Minimum spanning trees for valley and ridge characterization in digital elevation maps

Texture synthesis employs neighbourhood matching to generate appropriate new content. Terrain synthesis has the added constraint that new content must be geographically plausible. The profile recognition and polygon breaking algorithm (PPA) [Chang et al. 1998] provides a robust mechanism for characterizing terrain as systems of valley and ridge lines in digital elevation maps. We exploit this to create a terrain characterization metric that is robust, efficient to compute and is sensitive to terrain properties.

Terrain regions are characterized as a minimum spanning tree derived from a graph created from the sample points of the elevation map which are encoded as weights in the edges of the graph. This formulation allows us to provide a single consistent feature definition that is sensitive to the pattern of ridges and valleys in the terrain Alternative formulations of these weights provide richer characteristicmeasures and we provide examples of alternate definitions based on curvature and contour measures.

We show that the measure is robust, with a significant portion derived directly from information local to the terrain sample. Global terrain characteristics introduce the issue of over- and underconnected valley/ridge lines when working with sub-regions. This is addressed by providing two graph construction strategies, which respectively provide an upper bound on connectivity as a single spanning tree, and a lower bound as a forest of trees.

Efficient minimum spanning tree algorithms are adapted to the context of terrain data and are shown to provide substantially better performance than previous PPA implementations. In particular, these are able to characterize valley and ridge behaviour at every point even in large elevation maps, providing a measure sensitive to terrain features at all scales.

The resulting graph based formulation provides an efficient and elegant algorithm for characterizing terrain features. The measure can be calculated efficiently, is robust under changes of neighbourhood position, size and resolution and the hybrid measure is sensitive to terrain features both locally and globally.

Bayesian classification of catchments using spatial data: a first step to improved modelling of catchment effects on stream ecological condition

A major challenge facing freshwater ecologists and managers is the development of models that link stream ecological condition to catchment scale effects, such as land use. Previous attempts to make such models have followed two general approaches. The bottom-up approach employs mechanistic models, which can quickly become too complex to be useful. The top-down approach employs empirical models derived from large data sets, and has often suffered from large amounts of unexplained variation in stream condition.

We believe that the lack of success of both modelling approaches may be at least partly explained by scientists considering too wide a breadth of catchment type. Thus, we believe that by stratifying large sets of catchments into groups of similar types prior to modelling, both types of models may be improved. This paper describes preliminary work using a Bayesian classification software package, ‘Autoclass’ (Cheeseman and Stutz 1996) to create classes of catchments within the Murray Darling Basin based on physiographic data.

Autoclass uses a model-based classification method that employs finite mixture modelling and trades off model fit versus complexity, leading to a parsimonious solution. The software provides information on the posterior probability that the classification is ‘correct’ and also probabilities for alternative classifications. The importance of each attribute in defining the individual classes is calculated and presented, assisting description of the classes. Each case is ‘assigned’ to a class based on membership probability, but the probability of membership of other classes is also provided. This feature deals very well with cases that do not fit neatly into a larger class. Lastly, Autoclass requires the user to specify the measurement error of continuous variables.

Catchments were derived from the Australian digital elevation model. Physiographic data werederived from national spatial data sets. There was very little information on measurement errors for the spatial data, and so a conservative error of 5% of data range was adopted for all continuous attributes. The incorporation of uncertainty into spatial data sets remains a research challenge.

The results of the classification were very encouraging. The software found nine classes of catchments in the Murray Darling Basin. The classes grouped together geographically, and followed altitude and latitude gradients, despite the fact that these variables were not included in the classification. Descriptions of the classes reveal very different physiographic environments, ranging from dry and flat catchments (i.e. lowlands), through to wet and hilly catchments (i.e. mountainous areas). Rainfall and slope were two important discriminators between classes. These two attributes, in particular, will affect the ways in which the stream interacts with the catchment, and can thus be expected to modify the effects of land use change on ecological condition. Thus, realistic models of the effects of land use change on streams would differ between the different types of catchments, and sound management practices will differ.

A small number of catchments were assigned to their primary class with relatively low probability. These catchments lie on the boundaries of groups of catchments, with the second most likely class being an adjacent group. The locations of these ‘uncertain’ catchments show that the Bayesian classification dealt well with cases that do not fit neatly into larger classes.

