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GIS in Environmental Management
Abstract
In the modern day with environmental issues such as climate change, pollution and resource depletion becoming increasingly significant, there exists, more than at any other point in history, a necessity to effectively manage, preserve and restore natural resources and environments. This increased requirement for sustainability has led to a greater need for information to allow for the making of educated decisions in the process of environmental management. An important aspect of any approach to environmental management problems lies with the ability to represent spatially the elements of the environment pertinent to the decision context. GIS (Geographic Information Systems) provide a suitable interface for such a representation. This paper examines the role and functionality of GIS as a decision support tool for the conceptualization of solutions for environmental management problems.
provided as a means of illustrating the use of the tool in an Irish environment; the evolution of GIS in forestry management is articulated through the case study of Coilte; whilst Mayo County Council's renewable energy plan is employed as a means of demonstrating the utility of GIS in planning for the deployment of renewable energy technologies. With extensive context provided, the general field of GIS in environmental management is critically analyzed focusing on the key challenges presented by the development of the area.
2. What is GIS?
As Heywood et al (2011) observe, GIS is a somewhat problematic concept to define. A logical starting point is to individually examine the letters that comprise the acronym. “Geographic” identifies that what is being studied is of a spatial nature and that the distribution in terms of quality or quantity of this phenomena is spatially variable. “Information” indicates that considerations need to be made for the input of raw data, in a GIS this data is grounded in its pattern of spatial distribution and may be related to map coordinates or be representative of topological attributes. “Systems” suggests that there is some form of linkage between separate entities; in a GIS these may include computer hardware, software, raw data and the human user. As suggested by Pickles (1995), any given definition of GIS is likely to vary depending on the background and viewpoint of the individual giving the definition. Indeed, the large variability in definitions of GIS is exemplified by Maguire (1991), who offers a list of 11 different definitions. This high variability in definitions can in part be explained by the diverse knowledge base that underpins GIS. GIS draws on a substantial range of disciplines including, cartography, cognitive science, computer science, engineering, environmental science, geodesy, public policy, statistics and photogrammetry (Heywood et al, 2011). Central to GIS is spatial data, typically characterized by information about positions, connections with other features and details of nonspatial characteristics (Burrough, 1986). In order for it to be efficiently stored on a computer there is a
1. Introduction
The principal aim of this paper is to provide a broad overview of the development of GIS and associated technologies as utilities for the management of the environment and natural resources. The paper is roughly divided into two main sections, the first section of the paper provides context to the area as a whole, beginning with a brief definition of GIS and a review of the common applications for which GIS is employed. This is augmented by a consideration of notable developments in GIS technology in recent years. A broad foundation is then provided in the conceptual underpinnings of GIS for environmental management, additionally, the development of key GIS related technologies, principally focusing on remote sensing, is discussed and considered in relation to the area of study. The second section of the paper aims to build upon these foundations by adopting a more critical and analytical approach. Broad context is provided through a general literature review of contemporary studies where GIS have been employed in the process of environmental and natural resource management. More detail is provided as the main areas of focus, forestry management and renewable energy planning, are examined. Case studies on these two areas are
requirement for spatial data to be simplified. The most commonly employed methodology for doing this is to break down all the geographic features into three main entity types: points, lines and polygons. Points are used to represent exact locations of smaller features, line features may be used to represent features such as rivers or roads, whereas polygons are employed to represent geographical zones. In the case of polygon data the represented phenomenon may or may not be observable in the physical world. These representations are held within GIS according to one of two different data models – raster or vector. Put simply, the raster data model uses a system of rows, columns and cells, with each cell storing a single value relating to it's graphical properties. The vector data model employs an x and y coordinate system to plot geographic features, using the three aforementioned data types. In summary, GIS are a computer system, consisting of hardware, software and appropriate procedures. GIS deal with spatially referenced or geographical data and carries out a variety of management and analysis tasks on this data. As such, GIS can be utilized to add value to spatial data. This may be completed through the reorganization of data to allow it to be viewed more efficiently or through the integration of two or more sets of data thereby allowing for the creation of a new data-set that can be operated on in turn. Crucially, in an environmental management context, GIS create useful information to assist in the process of decision making.
(RRLs) in the UK (Goodchild & Rhind, 1990; Masser, 1990). Whilst much research was being carried out with GIS technology in specialist areas, due to the high set up and maintenance costs, it did not receive routine and mainstream usage until the early years of the twenty-first century (Heywood et al, 2011). Indeed, in the 2000s GIS usage diffused into a broad range of society, with it's use in navigation systems and online mapping it became a part of everyday life and accessible through devices such as mobile phones and desktop PCs. In the twenty-first century GIS systems can now handle raster and vector data types, rather than one or the other as was previously the case and data exchange has been standardized (Heywood et al, 2011). GIS continues to be an area of considerable growth, with a software industry that has been growing at more than 20% a year for several years and recent figures for total annual sales of GIS software exceed $800 million (Bernhardsen, 2002). In the modern day GIS technology finds application in myriad different fields. Both the public and private sectors have found increased utility for GIS and the optimised management capabilities that they provide. From it's use in supporting location decisions in the retail sector to it's use in assessment of natural hazards or infrastructure management in the public sector, GIS now pervade an ever increasing portion of society.
