Land cover change information in urban areas supports decision makers in dealing with public policy planning and resource management. Remote sensing has been demonstrated as an efficient and accurate way to monitor land cover change over large extents. The Canterbury Earthquake Sequence (CES) caused massive damage in Christchurch, New Zealand and resulted in significant land cover change over a short time period. This study combined two types of remote sensing data, aerial imagery (RGB) and LiDAR, as the basis for quantifying land cover change in Christchurch between 2011 – 2015, a period corresponding to the five years immediately following the 22 February 2011 earthquake, which was part of the CES. An object based image analysis (OBIA) approach was adopted to classify the aerial imagery and LiDAR data into seven land cover types (bare land, building, grass, shadow, tree and water). The OBIA approach consisted of two steps, image segmentation and object classification. For the first step, this study used multi-level segmentation to better segment objects. For the second step, the random forest (RF) classifier was used to assign a land cover type to each object defined by the segmentation. Overall classification accuracies for 2011 and 2015 were 94.0% and 94.32%, respectively. Based on the classification result, land cover changes between 2011 and 2015 were then analysed. Significant increases were found in road and tree cover, while the land cover types that decreased were bare land, grass, roof, water. To better understand the reasons for those changes, land cover transitions were calculated. Canopy growth, seasonal differences and forest plantation establishment were the main reasons for tree cover increase. Redevelopment after the earthquake was the main reason for road area growth. By comparing the spatial distribution of these transitions, this study also identified Halswell and Wigram as the fastest developing suburbs in Christchurch. These results provided quantitative information for the effects of CES, with respect to land cover change. They allow for a better understanding for the current land cover status of Christchurch. Among those land cover changes, the significant increase in tree cover aroused particularly interest as urban forests benefit citizens via ecosystem services, including health, social, economic, and environmental benefits. Therefore, this study firstly calculated the percentages of tree cover in Christchurch’s fifteen wards in order to provide a general idea of tree cover change in the city extent. Following this, an automatic individual tree detection and crown delineation (ITCD) was undertaken to determine the feasibility of automated tree counting. The accuracies of the proposed approach ranged between 56.47% and 92.11% in thirty different sample plots, with an overall accuracy of 75.60%. Such varied accuracies were later found to be caused by the fixed tree detection window size and misclassifications from the land cover classification that affected the boundary of the CHM. Due to the large variability in accuracy, tree counting was not undertaken city-wide for both time periods. However, directions for further study for ITCD in Christchurch could be exploring ITCD approaches with variable window size or optimizing the classification approach to focus more on producing highly accurate CHMs.
The Canterbury Earthquake Sequence (CES) of 2010-2011 produced large seismic moments up to Mw 7.1. These large, near-to-surface (<15 km) ruptures triggered >6,000 rockfall boulders on the Port Hills of Christchurch, many of which impacted houses and affected the livelihoods of people within the impacted area. From these disastrous and unpredicted natural events a need arose to be able to assess the areas affected by rockfall events in the future, where it is known that a rockfall is possible from a specific source outcrop but the potential boulder runout and dynamics are not understood. The distribution of rockfall deposits is largely constrained by the physical properties and processes of the boulder and its motion such as block density, shape and size, block velocity, bounce height, impact and rebound angle, as well as the properties of the substrate. Numerical rockfall models go some way to accounting for all the complex factors in an algorithm, commonly parameterised in a user interface where site-specific effects can be calibrated. Calibration of these algorithms requires thorough field checks and often experimental practises. The purpose of this project, which began immediately following the most destructive rupture of the CES (February 22, 2011), is to collate data to characterise boulder falls, and to use this information, supplemented by a set of anthropogenic boulder fall data, to perform an in-depth calibration of the three-dimensional numerical rockfall model RAMMS::Rockfall. The thesis covers the following topics: • Use of field data to calibrate RAMMS. Boulder impact trails in the loess-colluvium soils at Rapaki Bay have been used to estimate ranges of boulder velocities and bounce heights. RAMMS results replicate field data closely; it is concluded that the model is appropriate for analysing the earthquake-triggered boulder trails at Rapaki Bay, and that it can be usefully applied to rockfall trajectory and hazard assessment at this and similar sites elsewhere. • Detailed analysis of dynamic rockfall processes, interpreted from recorded boulder rolling experiments, and compared to RAMMS simulated results at the same site. Recorded rotational and translational velocities of a particular boulder show that the boulder behaves logically and dynamically on impact with different substrate types. Simulations show that seasonal changes in soil moisture alter rockfall dynamics and runout predictions within RAMMS, and adjustments are made to the calibration to reflect this; suggesting that in hazard analysis a rockfall model should be calibrated to dry rather than wet soil conditions to anticipate the most serious outcome. • Verifying the model calibration for a separate site on the Port Hills. The results of the RAMMS simulations show the effectiveness of calibration against a real data set, as well as the effectiveness of vegetation as a rockfall barrier/retardant. The results of simulations are compared using hazard maps, where the maximum runouts match well the mapped CES fallen boulder maximum runouts. The results of the simulations in terms of frequency distribution of deposit locations on the slope are also compared with those of the CES data, using the shadow angle tool to apportion slope zones. These results also replicate real field data well. Results show that a maximum runout envelope can be mapped, as well as frequency distribution of deposited boulders for hazard (and thus risk) analysis purposes. The accuracy of the rockfall runout envelope and frequency distribution can be improved by comprehensive vegetation and substrate mapping. The topics above define the scope of the project, limiting the focus to rockfall processes on the Port Hills, and implications for model calibration for the wider scientific community. The results provide a useful rockfall analysis methodology with a defensible and replicable calibration process, that has the potential to be applied to other lithologies and substrates. Its applications include a method of analysis for the selection and positioning of rockfall countermeasure design; site safety assessment for scaling and demolition works; and risk analysis and land planning for future construction in Christchurch.
