Feasibility of geographic information systems approach for natural resource management

Geographic information systems (GIS) technology is altering the work environment for planning and decision-making tasks. This article is an account of a resource application that make use of the GIS technology. It provides some cost estimates and reasons for the fairly slow development toward an integrated resource data base for environmental planning and management. It tries to identify some of the constraints of such an integrated data-base approach toward environmental assessment.     

A landscape ecological approach to countryside planning

Extensive losses of semi‐natural rural biotopes have led to pressures for conservation and habitat creation. Of particular concern is the loss of large‐scale structure and regional distinctiveness. If this is to be regained, planners will require both an effective body of theory relating to large‐scale visual and ecological cohesion, and effective methods of implementation. This study reviews the value of landscape ecology as a theoretical framework and discusses some applications, with particular reference to the re‐forestation of lowland Britain.     

Remote sensing for land management and planning

The primary role of remote sensing in land management and planning has been to provide information concerning the physical characteristics of the land which influence the management of individual land parcels or the allocation of lands to various uses These physical characteristics have typically been assessed through aerial photography, which is used to develop resource maps and to monitor changing environmental conditions These uses are well developed and currently well integrated into the planning infrastructure at local, state, and federal levels in the United States.Many newly emerging uses of remote sensing involve digital images which are collected, stored, and processed automatically by electromechanical scanning devices and electronic computers Some scanning devices operate from aircraft or spacecraft to scan ground scenes directly; others scan conventional aerial transparencies to yield digital images. Digital imagery offers the potential for computer-based automated map production, a process that can significantly increase the amount and timeliness of information available to land managers and planners.Future uses of remote sensing in land planning and management will involve geographic information systems, which store resource information in a geocoded format. Geographic information systems allow the automated integration of disparate types of resource data through various types of spatial models so that with accompanying sample ground data, information in the form of thematic maps and/ or aerially aggregated statistics can be produced Key issues confronting the development and integration of geographic information systems into planning pathways are restoration and rectification of digital images, automated techniques for combining both quantitative and qualitative types of data in information-extracting procedures, and the compatibility of alternative data storage modes     

Use of a geographic information system for storm runoff prediction from small urban watersheds

The use of computer-assisted map analysis techniques for prediction of storm runoff from a small urban watershed in the United States is investigated. An automated procedure for calculating input parameters for the US Soil Conservation Service (SCS) method of predicting storm runoff volume and peak timing is presented. Advanced techniques of spatial analysis are used to characterize spatial coincidence, surface configuration and effective hydrologic distance. A limited verification of the automated procedure indicates that the model reasonably characterizes water flow. A sensitivity analysis of basin disaggregation suggests that the SCS method yields increased volume and peak discharge predictions as the watershed is divided into smaller and smaller subunits. As a means to demonstrate the practical application of the automated procedure, a simulation of the effects on surface runoff for a potential residential development is presented.     

Geographic information systems and environmental impact assessment

The analytical structure of environmental impact assessment is continually changing as the applicability of established techniques from other fields and the development of novel methods become known. This paper illustrates the applicability of using existing data bases, through a geographic information system, for theex ante evaluation of land use disruption. More specifically, the Canada Geographic Information System was employed to retrieve, to analyze, and to produce land capability statistics and land use maps for the proposed Glengowan dam and reservoir.     

A Conceptual Model for Defining and Assessing Land Management Units Using a Fuzzy Modeling Approach in GIS Environment

Appropriate land management decisions are important for current and future use of the land to ensure its sustainability. This requires that land management units (LMUs) be specified to enable the identification of specific parameters employed in decision making processes. This paper presents the development of a conceptual model, within geographic information systems (GIS), for defining and assessing LMUs from available biophysical information. The model consists of two main components (sub-models): land quality-based suitability analysis and soil erosion estimation. Using a fuzzy set methodology, the first sub-model was constructed to derive a land suitability index (LSI) for a cropping land utilization type. The LSI thus highlights the suitability grades of every pixel in the study area on a continuous basis. A sub-model of soil erosion was established based on the Revised Universal Soil Loss Equation (RUSLE) utilising the same spatial data bases employed for structuring the LSI. Using a soil loss tolerance principle, a fuzzy membership function of average annual soil loss (called soil loss index, SLI) was established, leading to compatibility between LSI and SLI for data integration. LMUs were then derived from various combinations of LSI and SLI. The methodology developed shows the significance of the model for refining available land suitability evaluation systems, which take no account of expected land degradation (from erosion) due to a nominated land use. It also provides a valuable guideline for cost-effective GIS applications in the identification and assessment of homogeneous land units, using available spatial information sets, at a finer scale.     