3. Development of GIS
The history of GIS can be traced back to the 1960s, with the first notable use of the acronym to describe a system occurring in Canada with the Canadian Geographic Information System (CGIS) appearing in 1964 (Goodchild, 1995). Additionally pioneering work by the US Bureau of Census led to the digital input of the 1970 census (Heywood et al, 2011). Rhind (1987) contends that the term GIS was considered to be in common usage in the UK by the mid-1980s. Indeed, the advent of the first microcomputers using the Intel 80386 chip in 1986 allowed for the development of a new generation of microcomputer based GIS (Taylor, 1990). Another notable technical development, brought about by decreasing costs in computer memory, was the increasing use of the raster data model (Goodchild, 1988). The 1980s also saw the setting up of new GIS research initiatives, the National Center for Geographic Information and Analysis (NCGIA) in USA and the Regional Research Laboratories
4. Key GIS Concepts
In many situations, but particularly in environmental planning and decision making the use of GIS is closely related with a range of conceptual frameworks specifically relating to the structuring of the decision making process. A brief outline is provided of the development of this decision making process as relevant to the field of GIS. There does not exist a clear distinction between the conceptual frameworks outlined here, indeed, a combination of elements from two or more frameworks has been utilised in the area of environmental management (Sheppard & Meitner, 2005; Boroushaki & Malczewski, 2010).
4.1. Spatial Decision Support Systems
The role played by GIS in the process of environmental management and decision making is closely intertwined with that of spatial decision support systems (SDSS). SDSS typically combine GIS and decision support systems (DSS). The term 'decision support system' refers to the integration of
a decision maker's own insights with the information processing capabilities of a computer (Keen & Scott-Morton, 1978; Turban, 1993). DSS came about as a result of seminal work carried out by Herbert A. Simon in the 1950s and 1960s (Simon, 1960). An early example of a DSS was IBM’s Geodata Analysis and Display System (GADS) which was developed in the 1970s (Sprague & Watson, 1996). Whilst decision making that concerns geographic problems has been in existence for some time, increasing concerns about environmental, land use, natural resources and transportation issues have seen an increasing amount of emphasis put on the process of making spatial decisions. This emphasis has, in many cases, centred on how best to incorporate those who are affected by such issues in the decision making process. Indeed, many geographic decision problems are viewed as inherently unstructured and imbued with locational conflicts as their solution involves the participation of multiple stakeholder groups with a variety of different values and priorities. The complex and ill-defined nature of these problems necessitated an elevated level of organization in the process of decision making, leading to the development of SDSS (Malczewski, 1997). Simply defined, SDSS are, interactive, computer based systems designed to support a user or group of users in achieving a higher effectiveness of decision making while solving a semi-structured spatial problem (Sprague & Carlson, 1982). The decision support utility provided by GIS is particularly noteworthy in an environmental management context as it allows for the evaluation of a significantly greater number of alternatives, both of a spatial and aspatial nature, than would traditionally be the case (Cowen, 1990).
GIS is combined with the techniques and procedures for structuring decision problems and designing alternatives provided by MCDA. MCDA within the framework of GIS has been developed as a methodology for taking into account competing site selection objectives. As observed by Jankowski (1995), GIS and MCDA techniques are ideally suited to the spatial nature of site selection decision-making problems. The development of MCDA within GIS analysis is demonstrated by the extensive contemporary literature that employs the methodology. As Malczewski (2006) reports, in a comprehensive review of contemporary literature on the subject, over 300 GIS-MCDA articles have been published in refereed journals since 1990.
4.3. Participatory GIS
Participatory GIS (PGIS), a term first explicitly used by Harris et al (1995), is closely related to other forms of GIS that are based on societal interaction with geographic information, such as public participatory GIS (PPGIS) and communityintegrated GIS (CiGIS). The existence of these differing forms of classification produces a somewhat challenging definition space. Consequentially a simplified formulation of classification is adopted in the context of this paper, as previously contended by Harris and Weiner (2003), the umbrella term PGIS is employed to define the development and use of systems that involve participation of both the public and other stakeholders. In the context of environmental management PGIS provides an enhanced level of problem solving capabilities, as there is a general involvement of numerous stakeholders operating from a range of different perspectives and with a variety of different goals and objectives (Jankowski & Nyerges, 2001). This is of particular pertinence and utility in situations where there is an inequality in terms of decision making influence amongst stakeholder groups. As Harris and Weiner (2003) contend, the main challenges to successful implementation of PGIS are of a socio-political nature as many participatory projects are carried out in a top down manner with decision making power monopolised by local elites. Indeed, as Sieber (2006) observes, PGIS allows the academic practices of GIS to be brought to the local level in order to empower and include marginalized populations.
4.2. Multi Criteria Decision Analysis
Multi criteria decision analysis (MCDA) refers to a decision making approach that considers a variety of different criteria. In any decision making environment there are typically a range of multiple conflicting criterion, often there is no one optimal solution and the selected solution depends on the priorities of the decision maker. MCDA provides a structured process for the arrival at a considered and educated decision. The problem solving approach of MCDA has been integrated with GIS in many contemporary studies. The combination of the distinct areas of GIS and MCDA can provide significant benefit for the solution of problems of a spatial nature. As the decision analysis capability of
5. Remote Sensing
Remote sensing refers to techniques involved in making measurements of objects or phenomenon without actual physical contact. Remote sensing, as a field, encompasses a vast array of different techniques; from digital scanning and optochemical photography from satellites and aircraft, laser and radar profiling, to echo sounding from ships. Whilst a detailed discussion of remote sensing and it's scientific background lies far beyond the scope of this paper, the seminal work of Robert Colwell (1983) and later volumes in the same series (Henderson & Lewis, 1998; Rencz & Ryerson, 1999; Ustin, 2004) provide a comprehensive overview of the technological and scientific underpinnings of the subject and it's contemporary applications. Giles Foody (2008, pp. 223) notes that, “remote sensing now routinely provides environmental information at scales from the local to global and geographical information systems provide, among other things, a means to store, analyze and visualize spatial data”. A basic introduction is provided here to two of the most common forms of remote sensing pertinent to GIS: aerial photography and satellite images.
on natural habitats and biodiversity (Plieninger, 2006). The value of aerial photographs as an input data source for GIS is demonstrated by the aforementioned studies. Curran (1989) contends that aerial photographs are of particular value in a GIS context and identifies their wide availability and low cost in comparison to other sources of remotely sensed data as being integral to this. Additionally, the wide area views, time-freezing capabilities, high spectral and spatial resolution and three-dimensional perspectives afforded by aerial photographs are key qualities that make them of significant utility. As such, aerial photography represents a versatile, relatively affordable and detailed data source for many GIS applications.
