Multicriteria generalization (MCG): a decision-making framework for formalizing multiscale environmental data reduction

Environmental simulation models need automated geographic data reduction methods to optimize the use of high-resolution data in complex environmental models. Advanced map generalization methods have been developed for multiscale geographic data representation. In the case of map generalization, positional, geometric and topological constraints are focused on to improve map legibility and communication of geographic semantics. In the context of environmental modelling, in addition to the spatial criteria, domain criteria and constraints also need to be considered. Currently, due to the absence of domain-specific generalization methods, modellers resort to ad hoc methods of manual digitization or use cartographic methods available in off-the-shelf software. Such manual methods are not feasible solutions when large data sets are to be processed, thus limiting modellers to the single-scale representations. Automated map generalization methods can rarely be used with confidence because simplified data sets may violate domain semantics and may also result in suboptimal model performance. For best modelling results, it is necessary to prioritize domain criteria and constraints during data generalization. Modellers should also be able to automate the generalization techniques and explore the trade-off between model efficiency and model simulation quality for alternative versions of input geographic data at different geographic scales. Based on our long-term research with experts in the analytic element method of groundwater modelling, we developed the multicriteria generalization (MCG) framework as a constraint-based approach to automated geographic data reduction. The MCG framework is based on the spatial multicriteria decision-making paradigm since multiscale data modelling is too complex to be fully automated and should be driven by modellers at each stage. Apart from a detailed discussion of the theoretical aspects of the MCG framework, we discuss two groundwater data modelling experiments that demonstrate how MCG is not just a framework for automated data reduction, but an approach for systematically exploring model performance at multiple geographic scales. Experimental results clearly indicate the benefits of MCG-based data reduction and encourage us to continue expanding the scope of and implement MCG for multiple application domains.     

Handling Geographic Information. Report of the Committee of Enquiry Chaired by Lord Chorley,Department of the Environment. (London: HMSO, 1987.) [Pp. 208. ] Price £l14-95. ISBN Oil 752015 2.

ABSTRACT

A wide range of environmental process simulations would benefit from the development of GIS able to cope with the additional dimensions of vertical space and time, and having extended spatial modelling facilities. The results of a project in the first of these areas, namely on the development of techniques for handling four-dimensional (4-D) data, are described. The key topics of data models, visualization and interpolation have been studied. Problems include the large size of some 4-D data sets, the sparseness of sampling in some dimensions compared with others, and the need to combine data sets from different sensors which may be of different dimensionalities and scales. The gridded volume data common to most environmental models are stored in a 4-D bintree form in which all dimensions are treated identically. Simple 4-D objects may also be stored, and links are provided between volume and object databases. The techniques have been implemented within a computational testbed allowing parallel processing to cope with large data sizes.     

An iconic query language for topological relationships in GIS

Abstract

The study of query languages for spatial databases is an active research area. This paper describes a new spatial query language that uses a visual grammar to express topological relationships. It is supplemented by text and icons to handle other spatial and non-spatial queries. A graphical user interface is also developed to provide an interactive environment for composing the iconic query command. To test the language, the interface is implemented on a SUN 4 Workstation and linked to Ingres, a relational DBMS. Preliminary tests show that the iconic query language is more convenient for expressing spatial concepts than conventional textual languages. This is due mainly to the two-dimensionality of iconic languages in contrast with the linear nature of conventional languages.     

Multi-label class assignment in land-use modelling

During the last two decades, a variety of models have been applied to understand and predict changes in land use. These models assign a single-attribute label to each spatial unit at any particular time of the simulation. This is not realistic because mixed use of land is quite common. A more detailed classification allowing the modelling of mixed land use would be desirable for better understanding and interpreting the evolution of the use of land. A possible solution is the multi-label (ML) concept where each spatial unit can belong to multiple classes simultaneously. For example, a cluster of summer houses at a lake in a forested area should be classified as water, forest and residential (built-up). The ML concept was introduced recently, and it belongs to the machine learning field. In this article, the ML concept is introduced and applied in land-use modelling. As a novelty, we present a land-use change model that allows ML class assignment using the k nearest neighbour (kNN) method that derives a functional relationship between land use and a set of explanatory variables. A case study with a rich data-set from Luxembourg using biophysical data from aerial photography is described. The model achieves promising results based on the well-known ML evaluation criteria. The application described in this article highlights the value of the multi-label k nearest neighbour method (MLkNN) for land-use modelling.     

