Publications
A ChiMerge–WOE Ensemble Learning Framework for Landslide Susceptibility Assessment in Jiuzhaigou County, China
A novel framework combining ChiMerge discretization, Weight of Evidence (WOE) transformation, and tree-based ensemble learning achieves high accuracy in mapping landslide susceptibility in Jiuzhaigou Valley, China. The approach outperforms conventional methods by identifying statistically meaningful thresholds in conditioning factors and quantifying their association with landslides, leading to an AUC of 0.9432 for the best-performing model (WOE-CatBoost). High-risk zones, covering 28.59% of the study area, account for 85.96% of observed landslides, primarily in steep valleys, fractured lithological areas, and regions affected by human activities such as road construction and tourism development. This method enhances both prediction accuracy and interpretability, offering critical spatial support for landslide prevention and sustainable land management.
Object‑oriented landslide identification and susceptibility assessment for the Jiuzhaigou earthquake by integrating NDVI difference
A groundbreaking study identifies and maps earthquake-triggered landslides (EqTLs) with unprecedented accuracy in the Jiuzhaigou Valley. By integrating object-oriented detection with a Random Forest susceptibility model—enhanced by Normalized Difference Vegetation Index (NDVI) differences—the research pinpoints 841 landslides (covering 11.96 km²), primarily concentrated near the Huya Fault and on steep slopes (30–50°). The model achieved high accuracy (AUC = 0.98), highlighting fault distance, peak ground acceleration (PGA), and slope angle as critical controls. Notably, 95% of landslides were found in very high susceptibility zones, with a density of 2.83/km². This approach offers a robust framework for spatial analysis and risk management in alpine valley regions, advancing our understanding of seismic-induced geological hazards.
Analysis of disaster-affected population mobility through grid-aggregated mobile location data: The 2017 Jiuzhaigou earthquake, China
A novel analysis of grid-aggregated mobile location data reveals distinct evacuation patterns following the 2017 Jiuzhaigou earthquake, despite China's privacy regulations limiting individual trajectory data. Using empirical orthogonal function (EOF) analysis, researchers identified two primary evacuation routes: one extending northwest from Chuanzhusi Town and another southeast through Shuanghe Town. The study found a continuous outflow of population from the Jiuzhaigou Valley between midnight and 20:00, with significant increases in mobile activity along key roads during early morning hours (midnight to 10:00). Unlike traditional clustering methods, EOF analysis effectively pinpointed impact zones and inferred evacuation directions without relying on individual trajectory data. This approach demonstrates the potential of grid-based mobile data for disaster research, offering critical insights into population mobility during crises.
Influencing eco-conscious travelers: The role of green marketing in promoting sustainable destinations
Green marketing by eco-tourism providers significantly boosts tourists' intentions to visit sustainable destinations, primarily through fostering pro-environmental attitudes and trust in green destinations. A study of 317 tourists in Jiuzhaigou Valley, China, found that biospheric values—strong environmental concern—amplified the effect of destination trust on visit intentions, especially for high-value tourists, while eco-friendly attitudes consistently influenced intentions regardless of these values. The research applies customer engagement theory to show how meaningful green marketing interactions drive value co-creation and sustainable tourism behaviors. These insights offer actionable strategies for marketers and policymakers aiming to engage eco-conscious travelers effectively.
Low-Altitude UAV Trajectory Optimization for Complex 3D Terrains Based on Energy Consumption
A novel three-dimensional flight energy consumption model for UAVs, combined with an upgraded ant colony algorithm, significantly reduces energy usage by 9.1% to 36.3% compared to existing greedy algorithms while ensuring comprehensive coverage of complex terrains like Jiuzhaigou Valley. The approach incorporates dynamic pheromone updating and elite strategies to optimize climb energy consumption and obstruction penalties, addressing the limitations of traditional two-dimensional trajectory planning. Simulation experiments using real topographic data validate its effectiveness in enhancing UAV efficiency for applications such as environmental monitoring and geographic mapping.
Quantitative risk assessment and eco-engineering mitigation strategies for debris flows utilizing dynamic process simulation in Shuzheng gully, Jiuzhaigou valley scenic and historic interest area
A novel pine pile–gabion composite dam (PPGD) system, integrated with dynamic process simulation and adaptive eco-engineering strategies, effectively mitigates debris flow risks while preserving ecological integrity. Using high-resolution modeling, researchers simulated debris flows under 20- and 50-year rainfall return periods in Shuzheng gully, Jiuzhaigou Valley, revealing peak velocities of 6.49 m/s and discharges of 38.33 m³/s for the latter. The PPGD system reduced total inundation extent by 45.78% and decreased peak flow velocities downstream by up to 45.34%, demonstrating its potential for sustainable risk management in ecologically sensitive UNESCO World Heritage sites. This approach balances risk reduction with environmental conservation, offering a scalable solution for mountain areas vulnerable to debris flows.