5.2. Satellite Images
Satellite images are collected by sensors on board satellites orbiting Earth and are then relayed to ground level through a series of electronic signals, these signals are then processed by a computer to create an image. There are a variety of different methods for processing this information, with each methodology producing a different digital version of the image (Heywood et al, 2011). There exist two main methods of remote sensing through satellite images, the key difference being in the type of sensor used to collect the data. Put simply, the two principle types of sensor are passive and active. Passive sensors measure radiation that arrives at a detector without the sensor first emitting a radiation pulse. Whereas, active sensors release a pulse and later measure the energy returned or bounced back to a detector (Turner et al, 2003). Vegetation structure and ground surface elevations are regularly measured through active sensors. As the strength and timing of the returned signal describes the physical properties of remotely sensed objects (Turner et al, 2003). These qualities of remote sensing through satellite images have seen it find significant utility in the area of environmental management and specifically in the area of measuring biodiversity. Despite earlier studies having contended that the inability to resolve individual organisms makes remote sensing of biodiversity something of a 'fool's errand' (Turner et al, 2003). In a detailed review of literature on the subject Foody (2008), makes reference to a significant body of research using remote sensing to map land cover by vegetation and consequently using vegetation type as a surrogate for habitat type and therefore biodiversity. Additionally, Foody observes that the increasing spatial resolution of
5.1. Aerial Photography
The oldest method of terrestrial remote sensing, aerial photography is the capturing of images from a position above the surface of the earth or without direct contact with the object in question. Aerial photography finds two principle uses within GIS. Firstly, as a background for other data in order to provide spatial context and aid interpretation. Secondly, as a means for the abstraction of information pertaining to land use, vegetation type, moisture or heat levels or various other aspects of the environment from the photograph (Heywood et al, 2011). This function of aerial photography is of particular utility in the context of environmental management, particularly for the monitoring of change in environmental factors over a period of time. As such, there exists a burgeoning literature utilising GIS and aerial photography. One area that has seen significant use of aerial photography in conjunction with GIS is the mapping of temporal changes in the spatial distribution of a variety of species of plants and vegetation (Robbins, 1997; Higinbotham et al, 2004). More specifically, the technology has been utilised to map woodland coverage and the consequential risk of forest fires (Mast et al, 1997; Keane et al, 2001). Additionally, the combination of aerial photography and GIS has been utilised to study the effects of land use change
satellite images has allowed research to move away from broad classes such as land cover and move towards the mapping of specific classes such as tree species. Indeed this is exemplified by studies focused on tree species identification and tree mortality (Clark et al, 2004). As such, GIS used in conjunction with remotely sensed satellite images has provided a wealth of data on environmental properties. This is particularly true in studies of biodiversity, where remotely sensed data has provided a significant basis for better understanding of the environmental drivers of species distribution. Indeed, with further advances in the technology likely, there is great potential for its use in aiding conservation and protecting habitats.
management, are introduced and contextualized in terms of short case studies of the development of the respective areas in Ireland. It is hoped that this will allow for better articulation of the diverse applications for which GIS finds utility and facilitate discussion of the potential that exists for GIS based systems in the area of environmental management. The use of GIS to monitor and control pollution levels is an area of research that has been receiving increased attention in recent years. In an Irish context the compilation of the Environmental Protection Agency's programme of water quality monitoring was carried out with significant use of GIS (EPA, 2010). The aforementioned case, which came about as a response to the EU Water Framework Directive (EP & CEU, 2000), is one of numerous examples where GIS has been employed for the setting of sustainable environmental targets through centralised directives that are enacted on a local scale. There exists an extensive literature examining soil geochemistry and identifying potential pollutants, much of this research has been heavily grounded in the use of geostatistics to analyze the spatial and temporal changes of chemical composition of soil. This line of inquiry has been well researched in an Irish context (McGrath et al, 2004; McGrath & Zhang, 2004). Indeed, research carried out in Galway, Ireland, used GIS to map soil pollution and identified areas with significant levels of pollution, leading to changes in the use of public land as a result of the research (Zhang, 2006; Carr et al, 2008; Dao et al, 2010).
Fig.1. Satellite image of effects of deforestation in Milne Bay, Papua New Guinea.
6. GIS in Environmental Management in Ireland.
The development of environmental planning, as a field, has been catalyzed by the capabilities of GIS. This is demonstrated by the diverse nature of contemporary studies utilizing GIS. Indeed, the existence of such a wide ranging and significant body of literature on this area necessitates a more focused approach in the context of this paper. As such, the proceeding review of literature deals principally with studies carried out in an Irish context. Furthermore, the main areas of investigation are significantly distilled to allow for considered analysis. The use of GIS in studies monitoring pollution levels is briefly reviewed and discussed. The principle foci of investigation, renewable energy planning and forestry
The investigation of issues pertaining to air quality is an area that has also found application for GIS technology (Fedra & Haurie, 1999). In an Irish context, novel applications for utilising freely available data have been developed for the measuring of carbon dioxide sequestration by inner city trees (Ningal, 2011). The aforementioned study established the potential for trees to contribute to improved air quality, but also identified the requirement for better management in this area.