Mapping the stray domestic cat (Felis catus) population in New Zealand: Species distribution modelling with a climate change scenario and implications for protected areas

Species distribution models of stray cats were developed using two types of occurrence data: (i) a combined dataset of stray cats and cat colonies in Auckland and projected to the wider New Zealand area; and (ii) population density as an analogue for country-wide stray cat occurrence. These occurrence data, together with sets of environmental variables were used as input to the Maxent modelling tool to produce maps of suitability for the species. Environmental variables used in the models consist of current bioclimatic conditions, and a future climate scenario (RCP8.5 for year 2070 CCSM model). Commonly occurring bias in the modelling process due to latitude, the area for selecting background points in model evaluation, inherent spatial autocorrelation of occurrence points, and correlated bioclimatic variables were explicitly addressed. Results show that the North Island consistently provide more suitable areas for stray cats with increased suitability in a high emission climate change condition. Key protected areas at risk from the increased suitability to stray cats are also presented.     

Simple spatially-distributed models for predicting flood inundation: A review

In this paper we review recent progress in the use of reduced complexity models for predicting floodplain inundation. We review the theoretical basis for modelling floodplain flow with simplified hydraulic treatments based on a dimensional analysis of the one-dimensional shallow water equations. We then review how such schemes can be applied in practice and consider issues of space discretization, time discretization and model parameterisation, before going on to consider model assessment procedures. We show that a key advantage of reduced complexity codes is that they force modellers to think about the minimum process representation necessary to predict particular quantities and act as a check on any tendency to reductionism. At the same time, however, the use (compared to standard hydraulic codes) of strong simplifying assumptions requires us to also address the question “how simple can a model be and still be physically realistic?” We show that by making explicit this debate about acceptable levels of abstraction, reduced complexity codes allow progress to be made in addressing a number of long-standing debates in hydraulics.     

GIS-based modelling of topography-induced solar radiation variability in complex terrain for data sparse region

Solar radiation not only sustains the lives on the Earth, but also creates spatial and temporal variations of hydrological ingredients, such as vegetation, soil moisture, and snow. Precise quantification of spatial solar radiation incident on the Earth's surface which accounts for the topographic modulation, especially in complex terrain, underpins the study of many catchment hydro-meteorological and hydro-ecological processes. Topography is a key parameter that affects the spatial solar radiation pattern across different scales. This article addresses the issue of modelling spatial variability of actual solar radiation caused by topography from the hydrological perspective. Models with different algorithms and different complexities, from the simple empirical equations to process-based physical approach, have been developed to parameterize and calculate the potential radiation (under clear-sky condition) and the actual radiation (under overcast cloudy condition). Based on a review of the general steps of solar radiation modelling and the corresponding models for each step, two models with easily or globally available data for spatial solar radiation modelling in complex terrain, namely, the physically parameterized, remote-sensing-oriented Heliosat-2 model and the sunshine duration-based Angström–Prescott regression model are selected and implemented in a GIS framework. The capability of both models for simulation of cloudy-sky radiation on horizontal surfaces has been verified against observed station data showing an R ² greater than 0.9. The validity of the models for modelling inclined surface is tested by comparing against each other, which has shown a satisfactory agreement and demonstrated that the simple Angström–Prescott method performed reasonably well compared with the more elaborate Heliosat-2 method. Scale sensitivity of the models and the shading effect are examined with different digital elevation model (DEM) resolutions from 30 to 500 m and reveal the existence of a threshold grid size to resolve the topography-induced spatial solar radiation variability. Spatial mapping of potential solar radiation and actual solar radiation has been demonstrated in a small catchment in Southern Germany, with a spatial difference up to 30% in winter and 5% in summer. This may lead to a significant difference for the energy-limited hydrological processes, such as snowmelt, and evapotranspiration.     

