The research is funded by Callaghan Innovation (grant number MAIN1901/PROP-69059-FELLOW-MAIN) and the Ministry of Transport New Zealand in partnership with Mainfreight Limited. Need – The freight industry is facing challenges related to climate change, including natural hazards and carbon emissions. These challenges impact the efficiency of freight networks, increase costs, and negatively affect delivery times. To address these challenges, freight logistics modelling should consider multiple variables, such as natural hazards, sustainability, and emission reduction strategies. Freight operations are complex, involving various factors that contribute to randomness, such as the volume of freight being transported, the location of customers, and truck routes. Conventional methods have limitations in simulating a large number of variables. Hence, there is a need to develop a method that can incorporate multiple variables and support freight sustainable development. Method - A minimal viable model (MVM) method was proposed to elicit tacit information from industrial clients for building a minimally sufficient simulation model at the early modelling stages. The discrete-event simulation (DES) method was applied using Arena® software to create simulation models for the Auckland and Christchurch corridor, including regional pick-up and delivery (PUD) models, Christchurch city delivery models, and linehaul models. Stochastic variables in freight operations such as consignment attributes, customer locations, and truck routes were incorporated in the simulation. The geographic information system (GIS) software ArcGIS Pro® was used to identify and analyse industrial data. The results obtained from the GIS software were applied to create DES models. Life cycle assessment (LCA) models were developed for both diesel and battery electric (BE) trucks to compare their life cycle greenhouse gas (GHG) emissions and total cost of ownership (TCO) and support GHG emissions reduction. The line-haul model also included natural hazards in several scenarios, and the simulation was used to forecast the stock level of Auckland and Christchurch depots in response to each corresponding scenario. Results – DES is a powerful technique that can be employed to simulate and evaluate freight operations that exhibit high levels of variability, such as regional pickup and delivery (PUD) and linehaul. Through DES, it becomes possible to analyse multiple factors within freight operations, including transportation modes, routes, scheduling, and processing times, thereby offering valuable insights into the performance, efficiency, and reliability of the system. In addition, GIS is a useful tool for analysing and visualizing spatial data in freight operations. This is exemplified by their ability to simulate the travelling salesman problem (TSP) and conduct cluster analysis. Consequently, the integration of GIS into DES modelling is essential for improving the accuracy and reliability of freight operations analysis. The outcomes of the simulation were utilised to evaluate the ecological impact of freight transport by performing emission calculations and generating low-carbon scenarios to identify approaches for reducing the carbon footprint. LCA models were developed based on simulation results. Results showed that battery-electric trucks (BE) produced more greenhouse gas (GHG) emissions in the cradle phase due to battery manufacturing but substantially less GHG emissions in the use phase because of New Zealand's mostly renewable energy sources. While the transition to BE could significantly reduce emissions, the financial aspect is not compelling, as the total cost of ownership (TCO) for the BE truck was about the same for ten years, despite a higher capital investment for the BE. Moreover, external incentives are necessary to justify a shift to BE trucks. By using simulation methods, the effectiveness of response plans for natural hazards can be evaluated, and the system's vulnerabilities can be identified and mitigated to minimize the risk of disruption. Simulation models can also be utilized to simulate adaptation plans to enhance the system's resilience to natural disasters. Novel contributions – The study employed a combination of DES and GIS methods to incorporate a large number of stochastic variables and driver’s decisions into freight logistics modelling. Various realistic operational scenarios were simulated, including customer clustering and PUD truck allocation. This showed that complex pickup and delivery routes with high daily variability can be represented using a model of roads and intersections. Geographic regions of high customer density, along with high daily variability could be represented by a two-tier architecture. The method could also identify delivery runs for a whole city, which has potential usefulness in market expansion to new territories. In addition, a model was developed to address carbon emissions and total cost of ownership of battery electric trucks. This showed that the transition was not straightforward because the economics were not compelling, and that policy interventions – a variety were suggested - could be necessary to encourage the transition to decarbonised freight transport. A model was developed to represent the effect of natural disasters – such as earthquake and climate change – on road travel and detour times in the line haul freight context for New Zealand. From this it was possible to predict the effects on stock levels for a variety of disruption scenarios (ferry interruption, road detours). Results indicated that some centres rather than others may face higher pressure and longer-term disturbance after the disaster subsided. Remedies including coastal shipping were modelled and shown to have the potential to limit the adverse effects. A philosophical contribution was the development of a methodology to adapt the agile method into the modelling process. This has the potential to improve the clarification of client objectives and the validity of the resulting model.