Although the results are intuitive, we cannot yet assess whether the classifications described in this paper would assist the modelling of catchment scale effects on stream ecological condition. It is most likely that catchment classification and modelling will be an iterative process, where the needs of the model are used to guide classification, and the results of classifications used to suggest further refinements to models.

Assessment of habitat representation across a network of marine protected areas with implications for the spatial design of monitoring

Networks of marine protected areas (MPAs) are being adopted globally to protect ecosystems and supplement fisheries management. The state of California recently implemented a coast-wide network of MPAs, a statewide seafloor mapping program, and ecological characterizations of species and ecosystems targeted for protection by the network. The main goals of this study were to use these data to evaluate how well seafloor features, as proxies for habitats, are represented and replicated across an MPA network and how well ecological surveys representatively sampled fish habitats inside MPAs and adjacent reference sites. Seafloor data were classified into broad substrate categories (rock and sediment) and finer scale geomorphic classifications standard to marine classification schemes using surface analyses (slope, ruggedness, etc.) done on the digital elevation model derived from multibeam bathymetry data. These classifications were then used to evaluate the representation and replication of seafloor structure within the MPAs and across the ecological surveys. Both the broad substrate categories and the finer scale geomorphic features were proportionately represented for many of the classes with deviations of 1-6% and 0-7%, respectively. Within MPAs, however, representation of seafloor features differed markedly from original estimates, with differences ranging up to 28%. Seafloor structure in the biological monitoring design had mismatches between sampling in the MPAs and their corresponding reference sites and some seafloor structure classes were missed entirely. The geomorphic variables derived from multibeam bathymetry data for these analyses are known determinants of the distribution and abundance of marine species and for coastal marine biodiversity. Thus, analyses like those performed in this study can be a valuable initial method of evaluating and predicting the conservation value of MPAs across a regional network.

Accounting for uncertainty in volumes of seabed change measured with repeat multibeam sonar surveys

Seafloors of unconsolidated sediment are highly dynamic features; eroding or accumulating under the action of tides, waves and currents. Assessing which areas of the seafloor experienced change and measuring the corresponding volumes involved provide insights into these important active sedimentation processes. Computing the difference between Digital Elevation Models (DEMs) obtained from repeat Multibeam Echosounders (MBES) surveys has become a common technique to identify these areas, but the uncertainty in these datasets considerably affects the estimation of the volumes displaced. The two main techniques used to take into account uncertainty in volume estimations are the limitation of calculations to areas experiencing a change in depth beyond a chosen threshold, and the computation of volumetric confidence intervals. However, these techniques are still in their infancy and, as a result, are often crude, seldom used or poorly understood. In this article, we explored a number of possible methodological advances to address this issue, including: (1) using the uncertainty information provided by the MBES data processing algorithm CUBE, (2) adapting fluvial geomorphology techniques for volume calculations using spatially variable thresholds and (3) volumetric histograms. The nearshore seabed off Warrnambool harbour - located in the highly energetic southwest Victorian coast, Australia - was used as a test site. Four consecutive MBES surveys were carried out over a four-months period. The difference between consecutive DEMs revealed an area near the beach experiencing large sediment transfers - mostly erosion - and an area of reef experiencing increasing deposition from the advance of a nearby sediment sheet. The volumes of sediment displaced in these two areas were calculated using the techniques described above, both traditionally and using the suggested improvements. We compared the results and discussed the applicability of the new methodological improvements. We found that the spatially variable uncertainty derived from the CUBE algorithm provided the best results (i.e. smaller confidence intervals), but that similar results can be obtained using as a fixed uncertainty value derived from a reference area under a number of operational conditions.

