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Understanding the kinematic characteristics of the Longitudinal Valley Fault Zone (LVFZ) can help us to better understand the evolution of orogens. The 2022 Mw7.0 Taitung earthquake that occurred in Taiwan provides us with a good opportunity to understand the motion characteristics of the Central Range Fault (CRF) and the strain partitioning pattern within the Longitudinal Valley Fault (LVF). We obtained the coseismic displacement and slip distribution of the 2022 Taiwan earthquake based on the strong-motion and GPS data available. The causative fault of this earthquake is the west-dipping Central Range Fault, which is buried beneath the western boundary of the LVF. The coseismic displacement field exhibits a quadrant distribution pattern, indicating a left-lateral strike-slip mechanism with a maximum displacement exceeding 1.25 m. The joint inversion results show that the size of the main asperity is 40 km × 20 km, and the maximum slip amount of 2.6 m is located at a depth of 10 km, equivalent to an earthquake of Mw7.04. The LVFZ is composed of LVF and CRF, which accommodates nearly half of the oblique convergence rate between the Philippine Sea Plate and the Eurasian Plate. There is a phenomenon of strain partitioning in the southern segment of the Longitudinal Valley Fault Zone. The Central Mountain Range Fault is primarily responsible for accommodating strike-slip motion, while the Longitudinal Valley Fault is mainly responsible for accommodating thrust motion. [ABSTRACT FROM AUTHOR]

The problem of estimating earthquake risk is one of the primary themes for researchers and investigators in the field of geosciences. The combined assessment of spatial probability and the determination of earthquake risk at large scales is challenging. To the best of the authors' knowledge, there no updated earthquake-hazard-and-risk assessments for the Eurasia region have been published since 1999. Considering that Eurasia is characterized by a seismically active Alpine–Himalayan fault zone and the Pacific Ring of Fire, which are frequently affected by devastating events, a continental-scale risk assessment for Eurasia is necessary to check the global applicability of developed methods and to update the earthquake-hazard, -vulnerability, and -risk maps. The current study proposes an integrated deep-transfer-learning approach called the gated recurrent unit–simple recurrent unit (GRU–SRU) to estimate earthquake risk in Eurasia. In this regard, the GRU model estimates the spatial probability, while the SRU model evaluates the vulnerability. To this end, spatial probability assessment (SPA), and earthquake-vulnerability assessment (EVA) results were integrated to generate risk A, while the earthquake-hazard assessment (EHA) and EVA were considered to generate risk B. This research concludes that in the case of earthquake-risk assessment (ERA), the results obtained for Risk B were better than those for risk A. Using this approach, we also evaluated the stability of the factors and interpreted the interaction values to form a spatial prediction. The accuracy of our proposed integrated approach was examined by means of a comparison between the obtained deep learning (DL)-based results and the maps generated by the Global Earthquake Model (GEM). The accuracy of the SPA was 93.17%, while that of the EVA was 89.33%. [ABSTRACT FROM AUTHOR]

Vegetation recovery monitoring is critical for assessing denudation areas after landslides have occurred. A long-term and broad area investigation using remote sensing techniques is an efficient and cost-effective approach incorporating the consideration of radiometric correction and seasonality variations across multi-date satellite images. This paper investigates long-term vegetation recovery using 14 SPOT satellite images spanning from 1999 to 2011 over the landslide area of Mt. Jou-Jou in central Taiwan, which was caused by the Chi-Chi earthquake in 1999. The vegetation status was evaluated by the Normalized Difference Vegetation Index (NDVI) with radiometric correction between multi-date images based on pseudoinvariant features, and subsequently a vegetation recovery rate (VRR) model was empirically established after seasonality adjustment was performed on the multi-date NDVI images. An increasing tendency of the vegetation recovery in the landslide area of Mt. Jou-Jou appeared based on the NDVI value rising to 0.367 in March 2011 from -0.044 right after the catastrophic earthquake. The vegetation recovery rate with seasonality adjustment approached 81.5% for the total area and 81.3% for the landslide area through 12 years succession. The seasonality adjustment also enhanced the VRR model with a determination coefficient that increased from 0.883 to 0.916 for the landslide area and from 0.584 to 0.915 for the total area, highlighting the necessity of seasonality adjustment in multi-date vegetation observations using satellite images. Furthermore, the association between precipitation and NDVI was discussed, and the inverse relationship with the reoccurrence of high-intensity short-duration rainfall and yearly heavy rainfall was observed, in agreement with the on-site investigation. [ABSTRACT FROM AUTHOR]