A dimension-independent extrusion algorithm using generalised maps

One solution to the integration of additional characteristics, for example, time and scale, into GIS data sets is to model them as extra geometric dimensions perpendicular to the spatial ones, creating a higher-dimensional model. While this approach has been previously described and advocated, it is scarcely used in practice because of a lack of high-level construction algorithms and accompanying implementations. We present in this paper a dimension-independent extrusion algorithm permitting us to construct from any (n–1)-dimensional linear cell complex represented as a generalised map, an n-dimensional one by assigning to each (n–1)-cell one or more intervals where it exists along the nth dimension. We have implemented the algorithm in C++11 using CGAL, made the source code publicly available and tested it in experiments using real-world 2D GIS data sets which were extruded to construct up to 5D models.     

Why not SQL!

Abstract

The application of traditional database query languages, primarily the Structured Query Language SQL, for geographical information systems (GIS) and other non–standard database applications has been tried unsuccessfully; therefore, several extensions to the relational database query language SQL have been proposed to serve as a spatial query language. It is argued that the SQL framework is inappropriate for an interactive query language for a GIS and an extended SQL is at best a short term solution. Any spatial SQL dialect has a number of serious deficiencies, particularly the patches to incorporate the necessary spatial concepts into SQL.     

Simulating artificial cities in a GIS environment: urban growth under alternative regulation regimes

This paper reports on an attempt to combine neo-classical urban economic theory with complex systems methods. The innovative feature of our model from the point of view of conventional economic theory lies in its explicit treatment of spatial relationships and time sequence. From the perspective of raster or cellular GIS models of urban processes, the work is innovative in that it replaces the more usual heuristic cell-transition rules with micro-economic theory. The mix of modelling paradigms is not unproblematic, however, and we discuss the challenges encountered at this research frontier. These notwithstanding, our hybrid model has the potential to be used as a GIS-based laboratory for exploring micro-economic propositions, particularly those relating to urban processes that are path dependent. The version of the model reported simulates spatially equilibriated path dependent futures of a city governed by local development decisions that are at partial equilibria in the neo-classical sense. Two simulations are described which permit visual and economic exploration of (a) an explicitly spatial version of the economic theory of externalities and (b) a new theory of densification. The dual paradigm (Cellular Automata-neo-classical economics) leads to an interesting class of simulations in terms of stability. Economically our simulated cities become increasingly efficient, in terms of private and social product. The long-run economic equilibrium is achieved by many individually efficient negotiations based only on local information. There is no parallel long-run spatial equilibrium however. The spatial configuration of land uses is constantly shifting as a result of randomness in the land use bidding process. The spatial instability is, however, limited by the self-organised drive for greater overall economic efficiency. In economic terms, the model's spatial instability represents random re-allocation of land-use within a set of Pareto-efficient spatial configurations - an intriguing result that we intend to follow up in future work.     

Reduced complexity strategies for modelling urban floodplain inundation

Significant advances in flood inundation modelling have been made in the last decade through the use of a new generation of 2D hydraulic numerical models. These offer the potential to predict the local pattern and timing of flood depth and velocity, enabling informed flood risk zoning and improved emergency planning. With the availability of high resolution DEMs derived from airborne lidar, these models can theoretically now be routinely parameterized to represent considerable topographic complexity, even in urban areas where the potential exists to represent flows at the scale of individual buildings. Currently, however, computational constraints on conventional finite element and volume codes typically require model discretization at scales well below those achievable with lidar and are thus unable to make optimal use of this emerging data stream.In this paper we review two strategies that attempt to address this mismatch between model and data resolution in an effort to improve urban flood forecasts. The first of these strives for a solution by simplifying the mathematical formulation of the numerical model by using a computationally efficient 2D raster storage cell approach coupled to a 1D channel model. This parsimonious model structure enables simulations over large model domains offering the opportunity to employ a topographic discretization strategy which explicitly represents the built environment. The second approach seeks to further reduce the computational overhead of this raster method by employing a subgrid parameterization to represent the effect of buildings and micro-relief on flow pathways and floodplain storage. This multi-scale methodology enables highly efficient model applications at coarse spatial resolutions while retaining information about the complex geometry of the built environment.These two strategies are evaluated through numerical experiments designed to reconstruct a flood in the small town of Linton in southern England, which occurred in response to a 1 in 250 year rainfall event in October 2001. Results from both approaches are encouraging, with the spatial pattern of inundation and flood wave propagation matching observations well. Both show significant advantages over a coarse resolution model without subgrid parameterisation, particularly in terms of their ability to reproduce both hydrograph and inundation depth measurements simultaneously, without need for recalibration. The subgrid parameterization is shown to achieve this without contributing significant computational complexity and reduces model run-times by an order of magnitude.     