6.1. GIS in Forestry Management
Due to the multi-faceted role of the resource, forest management requires decision-making that is capable of recognizing and incorporating a diverse range of ecological, economic and social processes. Additionally, it necessitates the consideration of a multitude of variables and conflicting objectives and constraints. As such, recent years have seen the development of a body of literature focusing on
methodologies for sustainable forest management. Sustainable forest management broadly refers to the stewardship and use of forests in a way that maintains diversity, productivity and regeneration capacity, whilst also maintaining ecological, economic and social functions without causing damage to other ecosystems. However, as Varma (2000) observes, the exact definition of sustainable forestry management has been widely contested. Nevertheless, it is generally accepted that sustainable forest management shares the same basic principles as the theory of sustainable development contended by Bruntland (1987) (Ferguson, 1996). As such, there exists significant potential for the use of GIS in combination with decision making frameworks such as SDSS or MCDA in the area of forestry management. Specifically, to address two main goals, the maintenance of the sustainability of the forest ecosystem and the maximization of utility through optimal land use. The decision support approach provides a means of overcoming the complexity of this problem, through combining the decision makers subjective knowledge and the data integration and analysis capabilities of GIS. Indeed, this approach is of particular utility when there is an elevated quantity of criteria and data combined with large physical areas of land. 6.1.1. Case Study: Forestry Management in Coilte (adapted from MacDonagh, 2011) Coilte is a commercial company operating primarily in the forestry industry and has been a client of leading GIS software producer ESRI since 1987; Coilte own 1 million acres of land in Ireland (7% of total land area). The problems faced by Coilte can be broadly defined as the sum of all available decisions versus decision processing capability, as a large variety of external factors impinge what decisions Coilte can legitimately enact. Firstly, a large body of regulation dictates what areas may or may not be harvested, this regulation relates to forest harvesting sustainability, forest environmental regulation and EU national habitats laws. These regulations need to be traded off against the high demand on part of the consumer and the need to provide other stakeholders with a profitable product, whilst also taking into account issues such as volatility of prices and consistency of product. Indeed, Coilte has to consider 29 relevant spatial datasets that specify details of what areas may be harvested and in what manner with separate rules existing for different species or contexts. This represents a significantly challenging decision space
and as such it is not practically possible to keep plans fluid and linked to strategy. As a result, in 2010 Coilte began 'solution hunting' and implemented GIS-MCDA technology, this was specifically designed by Remsoft Technology to meet the needs of the company. As a result Coilte has benefited from an expanded decision space that allows the company to achieve their strategy with increased ease and success. Ultimately the use of GIS and MCDA has allowed Coilte to compile a schedule of activity in the forest that meets strategic goals in a sustainable and more efficient way.
Fig.2. Coilte forests in Ireland. (MacDonagh, 2011)
6.2. GIS in Renewable Energy Planning
Renewable energy is energy which comes from natural resources such as wind, rain, sunlight, the ocean and geothermal heat. There is a global focus on the departure from reliance on fossil fuel for our energy needs to renewable options. This focus is exemplified by increasing legislation at both a national and international level (Government of Ireland, 2009; UNFCC, 1998; EP & CEU, 2000). There exists a burgeoning literature analyzing methodologies for the identification of optimal locations for the citing of renewable energy locations that employ GIS. Baban and Parry (2001) suggest that selection of suitable locations is one of the biggest issues impinging the exploitation of renewable resources. GIS has been utilised as a means for the identification of most suitable locations for a wide variety of renewable energy technologies, however wind and wave energy
predominate in contemporary studies. Baban and Parry (2001) evaluated a wide range of factors in a study of optimal wind farm locations in Lancashire, England. Whilst a similar study was carried out by Graham et al (2003), which focused on the identification of potential wave farm locations off the Scottish coast. Wind farm site suitability studies have also incorporated GIS as a means for the consideration of the impact of a wide range of physical, environmental and human factors (Meentemeyer & Rodman, 2006). The economic feasibility of wave energy in terms of cost to connect to the electricity grid and the challenges posed by physical and political constraints has been outlined in an Australian context (Prest et al, 2007). Additionally, the utility of GIS for the evaluation of the suitability of different forms of renewable energy technologies, such as wind, solar and biomass has been demonstrated (Yue & Wang, 2006). It is clear that the potential for GIS to assist in the decision making process in this field is being increasingly exploited. 6.2.1. Case Study: Renewable Energy Planning in Mayo County Council (adapted from Collier, 2010; Mayo County Council, 2011; Worsfold, 2012) The Renewable Energy Strategy (RES) implemented by Mayo County Council is underpinned by several assessments which gauge a wide range of environmental factors and identify areas of concern or importance. Specifically, the Strategic Environmental Assessment (SEA), Habitats Directive Assessment (HDA) and Flood Risk Assessment (FRA), these assessments assist in informing decision makers and interested parties of the likely impacts of implementing the strategy on different aspects of the environment. SEA is a statutory systematic process of predicting and evaluating the likely environmental effects of implementing a plan or programme in order to ensure that these effects are appropriately addressed at the earliest stage of decision making. In the context of Mayo, SEA production consisted of: screening, whereby the public and agencies were asked for their input; scoping, to determine the range of environmental issues and level of detail to be included; production of an environmental report, to identify, predict, evaluate and mitigate potential impacts; and, monitoring, in order to consult and revise activities after the adoption of the strategy. Once the environmental parameters and viable forms of renewable energy were identified from the SEA, an 'environmental vulnerability map' was created using GIS software FME. This process involved the input of key datasets, sourced from a
variety of different agencies and third parties. The key features were then filtered and any linear datasets were buffered where necessary. Sensitivity values were then assigned according to the findings of the SEA and attribute pre-fixers were used to tag input datasets, with the final step the spatial overlay of the datasets, thereby creating the environmental vulnerability map. This can then be used to strategically plan and make decisions as to where best to cite renewable energy technology without impinging on any of the areas of environmental sensitivity as identified at the assessment stage.