This study uses three periods of airborne laser scanning (ALS) digital elevation model (DEM) data to analyze the short-term erosional features of the Tsaoling landslide triggered by the 1999 Chi-Chi earthquake in Taiwan. Two methods for calculating the bedrock incision rate, the equal-interval cross section selection method and the continuous swath profiles selection method, were used in the study after nearly ten years of gully incision following the earthquake-triggered dip-slope landslide. Multi-temporal gully incision rates were obtained using the continuous swath profiles selection method, which is considered a practical and convenient approach in terrain change studies. After error estimation and comparison of the multi-period ALS DEMs, the terrain change in different periods can be directly calculated, reducing time-consuming fieldwork such as installation of erosion pins and measurement of topographic cross sections on site. The gully bedrock incision rate calculated by the three periods of ALS DEMs on the surface of the Tsaoling landslide ranged from 0.23 m/year to 3.98 m/year. The local gully incision rate in the lower part of the landslide surface was found to be remarkably faster than that of the other regions, suggesting that the fast incision of the toe area possibly contributes to the occurrence of repeated landslides in the Tsaoling area. [ABSTRACT FROM AUTHOR]

The M w 7.6 Chi-Chi earthquake struck central western Taiwan in 1999. The rupture was complex with several dislocations along the 100-km long Chelungpu thrust fault. Revisiting this earthquake is a challenge, as the precision and coverage of the data sets available are quite poor. Furthermore, the topographic and vegetation coverage complexity of the area prevents coherent radar images. In this paper, radar and optical images, and terrestrial geodetic measurements, were utilised to study the fault. The Particle Swarm Optimization and Okada Inversion (PSOKINV) geodetic inversion package was used with the generalized Akaike's Bayesian Information Criterion (gABIC) to precisely determine the slip distribution and relative weighting of datasets. Differences in results using the data sets jointly or separately (e.g., under-estimation due to InSAR, inconsistencies in SPOT offsets, smoother slip distribution with gABIC weighting) are observable. Most of the energy was released in the northern part of the fault, where the strike veers toward the east, and mainly at depths less than 4 km. The PSOKINV-gABIC approach is viable for the study of complicated cases such as the Chi-Chi earthquake and can significantly benefit the weight determination and physical realism of the fault geometry. [ABSTRACT FROM AUTHOR]

Despite numerous studies on the effect of a cold weather disaster on fisheries in 2008, no operational systems have been developed to monitor the threat of such an event to mariculturists in the Penghu Islands (PHI) region of Taiwan. The present study employed a suitable aquaculture site selection map of the inner bay of the PHI to reduce aquaculture losses and mortality rates of cobia (Rachycentron canadum) during extreme events. Daily marine environmental data, including sea surface temperature (SST), chlorophyll-a concentration (chl-a), and wind speed in the winter, were collected. An extreme event was defined as a period of over 11 days in a month of strong winds (>6 m/s). Four parameters in the PHI inner bay, including SST, cold-water intrusion days, chl-a, and offshore distance to the PHI coastline, were used to evaluate suitable aquaculture sites for cobia culture. The results indicated that La Niña events could not be used as a factor to detect cold-water intrusion events and select suitable aquaculture sites in the PHI. The evaluated suitable aquaculture site selection map, obtained using an arithmetic mean model and a geometric mean model, revealed that the avoidance sites during extreme events were concentrated in the northern and northwestern PHI. Suitable areas were concentrated in the southeastern areas. We further suggested that commercial cobia aquaculture operations in the PHI inner bay could be moved to the suitable sites in southeastern PHI during extreme events. [ABSTRACT FROM AUTHOR]