Seasonal Coloration and Ecological Adaptations of Adventitious Roots of Four Salicaceous Species in Jiuzhaigou World Natural Heritage Site, Southwestern China
Researchers have uncovered a novel link between the seasonal coloration of adventitious roots in Salicaceous species and environmental conditions, revealing their potential as bioindicators for wetland ecosystems. The study found that these roots, prominent in Jiuzhaigou Valley's tufa wetlands, transition from red or pink hues in summer to reddish-brown, maroon, or gray shades during other seasons due to the oxidation of proanthocyanidins influenced by temperature and light. This dynamic color change reflects seasonal climate fluctuations, offering a new biomarker for assessing environmental impacts. The roots also exhibit specialized adaptations, such as well-developed aerenchyma and floating habits, which enhance oxygen uptake in aquatic habitats. The findings provide insights into ecosystem management in karst areas.
Siphlonurus davidi
A detailed re-description of the mayfly species Siphlonurus davidi, found exclusively in Jiuzhaigou Valley, Sichuan Province, China, challenges previous diagnostic criteria used to distinguish it from closely related species. The study examines 198 specimens (65 nymphs and 133 imagos) collected between 2013 and 2023, providing comprehensive morphological descriptions of both life stages. Key findings include the identification of consistent diagnostic features in nymphs—such as reddish-brown oblique stripes on abdominal sterna and posterolateral spines—and distinct color patterns in adult males and females. Notably, the research debunks three proposed diagnostic traits by Yang et al. (2023), demonstrating that sclerotization patterns of the penis lobes and spine development are similar across S. davidi, S. dongxi, and a newly described species, S. orientalis. This work clarifies taxonomic confusion in the genus Siphlonurus, offering critical insights for future biodiversity studies in this UNESCO World Heritage Site.
3D Modelling and Measuring Dam System of a Pellucid Tufa Lake Using UAV Digital Photogrammetry
A novel approach using UAV digital photogrammetry successfully captured the complete 3D morphology of a tufa dam system, including both above-water and submerged components, overcoming previous limitations in measuring underwater structures. This study, conducted at Wolong Lake in Jiuzhaigou Valley, China, combined refraction correction for underwater DEM retrieval with ground interpolation to eliminate vegetation obstructions. The resulting high-precision 3D models enabled accurate measurement of dam dimensions along the lake's centerlines and provided insights into the formation and development of tufa dams through hydrodynamic analysis. This method offers a scalable solution for studying similar fluvial tufa landscapes, advancing our understanding of their geological processes.
Analysis of ecosystem resilience in Jiuzhaigou Valley Scenic Area under the effect of geohazards
A significant rebound in Jiuzhaigou Valley's ecosystem resilience is attributed to ecological restoration efforts, with habitat quality recovering to 98.88% of its historical peak by 2020. The study highlights that artificial restoration effectively mitigates geohazards' impact on this UNESCO World Heritage site. Using remote sensing and the InVEST model, researchers quantified ecosystem recovery under different restoration scenarios, demonstrating that forests are crucial for maintaining habitat quality. This work underscores the positive role of targeted ecological interventions in reducing geohazard risks and accelerating ecosystem service recovery.
Exploiting satellite SAR for archaeological prospection and heritage site protection
Advanced satellite Synthetic Aperture Radar (SAR) and optical remote sensing techniques have significantly enhanced archaeological prospection and heritage site protection, particularly for buried or subsurface assets. A study demonstrates that these methods, combined with big data analysis and high-performance computing, can effectively detect archaeological features, monitor threats from ground instability or urban development, and assess post-disaster impacts in natural reserves. The research showcases six case studies—including the Ostia-Portus area (Italy), Wuhan (China), Jiuzhaigou National Park (China), and Siberia’s ‘Valley of the Kings’ (Russia)—using high-resolution satellite and UAV imagery, DEMs, and geodetic data. Findings highlight SAR’s advantages in semi-vegetated landscapes while acknowledging limitations, offering a robust framework for heritage preservation.