Fig.3. Map showing potential areas for wave energy technology in Mayo (Mayo County Council, 2011).
7. Conclusion
This paper has provided a broad overview of the methodological components of GIS in environmental management. Specifically, it has sought to address two main goals: to contextualise the use of GIS and related technologies both in terms of their historical development and in their use and application in the management of the Irish environment; secondly, to illustrate the significant potential utility that exists for GIS to revise approaches to environmental management and optimise strategies for sustainable development of natural resources. A review of literature revealed numerous studies examining GIS based approaches to environmental management in a range of different contexts and with a similarly broad variety of methodologies. The proliferation of freely available
environmental data through government organisations and other research bodies means that significant potential exists for more development in this area. Indeed, there is a surprisingly little amount of research conducted using freely available data sets, such as that collected for the Water Frameworks Directive, as a basis for inquiry. This is especially noteworthy given the considerable expense that has gone into compiling such datasets. Nevertheless, it is clear that GIS, particularly as spatial decision support tool, has a key role to play in the future development of the field of environmental management. This is particularly significant in the milieu of legislation and regulation that pervades the general area of environmental planning and natural resource management. As the use of GIS and related technologies allow for the management of the environment in a manner that complies with regulation and maintains sustainability. GIS is able to provide significant utility in this aspect and offers great potential for future development as technological capabilities increase. However, it is worth considering the criticality of the role played by the human user. GIS offers considerable capabilities in terms of data analysis and integration, however, without some form of human innovation in terms of management, interpretation and development this data is rendered redundant.
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doc_382550892.pdf
This is a pdf explains about GIS in environmental management.
GIS in Environmental Management
Abstract
In the modern day with environmental issues such as climate change, pollution and resource depletion becoming increasingly significant, there exists, more than at any other point in history, a necessity to effectively manage, preserve and restore natural resources and environments. This increased requirement for sustainability has led to a greater need for information to allow for the making of educated decisions in the process of environmental management. An important aspect of any approach to environmental management problems lies with the ability to represent spatially the elements of the environment pertinent to the decision context. GIS (Geographic Information Systems) provide a suitable interface for such a representation. This paper examines the role and functionality of GIS as a decision support tool for the conceptualization of solutions for environmental management problems.
provided as a means of illustrating the use of the tool in an Irish environment; the evolution of GIS in forestry management is articulated through the case study of Coilte; whilst Mayo County Council's renewable energy plan is employed as a means of demonstrating the utility of GIS in planning for the deployment of renewable energy technologies. With extensive context provided, the general field of GIS in environmental management is critically analyzed focusing on the key challenges presented by the development of the area.
2. What is GIS?
As Heywood et al (2011) observe, GIS is a somewhat problematic concept to define. A logical starting point is to individually examine the letters that comprise the acronym. “Geographic” identifies that what is being studied is of a spatial nature and that the distribution in terms of quality or quantity of this phenomena is spatially variable. “Information” indicates that considerations need to be made for the input of raw data, in a GIS this data is grounded in its pattern of spatial distribution and may be related to map coordinates or be representative of topological attributes. “Systems” suggests that there is some form of linkage between separate entities; in a GIS these may include computer hardware, software, raw data and the human user. As suggested by Pickles (1995), any given definition of GIS is likely to vary depending on the background and viewpoint of the individual giving the definition. Indeed, the large variability in definitions of GIS is exemplified by Maguire (1991), who offers a list of 11 different definitions. This high variability in definitions can in part be explained by the diverse knowledge base that underpins GIS. GIS draws on a substantial range of disciplines including, cartography, cognitive science, computer science, engineering, environmental science, geodesy, public policy, statistics and photogrammetry (Heywood et al, 2011). Central to GIS is spatial data, typically characterized by information about positions, connections with other features and details of nonspatial characteristics (Burrough, 1986). In order for it to be efficiently stored on a computer there is a
1. Introduction
The principal aim of this paper is to provide a broad overview of the development of GIS and associated technologies as utilities for the management of the environment and natural resources. The paper is roughly divided into two main sections, the first section of the paper provides context to the area as a whole, beginning with a brief definition of GIS and a review of the common applications for which GIS is employed. This is augmented by a consideration of notable developments in GIS technology in recent years. A broad foundation is then provided in the conceptual underpinnings of GIS for environmental management, additionally, the development of key GIS related technologies, principally focusing on remote sensing, is discussed and considered in relation to the area of study. The second section of the paper aims to build upon these foundations by adopting a more critical and analytical approach. Broad context is provided through a general literature review of contemporary studies where GIS have been employed in the process of environmental and natural resource management. More detail is provided as the main areas of focus, forestry management and renewable energy planning, are examined. Case studies on these two areas are
requirement for spatial data to be simplified. The most commonly employed methodology for doing this is to break down all the geographic features into three main entity types: points, lines and polygons. Points are used to represent exact locations of smaller features, line features may be used to represent features such as rivers or roads, whereas polygons are employed to represent geographical zones. In the case of polygon data the represented phenomenon may or may not be observable in the physical world. These representations are held within GIS according to one of two different data models – raster or vector. Put simply, the raster data model uses a system of rows, columns and cells, with each cell storing a single value relating to it's graphical properties. The vector data model employs an x and y coordinate system to plot geographic features, using the three aforementioned data types. In summary, GIS are a computer system, consisting of hardware, software and appropriate procedures. GIS deal with spatially referenced or geographical data and carries out a variety of management and analysis tasks on this data. As such, GIS can be utilized to add value to spatial data. This may be completed through the reorganization of data to allow it to be viewed more efficiently or through the integration of two or more sets of data thereby allowing for the creation of a new data-set that can be operated on in turn. Crucially, in an environmental management context, GIS create useful information to assist in the process of decision making.