As a global phenomenon, many cities are undergoing urban renewal to accommodate rapid growth in urban population. However, urban renewal can struggle to balance social, economic, and environmental outcomes, whereby economic outcomes are often primarily considered by developers. This has important implications for urban forests, which have previously been shown to be negatively affected by development activities. Urban forests serve the purpose of providing ecosystem services and thus are beneficial to human wellbeing. Better understanding the effect of urban renewal on city trees may help improve urban forest outcomes via effective management and policy strategies, thereby maximising ecosystem service provision and human wellbeing. Though the relationship between certain aspects of development and urban forests has received consideration in previous literature, little research has focused on how the complete property redevelopment cycle affects urban forest dynamics over time. This research provides an opportunity to gain a comprehensive understanding of the effect of residential property redevelopment on urban forest dynamics, at a range of spatial scales, in Christchurch, New Zealand following a series of major earthquakes which occurred in 2010 – 2011. One consequence of the earthquakes is the redevelopment of thousands of properties over a relatively short time-frame. The research quantifies changes in canopy cover city-wide, as well as, tree removal, retention, and planting on individual residential properties. Moreover, the research identifies the underlying reasons for these dynamics, by exploring the roles of socio-economic and demographic factors, the spatial relationships between trees and other infrastructure, and finally, the attitudes of residential property owners. To quantify the effect of property redevelopment on canopy cover change in Christchurch, this research delineated tree canopy cover city-wide in 2011 and again in 2015. An object-based image analysis (OBIA) technique was applied to aerial imagery and LiDAR data acquired at both time steps, in order to estimate city-wide canopy cover for 2011 and 2015. Changes in tree canopy cover between 2011 and 2015 were then spatially quantified. Tree canopy cover change was also calculated for all meshblocks (a relatively fine-scale geographic boundary) in Christchurch. The results show a relatively small magnitude of tree canopy cover loss, city-wide, from 10.8% to 10.3% between 2011 and 2015, but a statistically significant change in mean tree canopy cover across all the meshblocks. Tree canopy cover losses were more likely to occur in meshblocks containing properties that underwent a complete redevelopment cycle, but the loss was insensitive to the density of redevelopment within meshblocks. To explore property-scale individual tree dynamics, a mixed-methods approach was used, combining questionnaire data and remote sensing analysis. A mail-based questionnaire was delivered to residential properties to collect resident and household data; 450 residential properties (321 redeveloped, 129 non- redeveloped) returned valid questionnaires and were identified as analysis subjects. Subsequently, 2,422 tree removals and 4,544 tree retentions were identified within the 450 properties; this was done by manually delineating individual tree crowns, based on aerial imagery and LiDAR data, and visually comparing the presence or absence of these trees between 2011 and 2015. The tree removal rate on redeveloped properties (44.0%) was over three times greater than on non-redeveloped properties (13.5%) and the average canopy cover loss on redeveloped properties (52.2%) was significantly greater than on non-redeveloped properties (18.8%). A classification tree (CT) analysis was used to model individual tree dynamics (i.e. tree removal, tree retention) and candidate explanatory variables (i.e. resident and household, economic, land cover, and spatial variables). The results indicate that the model including land cover, spatial, and economic variables had the best predicting ability for individual tree dynamics (accuracy = 73.4%). Relatively small trees were more likely to be removed, while trees with large crowns were more likely to be retained. Trees were most likely to be removed from redeveloped properties with capital values lower than NZ$1,060,000 if they were within 1.4 m of the boundary of a redeveloped building. Conversely, trees were most likely to be retained if they were on a property that was not redeveloped. The analysis suggested that the resident and household factors included as potential explanatory variables did not influence tree removal or retention. To conduct a further exploration of the relationship between resident attitudes and actions towards trees on redeveloped versus non-redeveloped properties, this research also asked the landowners from the 450 properties that returned mail questionnaires to indicate their attitudes towards tree management (i.e. tree removal, tree retention, and tree planting) on their properties. The results show that residents from redeveloped properties were more likely to remove and/or plant trees, while residents from non- redeveloped properties were more likely to retain existing trees. A principal component analysis (PCA) was used to explore resident attitudes towards tree management. The results of the PCA show that residents identified ecosystem disservices (e.g. leaf litter, root damage to infrastructure) as common reasons for tree removal; however, they also noted ecosystem services as important reasons for both tree planting and tree retention on their properties. Moreover, the reasons for tree removal and tree planting varied based on whether residents’ property had been redeveloped. Most tree removal occurred on redeveloped properties because trees were in conflict with redevelopment, but occurred on non- redeveloped properties because of perceived poor tree health. Residents from redeveloped properties were more likely to plant trees due to being aesthetically pleasing or to replace trees removed during redevelopment. Overall, this research adds to, and complements, the existing literature on the effects of residential property redevelopment on urban forest dynamics. The findings of this research provide empirical support for developing specific legislation or policies about urban forest management during residential property redevelopment. The results also imply that urban foresters should enhance public education on the ecosystem services provided by urban forests and thus minimise the potential for tree removal when undertaking property redevelopment.