Reconstruction of megalake Chad using shuttle radar topographic mission data

In the 2,500,000 km² Lake Chad Basin in central Africa, the 2000 Shuttle Radar Topographic Mission (SRTM) data have been used to supplement the existing topographic data. SRTM data produce much sharper images of the region's topography and provide new insights into debates about the nature and extent of late Quaternary Lake Chad. This paper shows that the accuracy of SRTM30, the recently released 30 arc seconds topographic data from SRTM, largely surpasses that of previous global Digital Elevation Models (DEMs) available in the region. Using a GIS we identified from SRTM30 elevation data key features in the landscape topography providing further evidence for the existence of a Megalake Chad. The SRTM30 data corroborate the presence of two ancient shorelines associated with stillstands of the paleolake at the elevation of the Mayo Kebbi and Bahr el Ghazal spillovers. We found a general flattening of the topography in the region covered by Megalake Chad which is most likely the result of wave-cut action. The SRTM30 data show that the remains of the highest paleoshoreline have a constant elevation of 325 ± 5 m amsl. At its maximum extent, Megalake Chad had an area of about 340 000 km² (only 8% less than the present-day world's largest lake, the Caspian Sea). The SRTM30 data also revealed ancient drainage networks in the Sahara that lead to Megalake Chad. We compiled available 14C dates to constrain Holocene Megalake Chad events. The results presented in this paper have significant consequences for improving our knowledge of regional paleohydrology and continental climate change. This study is also the first step for a GIS-based reconstruction of late Quaternary paleohydrology in tropical Africa.

Research in practice : an exercise in generative urban massing

The following paper explores practice based research as a means of identifying issues within current urban design methods. It considers the application of parametric systems as a means of addressing these issues. These systems are developed and tested across both Australian and international urban design projects within Grimshaw Architects. A methodology is proposed for the development and application of these parametric tools across multiple scales of design resolution. It reports on the application of a set of parametric urban scale massing tools in real world design projects. This exploration is carried out in distinct phases of design defined by the scale of resolution. The phasing allows for discrete problems to be addressed more effectively at different stages of the design process while still encouraging a seamless, bi directional workflow through a digital master model.

Process model to support data rich digital environments

This paper proposes a theoretical process model and the associated detailed information structure which reflects the complexity of information, stakeholder interaction and intellectual property concerns which are currently seen in the construction industry. This is being developed and tested against a field study renovation project. The field study project identifies information flows and interactions between stakeholders such as designers, project managers, clients, contractors, subcontractors and suppliers. The process model which is being established shows very high levels of complexity in dependencies and interdependencies between implicit and explicit information within the project design and construction teams. Without an understanding of these detailed and complex process interactions, proposals for the application of ICT to the construction industry will not reflect the requirements of those for whom they are being developed.

The language of design resolution in a digital building information model

Information in construction industry is delivered and interpreted in a language specific to the industry in which large complex objects are only partially described and with much information being implicit in the language used. Successful communication therefore relies on participants in the industry leaming how to interpret the language through many years of education, training and experience. With the introduction of computer technology, and in particular the detailed digital building information model (DB 1M), the accepted language currently in use is no longer a valid method of describing the building. At all stages in the paper based design and documentation process it is generally readily apparent which parts of the design require further completion and which are fully resolved. This is able to be achieved through the complex graphical language currently in use. In the DBIM, all information appears at the same level of resolution making difficult the interpretation of implicit information embedded in the model. This compromises the collaborative design environment which is being described as a fundamental characteristic of the future construction industry. This paper focuses on two areas. The first analyses design resolution and the role uncertain information plays in the design process. It then discusses the manner in which designers and the industry in general deal with incomplete or unresolved information. The second describes a theoretical model in which a design resolution (DR) environment incorporates the level of design resolution as an operable element in a collaborative DBIM. The development and implementation of this model will allow designers to better share, understand and interpret design knowledge from the shared information during the various stages of digital design and before full resolution is achieved.

Towards a universal and integrated digital representation of physical phenomena: a model to investigate comfort and energy efficiency in future environments

This thesis describes the exploration and the development of computational means to investigate the behaviour of design objects before they are available for investigation in the physical world. The motivation is to inform the design process about the design object's performance in order to achieve better--more performance-oriented--design outcomes in the sense of energy efficiency and comfort performance than can be achieved by conventional design techniques.

Digital library service quality assessment model

With the introduction of digital library services, the quality of service (QoS) has become paramount importance for evaluating the performance of the digital library service provisioning. Various models and frameworks have been proposed to evaluate digital library QoS. However, the prevalent research concentration in QoS for digital library is on the dimensions of the perspective of users’ perception. In this paper, we address the same research problem from a different dimension which is from the perspective of the digital service providers. To this end, we propose a new model suitable for evaluating the performance of digital library services. We argue that the level of QoS provided by the digital service providers have direct impact on the perception and satisfaction of the digital service end-users.

