The city of Christchurch, New Zealand, incurred significant damage due to a series of earthquakes in 2010 and 2011. The city had, by the late 2010s, regained economic and social normalcy after a sustained period of rebuilding and economic recovery. Through the concerted rebuilding effort, a modern central business district (CBD) with redesigned infrastructure and amenities was developed. The Christchurch rebuild was underpinned by a commitment of urban planners to an open and connected city, including the use of innovative technologies to gather, use and share data. As was the case elsewhere, the COVID-19 pandemic brought about significant disruptions to social and economic life in Christchurch. Border closures, lockdowns, trading limitations and other restrictions on movement led to changes in traditional consumer behaviors and affected the retail sector’s resilience. In this study, we used CBD pedestrian traffic data gathered from various locations to predict changes in retail spending and identify recovery implications through the lens of retail resilience. We found that the COVID-19 pandemic and its related lockdowns have driven a substantive change in the behavioral patterns of city users. The implications for resilient retail, sustainable policy and further research are explored.
Within four weeks of the September 4 2010 Canterbury Earthquake a new, loosely-knit community group appeared in Christchurch under the banner of “Greening the Rubble.” The general aim of those who attended the first few meetings was to do something to help plug the holes that had already appeared or were likely to appear over the coming weeks in the city fabric with some temporary landscaping and planting projects. This article charts the first eighteen months of Greening the Rubble and places the initiative in a broader context to argue that although seismic events in Christchurch acted as a “call to palms,” so to speak, the city was already in need of some remedial greening. It concludes with a reflection on lessons learned to date by GTR and commentary on the likely issues ahead for this new mini-social-environmental movement in the context of a quake-affected and still quake-prone major New Zealand city. One of the key lessons for GTR and all of those involved in Christchurch recovery activities to date is that the city is still very much in the middle of the event and is to some extent a laboratory for seismic and agency management studies alike.
Tree mortality is a fundamental process governing forest dynamics, but understanding tree mortality patterns is challenging because large, long-term datasets are required. Describing size-specific mortality patterns can be especially difficult, due to few trees in larger size classes. We used permanent plot data from Nothofagus solandri var. cliffortioides (mountain beech) forest on the eastern slopes of the Southern Alps, New Zealand, where the fates of trees on 250 plots of 0.04 ha were followed, to examine: (1) patterns of size-specific mortality over three consecutive periods spanning 30 years, each characterised by different disturbance, and (2) the strength and direction of neighbourhood crowding effects on sizespecific mortality rates. We found that the size-specific mortality function was U-shaped over the 30-year period as well as within two shorter periods characterised by small-scale pinhole beetle and windthrow disturbance. During a third period, characterised by earthquake disturbance, tree mortality was less size dependent. Small trees (,20 cm in diameter) were more likely to die, in all three periods, if surrounded by a high basal area of larger neighbours, suggesting that sizeasymmetric competition for light was a major cause of mortality. In contrast, large trees ($20 cm in diameter) were more likely to die in the first period if they had few neighbours, indicating that positive crowding effects were sometimes important for survival of large trees. Overall our results suggest that temporal variability in size-specific mortality patterns, and positive interactions between large trees, may sometimes need to be incorporated into models of forest dynamics.
Disasters are a critical topic for practitioners of landscape architecture. A fundamental role of the profession is disaster prevention or mitigation through practitioners having a thorough understanding of known threats. Once we reach the ‘other side’ of a disaster – the aftermath – landscape architecture plays a central response in dealing with its consequences, rebuilding of settlements and infrastructure and gaining an enhanced understanding of the causes of any failures. Landscape architecture must respond not only to the physical dimensions of disaster landscapes but also to the social, psychological and spiritual aspects. Landscape’s experiential potency is heightened in disasters in ways that may challenge and extend the spectrum of emotions. Identity is rooted in landscape, and massive transformation through the impact of a disaster can lead to ongoing psychological devastation. Memory and landscape are tightly intertwined as part of individual and collective identities, as connections to place and time. The ruptures caused by disasters present a challenge to remembering the lives lost and the prior condition of the landscape, the intimate attachments to places now gone and even the event itself.
Numerous rockfalls released during the 2010–2011 Canterbury earthquake sequence affected vital road sections for local commuters. We quantified rockfall fatality risk on two main routes by adapting a risk approach for roads originally developed for snow avalanche risk. We present results of the collective and individual fatality risks for traffic flow and waiting traffic. Waiting traffic scenarios particularly address the critical spatial-temporal dynamics of risk, which should be acknowledged in operational risk management. Comparing our results with other risks commonly experienced in New Zealand indicates that local rockfall risk is close to tolerability thresholds and likely exceeds acceptable risk.
We examined the stratigraphy of alluvial fans formed at the steep range front of the Southern Alps at Te Taho, on the north bank of the Whataroa River in central West Coast, South Island, New Zealand. The range front coincides with the Alpine Fault, an Australian-Pacific plate boundary fault, which produces regular earthquakes. Our study of range front fans revealed aggradation at 100- to 300-year intervals. Radiocarbon ages and soil residence times (SRTs) estimated by a quantitative profile development index allowed us to elucidate the characteristics of four episodes of aggradation since 1000 CE. We postulate a repeating mode of fan behaviour (fan response cycle [FRC]) linked to earthquake cycles via earthquake-triggered landslides. FRCs are characterised by short response time (aggradation followed by incision) and a long phase when channels are entrenched and fan surfaces are stable (persistence time). Currently, the Te Taho and Whataroa River fans are in the latter phase. The four episodes of fan building we determined from an OxCal sequence model correlate to Alpine Fault earthquakes (or other subsidiary events) and support prior landscape evolution studies indicating ≥M7.5 earthquakes as the main driver of episodic sedimentation. Our findings are consistent with other historic non-earthquake events on the West Coast but indicate faster responses than other earthquake sites in New Zealand and elsewhere where rainfall and stream gradients (the basis for stream power) are lower. Judging from the thickness of fan deposits and the short response times, we conclude that pastoral farming (current land-use) on the fans and probably across much of the Whataroa River fan would be impossible for several decades after a major earthquake. The sustainability of regional tourism and agriculture is at risk, more so because of the vulnerability of the single through road in the region (State Highway 6).
The rapid classification of building damage states or placards after an earthquake is vital for enabling an efficient emergency response and informed decision-making for rehabilitation and recovery purposes. Traditional methods rely heavily on inspector-led on-site surveys, which are often time-consuming, resource-intensive, and susceptible to human error. This study introduces a machine learning-supported surrogate model designed to streamline the assessment of building damage, focusing on the automated assignment of damage placards within the context of New Zealand's post-earthquake evaluation frameworks. The study evaluates two key safety evaluation protocols—Rapid Building Assessment (RBA) and Detailed Damage Evaluation (DDE)—and integrates corresponding databases derived from the 2010–2011 Canterbury Earthquake Sequence (CES) in Christchurch. Six ML classifiers—Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Gradient Boosting Classifier (GBC), and Gradient Bagging (GBag)—were rigorously tested across both databases. The results indicate that the RF-based surrogate model outperforms the other classifiers across both RBA and DDE protocols. Two distinct sets of critical predictors have been further identified for each protocol, allowing for the rapid retrieval of essential data for future on-site surveys, while retaining the RF model's predictive accuracy. The developed surrogate model provides a pragmatic tool for practising engineers to rapidly assign placards to damaged structures and for policymakers and building owners to make informed recovery decisions for earthquake-affected buildings.