A critical evaluation of 3D spatial information models for managing legal arrangements of multi-owned developments in Victoria,Australia

Three-dimensional (3D) spatial information models are increasingly being adopted to help communicate the spatial dimensions of complex built environments. Land administration practices in multi-owned developments include the subdivision, registration and management of legal interests associated with private, communal and public properties, which are often located along the vertical dimension. The spatial structure of each legal interest is normally composed of invisible spaces, defined as the inside and outside of multi-owned developments, as well as physically built structures. Additionally, a wide variety of legal boundary types mark out the spatial limits of the individual parts of each legal interest. These legal boundaries are typically delineated by either relying on fixed surveying measurements or referencing physically existent objects. This article provides a critical assessment of 3D spatial information models in terms of their capabilities for modelling legal interests and legal boundaries defined in the Victorian jurisdiction. We classify these models into three categories: purely legal, purely physical and integrated. This assessment provides the basis for developing a new 3D spatial information model, which would subsequently support a pathway towards realising the Victorian land administration system in a 3D digital environment.     

Using geolifespans to model dynamic geographic domains

Geographic objects are characterized by having different durations of existence, or geolifespans. A typology based on the concept of a geolifespan is developed to model variations in the longevity of entities that are stored in geographic information systems. The typology consists of two upper-level classes: Persistent and Ephemeral. The Ephemeral class is composed of three subclasses: Temporary, Transient and Brief. The set of possible transitions between classes in the typology is described, capturing how objects can change from one class to another, e.g., from Temporary to Brief or from Transient to Persistent. A transition sequence models the geolifespan class(es) to which an object belongs over a period of time and captures the evolution of dynamic geographic objects with respect to their longevity. Geolifespan classes are applied to scenarios of spatial change as well as a geosensor network to illustrate their role in modelling geographic dynamics.     

Collaborative landscape research in Reunion Island: Using spatial modelling and simulation to support territorial foresight and urban planning

This paper reflects on collaborative landscape research conducted in Reunion Island, an outermost region of the European Union. On this 2,500 km² tropical island also considered a major international biodiversity hotspot, land-use planners must address important challenges, especially growing population densities and urban sprawl that cause important pressure on agricultural land and natural ecosystems. While progress has been made towards land-use zoning and planning at the island scale, entrenched interests and a lack of communication between the agricultural, urban and environmental sectors continue to hinder the design and implementation of integrated land-use plans at the local level. This paper presents an approach to territorial foresight where urban development scenarios and spatial models were co-constructed with a collective of institutional actors in order to facilitate dialogue on future urbanization patterns and impacts on landscapes. It describes how spatially explicit models and simulations of urban development, first used as demonstrators, have raised individual interests and expectations and facilitated the structuring of a collaborative research network. Models and scenarios were then questioned, redesigned collectively and used as boundary objects to facilitate a shift away from statistical and sectorial readings towards more territorialized and integrated perspectives. Analysing inputs, reactions and feedback from the actors involved in the research, this paper discusses the role and potential value of landscape modelling and simulation in mediating debates among planning stakeholders and creating social learning situations.     

A partitioned and asynchronous cellular automata model for urban growth simulation

Cellular automata (CA) models are used to analyze and simulate the global phenomenon of urban growth. However, these models are characterized by ignoring spatially heterogeneous transition rules and asynchronous evolving rates, which make it difficult to improve urban growth simulations. In this paper, a partitioned and asynchronous cellular automata (PACA) model was developed by implementing the spatial heterogeneity of both transition rules and evolving rates in urban growth simulations. After dividing the study area into several subregions by k-means and knn-cluster algorithms, a C5.0 decision tree algorithm was employed to identify the transition rules in each subregion. The evolving rates for cells in each regularly divided grid were calculated by the rate of changed cells. The proposed PACA model was implemented to simulate urban growth in Wuhan, a large city in central China. The results showed that PACA performed better than traditional CA models in both a cell-to-cell accuracy assessment and a shape dimension accuracy assessment. Figure of merit of PACA is 0.368 in this research, which is significantly higher than that of partitioned CA (0.327) and traditional CA (0.247). As for the shape dimension accuracy, PACA has a fractal dimension of 1.542, which is the closest to that of the actual land use (1.535). However, fractal dimension of traditional CA (1.548) is closer to that of the actual land use than that of partitioned CA (1.285). It indicates that partitioned transition rules play an important role in the cell-to-cell accuracy of CA models, whereas the combination of partitioned transition rules and asynchronous evolving rates results in improved cell-to-cell accuracy and shape dimension accuracy. Thus, implementing partitioned transition rules and asynchronous evolving rates yields better CA model performance in urban growth simulations due to its accordance with actual urban growth processes.     