Style evolution rules of Tibetan dwellings in the Amdo Tibetan region: An architectural typology perspective
Tibetan dwellings in Jiuzhaigou Valley, part of the Amdo Tibetan region, are evolving toward originality in design, modernity in structure, and autonomy in construction. This shift reflects a blend of cultural influences and environmental interactions, with rural settlements shaped by local managers, villagers, and their surroundings. The study employed architectural typology to classify folk styles through field research and a quantitative framework ('classified-iconic index-characteristic calculation index'), revealing how these factors manifest in dwelling appearances. These findings offer new theoretical perspectives for residential landscape studies and inform conservation strategies for ethnic areas, supporting rural revitalization efforts.
Susceptibility Mapping of Unhealthy Trees in Jiuzhaigou Valley Biosphere Reserve
A novel technology integration approach combining remote sensing and quantitative retrieval successfully mapped the susceptibility of unhealthy trees in Jiuzhaigou Valley, a UNESCO World Heritage Site and biosphere reserve. The method, utilizing high-resolution WorldView-2 satellite images and object-oriented classification with spectral and texture features, achieved an F1 Score exceeding 75%. Further analysis on Sentinel-2 data yielded susceptibility maps with an Area Under the Curve (AUC) over 0.85. Key findings reveal that while Jiuzhaigou's forests show resilience to geological disasters, human activities have increasingly adverse effects on vegetation health, necessitating urgent attention. This cost-effective methodology offers a scalable solution for monitoring and early warning in similar biosphere reserves.
Declining tree growth rates despite increasing water-use efficiency under elevated CO2 reveals a possible global overestimation of CO2 fertilization effect
A long-term study at Jiuzhaigou Valley, a UNESCO World Heritage Site in Southwest China, reveals that elevated CO2 (eCO2) may not enhance tree growth as previously thought. Despite increasing intrinsic water-use efficiency (iWUE), trees exposed to higher localized eCO2 due to intensive tourism showed declining growth rates, likely due to stomatal closures. This challenges the global overestimation of CO2 fertilization effects on forests, particularly under dry temperate conditions. The research used a novel dendrochronological approach comparing two valleys with contrasting anthropogenic activities, providing new insights into the complex interactions between CO2, climate change, and forest resilience.
Impact Assessment of the Ms7.0 Earthquake on Jiuzhaigou Valley from the Perspective of Vegetation Net Primary Productivity
A significant decline and subsequent recovery in vegetation net primary productivity (NPP) were observed in Jiuzhaigou Valley following the Ms7.0 earthquake on 8 August 2017. The study, using the Carnegie-Ames-Stanford Approach (CASA) model, found that NPP values dropped sharply by up to 27.2% in areas affected by landslides and debris flows but showed strong resilience, with a 23.0% increase in recovery within a year. Vegetation in debris flow zones demonstrated the fastest recovery, while overall NPP reductions lessened annually post-earthquake. The research introduces a vulnerability-resilience assessment system linked to seismic intensity, providing critical insights for ecosystem impact assessments and conservation strategies.
Automated Mapping of Ms 7.0 Jiuzhaigou Earthquake (China) Post-Disaster Landslides Based on High-Resolution UAV Imagery
A novel method combining high-resolution UAV imagery and machine learning achieved near-perfect accuracy (99.89%) in mapping landslides triggered by the 2017 Ms 7.0 Jiuzhaigou earthquake in China, surpassing traditional manual interpretation. The approach used a support vector machine (SVM) classification model integrated with pre-seismic road and village data to automatically identify landslide distribution with high precision (Kappa coefficient > 0.9). This advancement significantly improves post-disaster response capabilities by enabling rapid and accurate landslide mapping, critical for emergency rescue operations. The study also revealed spatial patterns of earthquake-triggered landslides, influenced by factors such as altitude, slope gradient, aspect, and proximity to faults, providing valuable insights for future risk assessment and susceptibility prediction in UNESCO World Heritage Sites.
Engineering Planning Method and Control Modes for Debris Flow Disasters in Scenic Areas
A novel engineering planning method and four control modes for debris flow disasters in scenic areas, including Jiuzhaigou Valley, have been developed. These strategies address the unique challenges posed by debris flows in UNESCO World Heritage Sites, where landscape and ecosystem damage is a significant concern alongside infrastructure threats. The proposed 'blocking + deposit stopping,' 'deposit stopping,' 'blocking,' and 'drainage + deposit stopping' modes provide a systematic approach to post-earthquake disaster management. The method quantifies debris flow material retention and enables rapid planning of control projects, addressing gaps in current practices that lack systematic scenic area planning. Field investigations and data from Jiuzhaigou Valley's gullies informed the development of these solutions.