(RRLs) in the UK (Goodchild & Rhind, 1990; Masser, 1990). Whilst much research was being carried out with GIS technology in specialist areas, due to the high set up and maintenance costs, it did not receive routine and mainstream usage until the early years of the twenty-first century (Heywood et al, 2011). Indeed, in the 2000s GIS usage diffused into a broad range of society, with it's use in navigation systems and online mapping it became a part of everyday life and accessible through devices such as mobile phones and desktop PCs. In the twenty-first century GIS systems can now handle raster and vector data types, rather than one or the other as was previously the case and data exchange has been standardized (Heywood et al, 2011). GIS continues to be an area of considerable growth, with a software industry that has been growing at more than 20% a year for several years and recent figures for total annual sales of GIS software exceed $800 million (Bernhardsen, 2002). In the modern day GIS technology finds application in myriad different fields. Both the public and private sectors have found increased utility for GIS and the optimised management capabilities that they provide. From it's use in supporting location decisions in the retail sector to it's use in assessment of natural hazards or infrastructure management in the public sector, GIS now pervade an ever increasing portion of society.
3. Development of GIS
The history of GIS can be traced back to the 1960s, with the first notable use of the acronym to describe a system occurring in Canada with the Canadian Geographic Information System (CGIS) appearing in 1964 (Goodchild, 1995). Additionally pioneering work by the US Bureau of Census led to the digital input of the 1970 census (Heywood et al, 2011). Rhind (1987) contends that the term GIS was considered to be in common usage in the UK by the mid-1980s. Indeed, the advent of the first microcomputers using the Intel 80386 chip in 1986 allowed for the development of a new generation of microcomputer based GIS (Taylor, 1990). Another notable technical development, brought about by decreasing costs in computer memory, was the increasing use of the raster data model (Goodchild, 1988). The 1980s also saw the setting up of new GIS research initiatives, the National Center for Geographic Information and Analysis (NCGIA) in USA and the Regional Research Laboratories
4. Key GIS Concepts
In many situations, but particularly in environmental planning and decision making the use of GIS is closely related with a range of conceptual frameworks specifically relating to the structuring of the decision making process. A brief outline is provided of the development of this decision making process as relevant to the field of GIS. There does not exist a clear distinction between the conceptual frameworks outlined here, indeed, a combination of elements from two or more frameworks has been utilised in the area of environmental management (Sheppard & Meitner, 2005; Boroushaki & Malczewski, 2010).
4.1. Spatial Decision Support Systems
The role played by GIS in the process of environmental management and decision making is closely intertwined with that of spatial decision support systems (SDSS). SDSS typically combine GIS and decision support systems (DSS). The term 'decision support system' refers to the integration of
a decision maker's own insights with the information processing capabilities of a computer (Keen & Scott-Morton, 1978; Turban, 1993). DSS came about as a result of seminal work carried out by Herbert A. Simon in the 1950s and 1960s (Simon, 1960). An early example of a DSS was IBM’s Geodata Analysis and Display System (GADS) which was developed in the 1970s (Sprague & Watson, 1996). Whilst decision making that concerns geographic problems has been in existence for some time, increasing concerns about environmental, land use, natural resources and transportation issues have seen an increasing amount of emphasis put on the process of making spatial decisions. This emphasis has, in many cases, centred on how best to incorporate those who are affected by such issues in the decision making process. Indeed, many geographic decision problems are viewed as inherently unstructured and imbued with locational conflicts as their solution involves the participation of multiple stakeholder groups with a variety of different values and priorities. The complex and ill-defined nature of these problems necessitated an elevated level of organization in the process of decision making, leading to the development of SDSS (Malczewski, 1997). Simply defined, SDSS are, interactive, computer based systems designed to support a user or group of users in achieving a higher effectiveness of decision making while solving a semi-structured spatial problem (Sprague & Carlson, 1982). The decision support utility provided by GIS is particularly noteworthy in an environmental management context as it allows for the evaluation of a significantly greater number of alternatives, both of a spatial and aspatial nature, than would traditionally be the case (Cowen, 1990).
GIS is combined with the techniques and procedures for structuring decision problems and designing alternatives provided by MCDA. MCDA within the framework of GIS has been developed as a methodology for taking into account competing site selection objectives. As observed by Jankowski (1995), GIS and MCDA techniques are ideally suited to the spatial nature of site selection decision-making problems. The development of MCDA within GIS analysis is demonstrated by the extensive contemporary literature that employs the methodology. As Malczewski (2006) reports, in a comprehensive review of contemporary literature on the subject, over 300 GIS-MCDA articles have been published in refereed journals since 1990.
4.3. Participatory GIS
Participatory GIS (PGIS), a term first explicitly used by Harris et al (1995), is closely related to other forms of GIS that are based on societal interaction with geographic information, such as public participatory GIS (PPGIS) and communityintegrated GIS (CiGIS). The existence of these differing forms of classification produces a somewhat challenging definition space. Consequentially a simplified formulation of classification is adopted in the context of this paper, as previously contended by Harris and Weiner (2003), the umbrella term PGIS is employed to define the development and use of systems that involve participation of both the public and other stakeholders. In the context of environmental management PGIS provides an enhanced level of problem solving capabilities, as there is a general involvement of numerous stakeholders operating from a range of different perspectives and with a variety of different goals and objectives (Jankowski & Nyerges, 2001). This is of particular pertinence and utility in situations where there is an inequality in terms of decision making influence amongst stakeholder groups. As Harris and Weiner (2003) contend, the main challenges to successful implementation of PGIS are of a socio-political nature as many participatory projects are carried out in a top down manner with decision making power monopolised by local elites. Indeed, as Sieber (2006) observes, PGIS allows the academic practices of GIS to be brought to the local level in order to empower and include marginalized populations.