Numerical investigation of influence of the Martensite Volume Fraction on dp steels fracture behavior on the basis of digital material representation model

Development of the methodology for creating reliable digital material representation (DMR) models of dual-phase steels and investigation of influence of the martensite volume fraction on fracture behavior under tensile load are the main goals of the paper. First, an approach based on image processing algorithms for creating a DMR is described. Then, obtained digital microstructures are used as input for the numerical model of deformation, which takes into account mechanisms of ductile fracture. Ferrite and martensite material model parameters are evaluated on the basis of micropillar compression tests. Finally, the model is used to investigate the impact of the martensite volume fraction on the DP steel behavior under plastic deformation. Results of calculations are presented and discussed in the paper.

Teaching a digital performing agent: artificial neural network and hidden Markov Model for recognising and performing dance movement

For a Digital Performing Agent to be able to perform live with a human dancer, it would be useful for the agent to be able to contextualize the movement the dancer is performing and to have a suitable movement vocabulary with which to contribute to the performance. In this paper we will discuss our research into the use of Artificial Neural Networks (ANN) as a means of allowing a software agent to learn a shared vocabulary of movement from a dancer. The agent is able to use the learnt movements to form an internal representation of what the dancer is performing, allowing it to follow the dancer, generate movement sequences based on the dancer's current movement and dance independently of the dancer using a shared movement vocabulary. By combining the ANN with a Hidden Markov Model (HMM) the agent is able to recognize short full body movement phrases and respond when the dancer performs these phrases. We consider the relationship between the dancer and agent as a means of supporting the agent's learning and performance, rather than developing the agent's capability in a self-contained fashion.

Elevation in tanis expression alters glucose metabolism and insulin sensitivity in H4IIE cells

Increased hepatic glucose output and decreased glucose utilization are implicated in the development of type 2 diabetes. We previously reported that the expression of a novel gene, Tanis, was upregulated in the liver during fasting in the obese/diabetic animal model Psammomys obesus. Here, we have further studied the protein and its function. Cell fractionation indicated that Tanis was localized in the plasma membrane and microsomes but not in the nucleus, mitochondria, or soluble protein fraction. Consistent with previous gene expression data, hepatic Tanis protein levels increased more significantly in diabetic P. obesus than in nondiabetic controls after fasting. We used a recombinant adenovirus to increase Tanis expression in hepatoma H4IIE cells and investigated its role in metabolism. Tanis overexpression reduced glucose uptake, basal and insulin-stimulated glycogen synthesis, and glycogen content and attenuated the suppression of PEPCK gene expression by insulin, but it did not affect insulin-stimulated insulin receptor phosphorylation or triglyceride synthesis. These results suggest that Tanis may be involved in the regulation of glucose metabolism, and increased expression of Tanis could contribute to insulin resistance in the liver.

Spatial model for predicting the presence of cinnamon fungus (Phytophthora cinnamomi) in sclerophyll vegetation communities in south-eastern Australia

The pathogen Phytophthora cinnamomi causes extensive 'dieback' of Australian native vegetation. This study investigated the distribution of infection in an area of significant sclerophyll vegetation in Australia. It aimed to determine the relationship of infection to site variables and to develop a predictive model of infection. Site variables recorded at 50 study sites included aspect, slope, altitude, proximity to road and road characteristics, soil profile characteristics and vegetation attributes. Soil and plant tissues were assayed for the presence of the pathogen. A geographical information systyem (GIS) was employed to provide accurate estimations of spatial variables and develop a predictive model for the distribution of P. cinnamomi. The pathogen was isolated from 76% of the study sites. Of the 17 site variables initially investigated during the study a logistic regression model identified only two, elevation and sun-index, as significant in determining the probability of infection. The presence of P. cinnamomi infection was negatively associated with elevation and positively associated with sun-index. The model predicted that up to 74% of the study area (11 875 ha) had a high probability of being affected by P. cinnamomi. However, the present areas of infection were small, providing an opportunity for management to minimize spread into highly susceptible uninvaded areas.