A new method for predicting vegetation distributions using decision tree analysis in a geographic information system

Decision tree analysis was used to predict the distribution of forest communities in an area on the south coast of New South Wales, Australia. The analysis was carried out using a geographical information system environmental data base of those topographic and geological variables thought to influence the distribution of vegetation and derived from cartographic sources. The resulting maps of forest communities are of a resolution sufficient to delimit individual forest stands and contain much ecological information.     

Systematic regional planning for multiple objective natural resource management

On-ground natural resource management actions such as revegetation and remnant vegetation management can simultaneously affect multiple objectives including land, water and biodiversity resources. Hence, planning for the sustainable management of natural resources requires consideration of these multiple objectives. However, planning the location of management actions in the landscape often treats these objectives individually to reduce the process and spatial complexity inherent in human-modified and natural landscapes. This can be inefficient and potentially counterproductive given the linkages and trade-offs involved. We develop and apply a systematic regional planning approach to identify geographic priorities for on-ground natural resource management actions that most cost-effectively meet multiple natural resource management objectives. Our systematic regional planning approach utilises integer programming within a structured multi-criteria decision analysis framework. Intelligent siting can capitalise on the multiple benefits of on-ground actions and achieve natural resource management objectives more efficiently. The focus of this study is the human-modified landscape of the River Murray, South Australia. However, the methodology and analyses presented here can be adapted to other regions requiring more efficient and integrated planning for the management of natural resources.     

Geographic information systems within the national health service: the scope for implementation

The paper starts by assessing some of the needs for information management within the health service in Great Britain. Geographic Information Systems are introduced, and some of the functions such as database management, networking and overlying are described. Principally, it is argued that GIS can fill the role as a health information system, resource management system, and has the potential to assist in family practitioner monitoring and epidemiological studies.     

Regression modeling of streamflow, baseflow, and runoff using geographic information systems

Regression models for predicting total streamflow (TSF), baseflow (TBF), and storm runoff (TRO) are needed for water resource planning and management. This study used 54 streams with >20 years of streamflow gaging station records during the period October 1971 to September 2001 in Pennsylvania and partitioned TSF into TBF and TRO. TBF was considered a surrogate of groundwater recharge for basins. Regression models for predicting basin-wide TSF, TBF, and TRO were developed under three scenarios that varied in regression variables used for model development. Regression variables representing basin geomorphological, geological, soil, and climatic characteristics were estimated using geographic information systems. All regression models for TSF, TBF, and TRO had R(2) values >0.94 and reasonable prediction errors. The two best TSF models developed under scenarios 1 and 2 had similar absolute prediction errors. The same was true for the two best TBF models. Therefore, any one of the two best TSF and TBF models could be used for respective flow prediction depending on variable availability. The TRO model developed under scenario 1 had smaller absolute prediction errors than that developed under scenario 2. Simplified Area-alone models developed under scenario 3 might be used when variables for using best models are not available, but had lower R(2) values and higher or more variable prediction errors than the best models.     

Identifying Potential Conflict Associated with Oil and Gas Exploration in Texas State Coastal Waters: A Multicriteria Spatial Analysis

Recent interest in expanding offshore oil production within waters of the United States has been met with opposition by groups concerned with recreational, environmental, and aesthetic values associated with the coastal zone. Although the proposition of new oil platforms off the coast has generated conflict over how coastal resources should be utilized, little research has been conducted on where these user conflicts might be most intense and which sites might be most suitable for locating oil production facilities in light of the multiple, and often times, competing interests. In this article, we develop a multiple-criteria spatial decision support tool that identifies the potential degree of conflict associated with oil and gas production activities for existing lease tracts in the coastal margin of Texas. We use geographic information systems to measure and map a range of potentially competing representative values impacted by establishing energy extraction infrastructure and then spatially identify which leased tracts are the least contentious sites for oil and gas production in Texas state waters. Visual and statistical results indicate that oil and gas lease blocks within the study area vary in their potential to generate conflict among multiple stakeholders.     

