David Pullar

Towards integrating GIS and catchment models

Abstract Modeling the impact of non-point source pollution in catchments is a complex problem, and one that has troubled natural resource managers for many years. The development of spatially distributed hydrologic models has led to improved model forecasting at the cost of requiring more detailed spatial information. In addition, the analysis is much more sensitive to errors in the data. Incorporation of catchment models into a Geographical Information System (GIS) has improved matters by streamlining data input and providing better interpretation of model outputs. This paper reviews different strategies for linking a catchment model with GIS. It examines data issues related to the performance of models and how well they match physical landscape conditions. Integration with GIS is shown to be necessary for the efficient and proper operation of models in resource management situations. The paper concludes that tighter integration between generic sub-models for physical landscape processes and GIS is still required.

An evaluation of the use of points versus polygons in public participation geographic information systems using quasi-experimental design and Monte Carlo simulation

The collection of spatial information through public participation geographic information systems (PPGIS) is most frequently implemented using either point or polygon spatial features but the research trade-offs between the two methods are not well-understood. In a quasi-experimental PPGIS design, we collected four attributes (aesthetic, recreation, economic, and biological values) as both point and polygon spatial features in the same PPGIS study. We then used Monte Carlo simulation methods to describe the relationship between the quantity of data collected and the degree of spatial convergence in the two methods for each of the four PPGIS attributes. The results demonstrate that the same PPGIS attributes identified by points and polygons will converge on a collective spatial ‘truth’ within the study area provided there are enough observations, however, the degree of spatial convergence varies by PPGIS attribute type and the quantity of data collected. The use of points for mapping PPGIS attributes and aggregating areas through density mapping constitutes a conservative approach to spatial inference about place significance, but the data demands for point collection are considerably higher than for polygon features. Based on our results, we provide heuristic guidelines for future PPGIS research when using point or polygon spatial attributes. We argue that other variables such as the cognitive complexity of the PPGIS mapping process and stronger claims of external validity favor the use of point features, but these advantages must be weighed against the significantly higher sampling effort required.

An integrated planning tool based upon multiple criteria evaluation of spatial information

Despite the widespread adoption of geographical information systems (GIS) in local government for parcel mapping and asset management, the full potential of GIS has not yet been realised. GIS is mainly used by planners for data management and querying land records. More advanced site planning has not taken advantage of the spatial analysis capability of GIS. On the basis of a user survey we identify the cause of the problem as being a disparity between the way planners solve urban design problems and the operational environment of a GIS. That is, when planners look at the tasks they need to perform to solve a problem they have difficulty relating this to operations provided by a GIS. The paper proposes a solution that involves integrating a rigorous decision-making procedure with spatial analysis and presenting this through an interface specifically designed for planners. The decision theory approach is based upon multi-criteria evaluation (MCE). Spatial analysis is used for defining design factors in MCE and again in the evaluation process to aggregate factors in the final solution. As a proof-of-concept a prototype system was developed customised to the way planners formulate and evaluate design problems. The prototype is demonstrated with a site control planning exercise within a city region.

MapScript: A Map Algebra Programming Language Incorporating Neighborhood Analysis

Map algebra is a data model and simple functional notation to study the distribution and patterns of spatial phenomena. It uses a uniform representation of space as discrete grids, which are organized into layers. This paper discusses extensions to map algebra to handle neighborhood operations with a new data type called a template. Templates provide general windowing operations on grids to enable spatial models for cellular automata, mathematical morphology, and local spatial statistics. A programming language for map algebra that incorporates templates and special processing constructs is described. The programming language is called MapScript. Example program scripts are presented to perform diverse and interesting neighborhood analysis for descriptive, model-based and processed-based analysis.