4.2. Multi Criteria Decision Analysis
Multi criteria decision analysis (MCDA) refers to a decision making approach that considers a variety of different criteria. In any decision making environment there are typically a range of multiple conflicting criterion, often there is no one optimal solution and the selected solution depends on the priorities of the decision maker. MCDA provides a structured process for the arrival at a considered and educated decision. The problem solving approach of MCDA has been integrated with GIS in many contemporary studies. The combination of the distinct areas of GIS and MCDA can provide significant benefit for the solution of problems of a spatial nature. As the decision analysis capability of
5. Remote Sensing
Remote sensing refers to techniques involved in making measurements of objects or phenomenon without actual physical contact. Remote sensing, as a field, encompasses a vast array of different techniques; from digital scanning and optochemical photography from satellites and aircraft, laser and radar profiling, to echo sounding from ships. Whilst a detailed discussion of remote sensing and it's scientific background lies far beyond the scope of this paper, the seminal work of Robert Colwell (1983) and later volumes in the same series (Henderson & Lewis, 1998; Rencz & Ryerson, 1999; Ustin, 2004) provide a comprehensive overview of the technological and scientific underpinnings of the subject and it's contemporary applications. Giles Foody (2008, pp. 223) notes that, “remote sensing now routinely provides environmental information at scales from the local to global and geographical information systems provide, among other things, a means to store, analyze and visualize spatial data”. A basic introduction is provided here to two of the most common forms of remote sensing pertinent to GIS: aerial photography and satellite images.
on natural habitats and biodiversity (Plieninger, 2006). The value of aerial photographs as an input data source for GIS is demonstrated by the aforementioned studies. Curran (1989) contends that aerial photographs are of particular value in a GIS context and identifies their wide availability and low cost in comparison to other sources of remotely sensed data as being integral to this. Additionally, the wide area views, time-freezing capabilities, high spectral and spatial resolution and three-dimensional perspectives afforded by aerial photographs are key qualities that make them of significant utility. As such, aerial photography represents a versatile, relatively affordable and detailed data source for many GIS applications.
5.2. Satellite Images
Satellite images are collected by sensors on board satellites orbiting Earth and are then relayed to ground level through a series of electronic signals, these signals are then processed by a computer to create an image. There are a variety of different methods for processing this information, with each methodology producing a different digital version of the image (Heywood et al, 2011). There exist two main methods of remote sensing through satellite images, the key difference being in the type of sensor used to collect the data. Put simply, the two principle types of sensor are passive and active. Passive sensors measure radiation that arrives at a detector without the sensor first emitting a radiation pulse. Whereas, active sensors release a pulse and later measure the energy returned or bounced back to a detector (Turner et al, 2003). Vegetation structure and ground surface elevations are regularly measured through active sensors. As the strength and timing of the returned signal describes the physical properties of remotely sensed objects (Turner et al, 2003). These qualities of remote sensing through satellite images have seen it find significant utility in the area of environmental management and specifically in the area of measuring biodiversity. Despite earlier studies having contended that the inability to resolve individual organisms makes remote sensing of biodiversity something of a 'fool's errand' (Turner et al, 2003). In a detailed review of literature on the subject Foody (2008), makes reference to a significant body of research using remote sensing to map land cover by vegetation and consequently using vegetation type as a surrogate for habitat type and therefore biodiversity. Additionally, Foody observes that the increasing spatial resolution of
5.1. Aerial Photography
The oldest method of terrestrial remote sensing, aerial photography is the capturing of images from a position above the surface of the earth or without direct contact with the object in question. Aerial photography finds two principle uses within GIS. Firstly, as a background for other data in order to provide spatial context and aid interpretation. Secondly, as a means for the abstraction of information pertaining to land use, vegetation type, moisture or heat levels or various other aspects of the environment from the photograph (Heywood et al, 2011). This function of aerial photography is of particular utility in the context of environmental management, particularly for the monitoring of change in environmental factors over a period of time. As such, there exists a burgeoning literature utilising GIS and aerial photography. One area that has seen significant use of aerial photography in conjunction with GIS is the mapping of temporal changes in the spatial distribution of a variety of species of plants and vegetation (Robbins, 1997; Higinbotham et al, 2004). More specifically, the technology has been utilised to map woodland coverage and the consequential risk of forest fires (Mast et al, 1997; Keane et al, 2001). Additionally, the combination of aerial photography and GIS has been utilised to study the effects of land use change
satellite images has allowed research to move away from broad classes such as land cover and move towards the mapping of specific classes such as tree species. Indeed this is exemplified by studies focused on tree species identification and tree mortality (Clark et al, 2004). As such, GIS used in conjunction with remotely sensed satellite images has provided a wealth of data on environmental properties. This is particularly true in studies of biodiversity, where remotely sensed data has provided a significant basis for better understanding of the environmental drivers of species distribution. Indeed, with further advances in the technology likely, there is great potential for its use in aiding conservation and protecting habitats.
management, are introduced and contextualized in terms of short case studies of the development of the respective areas in Ireland. It is hoped that this will allow for better articulation of the diverse applications for which GIS finds utility and facilitate discussion of the potential that exists for GIS based systems in the area of environmental management. The use of GIS to monitor and control pollution levels is an area of research that has been receiving increased attention in recent years. In an Irish context the compilation of the Environmental Protection Agency's programme of water quality monitoring was carried out with significant use of GIS (EPA, 2010). The aforementioned case, which came about as a response to the EU Water Framework Directive (EP & CEU, 2000), is one of numerous examples where GIS has been employed for the setting of sustainable environmental targets through centralised directives that are enacted on a local scale. There exists an extensive literature examining soil geochemistry and identifying potential pollutants, much of this research has been heavily grounded in the use of geostatistics to analyze the spatial and temporal changes of chemical composition of soil. This line of inquiry has been well researched in an Irish context (McGrath et al, 2004; McGrath & Zhang, 2004). Indeed, research carried out in Galway, Ireland, used GIS to map soil pollution and identified areas with significant levels of pollution, leading to changes in the use of public land as a result of the research (Zhang, 2006; Carr et al, 2008; Dao et al, 2010).