Two-stage vertex analysis method for planning electric power systems with greenhouse gas abatement consideration

This study presents a two-stage vertex analysis (TSVA) method for the planning of electric power systems (EPS) under uncertainty. TSVA has advantages in comparison to other optimization techniques. Firstly, TSVA can incorporate greenhouse gas (GHG) abatement policies directly into its optimization process, and, secondly, it can readily integrate inherent system uncertainties expressed as fuzzy sets and probability distributions directly into its modeling formulation and solution procedure. The TSVA method is applied to a case study of planning EPS and it is demonstrated how the TSVA efficiently identify optimal electricity-generation schemes that could help to minimize system cost under different GHG-abatement considerations. Different combinative considerations on the uncertain inputs lead to varied system costs and GHG emissions. Results reveal that the total electricity supply will rise up along with the time period due to the increasing demand and, at the same time, more non-fossil fuels should be used to satisfy the increasing requirement for GHG mitigation. Moreover, uncertainties in connection with complexities in terms of information quality (e.g., capacity, efficiency, and demand) result in changed electricity-generation patterns, GHG-abatement amounts, as well as system costs. Minimax regret (MMR) analysis technique is employed to identify desired alternative that reflects compromises between system cost and system-failure risk.     

Integrating social preference in GIS-aided planning for forestry and conservation activities: a case study from rural SE Asia

Land-use planning using geographic information systems (GIS) commonly emphasizes biophysical spatial data; however planning can be improved by integrating spatial sets of socioeconomic data into the GIS. As an example, we compared a traditional GIS-aided forestry planning protocol that considered only biophysical suitability, with an integrated GIS-aided approach that incorporated both biophysical and socioeconomic suitability. The analyses were conducted for the planning of plantation investments in the Kyaukpadaung Township in the dry zone of central Myanmar. The traditional approach used three biophysical layers for suitability: land use, slope, and accessibility. In contrast, the integrated GIS approach included biophysical suitability data, perceptions and preferences of local villagers towards forestry (social suitability), and quantitative socioeconomic data. The results indicated that the integrated approach provided two principal benefits over the traditional method. First, the integrated method resulted in a more precise idea of suitable sites for plantation investment that could benefit more rural people and also lead to greater investment efficiency. Second, incorporating social preference into the GIS takes into account the crucial element of social capital (viz., social preference), which should lead to higher levels of community acceptance of plantation projects because those plantations would be established on socially suitable land. A second GIS exercise showed how conservation investment decisions could be informed using the integrated method. The results of this study support the idea that GIS-aided planning activities can be enhanced through the incorporation of social data into the analysis. When applicable, spatial data collection efforts for GIS-based planning exercises should incorporate spatial socioeconomic data.     

Selecting suitable sites for animal waste application using a raster GIS

Rapid growth of intensive animal industries in southeast Queensland, Australia, has led to large volumes of animal waste production, which posses serious environmental problems in the Murray Darling Basin (MDB). This study presents a method of selecting sites for the safe application of animal waste as fertiliser to agricultural land. A site suitability map for the Westbrook subcatchment within the MDB was created using a geographic information system (GIS)-based weighted linear combination (WLC) model. The factors affecting the suitability of a site for animal waste application were selected, and digital data sets derived from up to 1:50,000 scale maps were acquired. After initial preprocessing, digital data sets were clipped to the size of the delineated subcatchment boundary producing input factors. These input factors were weighted using the analytical hierarchy process (AHP) that employed an objectives-oriented comparison (OOC) technique to formulate the pairwise comparison matrix. The OOC technique, which is capable of deriving factor weight independently, formulated the weight derivation process by making it more logical and systematic. The factor attributes were classified into multiple classes and weighted using the AHP. The effects of the number of input factors and factor weighting on the areal extent and the degree of site suitability were examined. Due to the presence of large nonagricultural and residential areas in the subcatchment, only 16% of the area was found suitable for animal waste application. The areal extent resulting from this site suitability assessment was found to be dependent on the areal constraints imposed on each input factor, while the degree of suitability was principally a function of the weight distribution between the factors.