Monitoring and Assessment for the Susceptibility of Landslide Changes After the 2017 Ms 7.0 Jiuzhaigou Earthquake Using the Remote Sensing Technology
A net increase of 1.2 km² in landslide area was observed at Jiuzhaigou Valley up to September 2019 following the 2017 Ms 7.0 earthquake. This expansion, driven by coseismic and post-seismic landslides along with vegetation degradation, is primarily linked to debris flows triggered by torrential rainfall. Remote sensing technology, including Support Vector Machine classification and Geographic Information System analysis, revealed that susceptibility to post-seismic landslides is influenced by slope, altitude, aspect, peak ground acceleration, fault lines, and strata, with higher susceptibility paradoxically found in areas with lower initial coseismic landslide density. The study highlights the need for proactive monitoring of unstable slopes to mitigate potential landslides, offering a model for assessing seismic-induced geological risks in mountainous regions.
Quantitative multi-hazard risk assessment to buildings in the Jiuzhaigou valley, a world natural heritage site in Western China
A quantitative multi-hazard risk assessment reveals that debris flows pose significantly higher risks to buildings in the Jiuzhaigou Valley compared to rockfalls. The study integrates geomorphological and geotechnical analyses with historical records to estimate hazard occurrence probabilities, while run-out simulations and building vulnerability assessments inform spatial impact likelihoods. Risk curves for both hazards were generated, accounting for uncertainties through error propagation techniques. Multi-hazard risk maps highlight debris flows as the dominant threat, emphasizing the need for targeted mitigation measures in high-risk areas to protect vulnerable residential structures.
Case study on debris-flow hazard mitigation at a world natural heritage site, Jiuzhaigou Valley, Western China
A comprehensive debris-flow prevention and control system, tailored to the topographic features of Jiuzhaigou Valley's gullies, was developed following the 2017 earthquake that increased loose material and debris-flow activity. The study focuses on Xiajijie Lake gully, analyzing its disaster history and formation while proposing principles and measures for mitigation, including lateral diversion and deposition at the outlet. Environmental considerations were also integrated, such as using galvanized wire gabions to reduce impact force and planting bushes or grass on retaining walls for aesthetic enhancement. This approach combines structural and environmental strategies to mitigate debris-flow hazards in UNESCO World Heritage Sites.
Characteristics of a Debris Flow Disaster and Its Mitigation Countermeasures in Zechawa Gully, Jiuzhaigou Valley, China
A devastating debris flow event in Zechawa Gully, Jiuzhaigou Valley, China, was triggered by heavy rainfall following the 2017 Ms 7.0 earthquake, causing significant traffic disruption and property damage. Research reveals that a failed check dam amplified the debris flow's peak discharge, intensifying its destructive impact. The study proposes optimized mitigation strategies combining blocking and deposit-stopping measures, which were successfully implemented in May 2019 to control subsequent debris flows, including one on June 21, 2019. These findings highlight the critical role of engineered countermeasures in managing post-earthquake disaster risks, particularly in earthquake-prone World Heritage Sites like Jiuzhaigou Valley.
Remote Sensing Detection and Impact Analysis of Tibetan Human Landscape in Jiuzhaigou
A significant increase in vulnerability has been detected in the Tibetan human landscape of Jiuzhaigou Valley, with natural environmental factors playing a more substantial role than tourism activities. However, tourism's negative impact on protection efforts is nearly three times greater than the positive benefits of protective measures. The study utilized remote sensing and spatial data to quantitatively evaluate landscape vulnerability, offering a rapid tool for change detection analysis. It also highlights the need to reconstruct current management models to address the disappearing human landscape, particularly as tourism development threatens the Balance Zone.
Study on the tufa Thickness and Formation Age of Dyke at Sparkling Lake, Jiuzhaigou Scenic Area, Sichuan Province
A comprehensive study of Sparkling Lake’s Dyke in Jiuzhaigou Valley, Sichuan Province, reveals that the tufa thickness ranges from 8 meters to 22.78 meters, underlain by glacial till, with a formation age spanning 4.3 thousand to 27 thousand years ago. Carbon-14 dating indicates a deposition rate of 2.25 mm to 9.35 mm per year, challenging the assumption of simple bottom-up overlaying in tufa deposition. The research, conducted post-earthquake, combines large-scale geological surveys, drone imagery (dronestagram), and minor-caliber backpack drilling to analyze the dyke’s structure and evolution, providing critical data for ecological restoration efforts at this UNESCO World Heritage Site.
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