) and East–West (EW) were revealed. The 2D co-seismic deformation field showed that the near-filed deformations were dominating compared with the deformations at the HCW, the UD deformation was mainly featured with subsidence with a maximum value of ~21 cm, the EW deformation was ~9 cm westward and ~10 cm eastward. The time-series measurements showed that: (1) temporally, the HCW responded quickly to the Arkalochori earthquake, and the accumulative deformations at the seven different bastions of the HCW showed the same trend as the near-field area over time. (2) Spatially, the closer to the Mw 5.9 epicenter, the larger the deformations that occurred. (3) The EW and UD deformation trends of the HCW that were consistent with the Mw 5.9 epicenter were interrupted at the middle time spot (22 January 2022), indicating the influence of another earthquake sequence consisting of eight earthquakes with magnitudes larger than 3.5 that happened on 16–18 January 2022. Respectively, to summarize and address the aforementioned 3Ws based on the post-seismic analysis accomplished by the MSBAS method, the Arkalochori earthquake did affect the HCW; besides, the influences of the ~13 km earthquake sequence were also detected; the nearest part to the epicenter suffered the most; the deformation trends of the HCW were approximately the same with the epicenter area of the Arkalochori earthquake both in the UD and EW directions.

Jiuzhaigou Valley is recognized as both a world natural heritage site and a biosphere reserve. Conducting research on vegetation health within its scope can provide a demonstration role for sustainable development research. In this study, we proposed a technology integration approach that combined remote sensing intelligent identification and quantitative retrieval, and achieved vegetation health monitoring and susceptibility mapping of unhealthy trees. Leveraging WorldView-2 high-resolution satellite images, unhealthy trees were elaborately identified through the object-oriented classification method employing spectral and texture features, with F1 Score exceeding 75%. By applying fuzzy operations on indices related to leaf pigment and canopy architecture, we ultimately generated susceptibility maps of unhealthy trees on Sentinel-2 satellite images, with Area Under the Curve (AUC) exceeding 0.85. Our findings underscore that the vegetation health in Jiuzhaigou Valley is predominantly influenced by human activities and geological hazards. The forests of Jiuzhaigou Valley exhibit a certain degree of resilience to geological disasters, while human activities have been continuously exerting adverse effects on forest health in recent years, necessitating heightened attention. The methodology proposed in this study for mapping unhealthy trees susceptibility presents a cost-effective solution that can be readily applied for vegetation health monitoring and early warning in analogous biosphere reserves.