Coupling 3D visualisation to qualitative assessment of built environment designs

Geographical information systems (GIS) coupled to 3D visualisation technology is an emerging tool for urban planning and landscape design applications. The utility of 3D GIS for realistically visualising the built environment and proposed development scenarios is much advocated in the literature. Planners assess the merits of proposed changes using visual impact assessment (VIA). We have used Arcview GIS and visualisation software called PolyTRIM from the University of Toronto, Centre for Landscape Research (CLR) to create a 3D scene for the entrance to a University campus. The paper investigates the thesis that to facilitate VIA in planning and design requires not only visualisation, but also a structured evaluation technique (Delphi) to arbitrate the decision-making process.

A Way Forward for Land-Use Planning to Achieve Policy Goals by Using Spatial Modelling Scenarios

This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A (‘continued growth’) is based on existing socioeconomic trends. Scenario B (‘maximising rates base’) is derived using optimisation modelling of land-valuation data. Scenario C (‘sustainable development’) is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.

Mapping forest patches and scattered trees from SPOT images and testing their ecological importance for woodland birds in a fragmented agricultural landscape

Scattered trees represent an important element within the agricultural matrix for birds. The aims of this study were to develop methods for mapping isolated trees from satellite imagery and to assess the importance of isolated trees for bird species richness. Field sampling of birds and plants was conducted at 120 sites in south-east Australia. We mapped tree cover from Landsat and SPOT images using a combination of spectral and segmentation based methods. Mapping of isolated trees as point objects was highly accurate (80–90%). Tree cover at spatial extents of 3–28 ha around sites explained 60% of the variability in woodland–dependent bird species richness. However, isolated trees in agricultural areas made just a small contribution to explaining the spatial variability in overall avian richness. This approach can be used for more extensive assessment of avian habitat quality from high spatial resolution images across a range of human modified landscapes.

A comparison of spatial disaggregation techniques as applied to population estimation for south east Queensland (SEQ), Australia

The accuracy of spatial disaggregation techniques largely depends on their underlying density assumptions and the quality of the data applied. This paper presents the results of a comparative investigation of four spatial disaggregation methodologies to determine their relative accuracies. These methodologies include binary dasymetric, a regression model, a locally fitted regression model and three-class dasymetric, each of which provides different solutions for explaining spatially heterogeneous density when population data is spatially disaggregated. In contrast to previous studies, we apply the spatial disaggregation techniques to a comparably larger and more varied geographical area which allows the spatial disaggregation techniques to be more rigorously tested. Results indicate that the three-class dasymetric technique generates higher levels of accuracy compared to the other spatial disaggregation techniques and this result is more conclusive than previous findings.

Simulation Modelling Applied to Runoff Modelling Using MapScript

Dynamic spatial analysis addresses computational aspects of space–time processing. This paper describes the development of a spatial analysis tool and modelling framework that together offer a solution for simulating landscape processes. A better approach to integrating landscape spatial analysis with Geographical Information Systems is advocated in this paper. Enhancements include special spatial operators and map algebra language constructs to handle dispersal and advective flows over landscape surfaces. These functional components to landscape modelling are developed in a modular way and are linked together in a modelling framework that performs dynamic simulation. The concepts and modelling framework are demonstrated using a hydrological modelling example. The approach provides a modelling environment for scientists and land resource managers to write and to visualize spatial process models with ease.

Describing dynamic modeling for landscapes with vector map algebra in GIS

A large class of applications that model physical processes use vector fields. This includes landscape processes that are naturally expressed using mathematics for two-dimensional vector fields. Geographical information systems (GIS) are a ubiquitous technology used not only for managing, analyzing and visualizing spatial data for landscapes, but also has the capability to perform landscape analysis and to compose models to address a wide range of problems. This paper proposes ways to extend data models in GIS to allow it to address an even wider range of problems that require the use of vector field representations and analysis operations. The paper describes a vector field data model, which relates well to the field data model commonly implemented in GIS using a raster data type, and demonstrates its application for landscape characterization and hydrological modeling in GIS. The main contribution of this paper is the definition of operations that are consistent with the theory for vector fields and may be implemented to manipulate rasters and multi-component rasters in GIS. The implementation describes a computational environment that supports writing models using primitive operations that are part of a vector map algebra (VMA) and for modeling dynamic changes to mapped landscapes over time.