Zehua Zhang

Australian cities have long remained "cycling-starter" cities, with fewer than 3% of commuters using bicycles, despite sustained policy efforts. Understanding this low uptake requires a comprehensive examination of population-level determinants of cycling ownership and behaviour. This study investigates cycling behaviour across Australia's four largest metropolitan areas-Sydney, Melbourne, Brisbane, and Perth-using a representative survey of transport attitudes and behaviours. Multi-city, multipurpose mixed logit models are estimated, applying coefficient scaling to enable valid cross-city comparisons. This modelling framework allows us to identify both common determinants and city-specific differences. Results show that cycling remains a minority activity for everyday travel, with only 23-24% of respondents reporting cycling in the past year, though Perth is higher at 28%. Higher cycling propensity is associated with being male and younger, while pro-cycling perceptions and proximity to the CBD, and higher access to cycleways, emerge as the strongest enablers across all cities. The analysis also reveals substantial variation in factors influencing cycling for transport versus recreation. In particular, significant behavioural heterogeneity is observed in responses to accessibility variables, including distance to the CBD for transport cycling and access to cycleways for recreational cycling. By providing city-comparable behavioural evidence using a unified modelling framework, this study advances understanding of cycling adoption in low-cycling contexts. The findings highlight the importance of policies that improve equitable access to bicycle ownership, expand extensive, well-connected cycling networks, and plan for cycling perception uptake campaigns.

Landslides are among the most frequent geological hazards, often resulting in casualties and economic losses, particularly in alpine valley areas characterized by complex topography and dense vegetation. Landslides in these regions are distinguished by their high altitude, concealment, and sudden onset, which render traditional monitoring methods inefficient. This study proposes a landslide monitoring method for complex environments that leverages multi-source remote sensing data, incorporating the radiative transfer model and Small Baseline Subset-Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology. The proposed method was implemented to monitor the instability of the Baige landslide in Tibet, China. The results show that the vegetation Canopy Water Content (CWC) estimated using the radiative transfer model indirectly reflects landslide susceptibility. Specifically, excessive soil moisture from rainfall reduces oxygen in plant roots, affecting growth and lowering canopy water content. The region with lower Canopy Water Content (CWC < 0.04) exhibited an increasing trend in the number of pixels, rising from 271 to 549 before the landslide event, indicating poorer vegetation conditions in the area. Additionally, the SBAS-InSAR technique was utilized to extract surface displacement, achieving a maximum displacement of 112 mm during the monitoring period. Ultimately, the spatial changes of the two monitoring signals exhibited a high consistency. This study enhances the reliability of landslide displacement monitoring in complex environments and provides substantial scientific support for future large-scale monitoring efforts.

Transportation is a key component in urban design for cities’ efficiency and residents’ life quality, and GIS has the capability of handling data management, model design, and scientific decision-making for transportation studies. This article reviews how spatial big data and analysis strategies help GIS-T studies from the phases of conceptual design, modelling, and decision-making. In this research, we firstly summarized categorizes of data objects and relevant information for real-world issues from transportation applications in the conceptual design phase. In the modelling phase, optimization strategies for transport planning and accessibility measures through network data were also summarized. Finally, we reviewed spatial analysis methods in supporting transport decision-making, and how spatial methods take advantage of geography features of transport variables in previous studies. Our research primarily focuses on geography research with transportation topics as applications, and this work can help transport experts to have a better understanding of GIS values for transportation modelling and planning.

Vegetation quality is crucial for maintaining ecological health, and remote sensing techniques offer precise assessments of vegetation’s environmental quality. Although existing indicators and remote sensing approaches provide extensive spatial coverage, challenges remain in effectively integrating diverse indicators for a comprehensive evaluation. This study introduces a comprehensive ecological quality index (EQI) to assess vegetation quality on the Mongolian Plateau from 2001 to 2020 and to identify the determinants of EQI variations over space and time. We developed the EQI using remotely sensed normalized difference vegetation index (NDVI) data and the net primary productivity (NPP). Our analysis revealed distinct spatial patterns, with high ecological quality concentrated in northern Mongolia and eastern Inner Mongolia. Temporal fluctuations, indicative of ecological shifts, were primarily observed in eastern Mongolia and specific zones of Inner Mongolia. We employed a Geographically Optimal Zones-based Heterogeneity (GOZH) model to analyze the spatial scales and interactions influencing EQI patterns. This study found that precipitation, with an Omega value of 0.770, was the dominant factor affecting the EQI, particularly at spatial scales of 40–50 km. The GOZH model provided deeper insights into the spatial determinants of the EQI compared with previous models, highlighting the importance of climatic variables and their interactions in driving ecological quality. This research enhanced our understanding of vegetation quality dynamics and established a foundation for ecosystem conservation and informed management strategies, emphasizing the critical role of climate, especially precipitation, in shaping ecological landscapes.