Modelling patterned ground distribution in Finnish Lapland: an integration of topographical, ground and remote sensing information

New data technologies and modelling methods have gained more attention in the field of periglacial geomorphology during the last decade. In this paper we present a new modelling approach that integrates topographical, ground and remote sensing information in predictive geomorphological mapping using generalized additive modelling (GAM) . First, we explored the roles of different environmental variable groups in determining the occurrence of non‐sorted and sorted patterned ground in a fell region of 100 km2 at the resolution of 1 ha in northern Finland. Second, we compared the predictive accuracy of ground‐topography‐ and remote‐sensing‐based models. The results indicate that non‐sorted patterned ground is more common at lower altitudes where the ground moisture and vegetation abundance is relatively high, whereas sorted patterned ground is dominant at higher altitudes with relatively high slope angle and sparse vegetation cover. All modelling results were from good to excellent in model evaluation data using the area under the curve (AUC) values, derived from receiver operating characteristic (ROC) plots. Generally, models built with remotely sensed data were better than ground‐topography‐based models and combination of all environmental variables improved the predictive ability of the models. This paper confirms the potential utility of remote sensing information for modelling patterned ground distribution in subarctic landscapes.     

A population based assessment of the geographical accessibility of outdoor recreation opportunities in New Zealand

Active participation in the outdoors not only provides enjoyment and adventure, but it is also important for health and promoting conservation values. The latter is particularly important for young people as they are at an impressionable stage in their lives. Geographical accessibly of recreation opportunities can be a major barrier to utlization of the New Zealand outdoors. While it would be ideal to have a variety of opportunities available to everyone regardless of residence, the distribution of opportunities is constrained by the extent of suitable lands. This research provides a population based assessment of the geographical accessibility of recreational opportunities. Accessibility has many dimensions and includes cultural, financial, and geographical barriers; therefore this research is only addressing one dimension of accessibility. Geographical Information Systems is used for the analysis, which involves a function called least-cost path analysis. This identified the travel time (using a private vehicle) via the quickest route from where people live (represented by census enumeration points) to the entry point of the recreation sites. The outputs of this research are maps and spatial statistics on the travel times to a range of recreation opportunities for different parts of New Zealand. This information is important for recreation planning. In addition, the information also provides research opportunities for modelling recreation use, especially when accessibility information is combined with landscape experience information and recreation usage statistics.     

Cellular modelling of river catchments and reaches: Advantages, limitations and prospects

The last decade has witnessed the development of a series of cellular models that simulate the processes operating within river channels and drive their geomorphic evolution. Their proliferation can be partly attributed to the relative simplicity of cellular models and their ability to address some of the shortcomings of other numerical models. By using relaxed interpretations of the equations determining fluid flow, cellular models allow rapid solutions of water depths and velocities. These can then be used to drive (usually) conventional sediment transport relations to determine erosion and deposition and alter the channel form. The key advance of using these physically based yet simplified approaches is that they allow us to apply models to a range of spatial scales (1–100 km²) and time periods (1–100 years) that are especially relevant to contemporary management and fluvial studies.However, these approaches are not without their limitations and technical problems. This paper reviews the findings of nearly 10 years of research into modelling fluvial systems with cellular techniques, principally focusing on improvements in routing water and how fluvial erosion and deposition (including lateral erosion) are represented. These ideas are illustrated using sample simulations of the River Teifi, Wales. A detailed case study is then presented, demonstrating how cellular models can explore the interactions between vegetation and the morphological dynamics of the braided Waitaki River, New Zealand. Finally, difficulties associated with model validation and the problems, prospects and future issues important to the further development and application of these cellular fluvial models are outlined.