Fig.1. Satellite image of effects of deforestation in Milne Bay, Papua New Guinea.
6. GIS in Environmental Management in Ireland.
The development of environmental planning, as a field, has been catalyzed by the capabilities of GIS. This is demonstrated by the diverse nature of contemporary studies utilizing GIS. Indeed, the existence of such a wide ranging and significant body of literature on this area necessitates a more focused approach in the context of this paper. As such, the proceeding review of literature deals principally with studies carried out in an Irish context. Furthermore, the main areas of investigation are significantly distilled to allow for considered analysis. The use of GIS in studies monitoring pollution levels is briefly reviewed and discussed. The principle foci of investigation, renewable energy planning and forestry
The investigation of issues pertaining to air quality is an area that has also found application for GIS technology (Fedra & Haurie, 1999). In an Irish context, novel applications for utilising freely available data have been developed for the measuring of carbon dioxide sequestration by inner city trees (Ningal, 2011). The aforementioned study established the potential for trees to contribute to improved air quality, but also identified the requirement for better management in this area.
6.1. GIS in Forestry Management
Due to the multi-faceted role of the resource, forest management requires decision-making that is capable of recognizing and incorporating a diverse range of ecological, economic and social processes. Additionally, it necessitates the consideration of a multitude of variables and conflicting objectives and constraints. As such, recent years have seen the development of a body of literature focusing on
methodologies for sustainable forest management. Sustainable forest management broadly refers to the stewardship and use of forests in a way that maintains diversity, productivity and regeneration capacity, whilst also maintaining ecological, economic and social functions without causing damage to other ecosystems. However, as Varma (2000) observes, the exact definition of sustainable forestry management has been widely contested. Nevertheless, it is generally accepted that sustainable forest management shares the same basic principles as the theory of sustainable development contended by Bruntland (1987) (Ferguson, 1996). As such, there exists significant potential for the use of GIS in combination with decision making frameworks such as SDSS or MCDA in the area of forestry management. Specifically, to address two main goals, the maintenance of the sustainability of the forest ecosystem and the maximization of utility through optimal land use. The decision support approach provides a means of overcoming the complexity of this problem, through combining the decision makers subjective knowledge and the data integration and analysis capabilities of GIS. Indeed, this approach is of particular utility when there is an elevated quantity of criteria and data combined with large physical areas of land. 6.1.1. Case Study: Forestry Management in Coilte (adapted from MacDonagh, 2011) Coilte is a commercial company operating primarily in the forestry industry and has been a client of leading GIS software producer ESRI since 1987; Coilte own 1 million acres of land in Ireland (7% of total land area). The problems faced by Coilte can be broadly defined as the sum of all available decisions versus decision processing capability, as a large variety of external factors impinge what decisions Coilte can legitimately enact. Firstly, a large body of regulation dictates what areas may or may not be harvested, this regulation relates to forest harvesting sustainability, forest environmental regulation and EU national habitats laws. These regulations need to be traded off against the high demand on part of the consumer and the need to provide other stakeholders with a profitable product, whilst also taking into account issues such as volatility of prices and consistency of product. Indeed, Coilte has to consider 29 relevant spatial datasets that specify details of what areas may be harvested and in what manner with separate rules existing for different species or contexts. This represents a significantly challenging decision space
and as such it is not practically possible to keep plans fluid and linked to strategy. As a result, in 2010 Coilte began 'solution hunting' and implemented GIS-MCDA technology, this was specifically designed by Remsoft Technology to meet the needs of the company. As a result Coilte has benefited from an expanded decision space that allows the company to achieve their strategy with increased ease and success. Ultimately the use of GIS and MCDA has allowed Coilte to compile a schedule of activity in the forest that meets strategic goals in a sustainable and more efficient way.
Fig.2. Coilte forests in Ireland. (MacDonagh, 2011)
6.2. GIS in Renewable Energy Planning
Renewable energy is energy which comes from natural resources such as wind, rain, sunlight, the ocean and geothermal heat. There is a global focus on the departure from reliance on fossil fuel for our energy needs to renewable options. This focus is exemplified by increasing legislation at both a national and international level (Government of Ireland, 2009; UNFCC, 1998; EP & CEU, 2000). There exists a burgeoning literature analyzing methodologies for the identification of optimal locations for the citing of renewable energy locations that employ GIS. Baban and Parry (2001) suggest that selection of suitable locations is one of the biggest issues impinging the exploitation of renewable resources. GIS has been utilised as a means for the identification of most suitable locations for a wide variety of renewable energy technologies, however wind and wave energy
predominate in contemporary studies. Baban and Parry (2001) evaluated a wide range of factors in a study of optimal wind farm locations in Lancashire, England. Whilst a similar study was carried out by Graham et al (2003), which focused on the identification of potential wave farm locations off the Scottish coast. Wind farm site suitability studies have also incorporated GIS as a means for the consideration of the impact of a wide range of physical, environmental and human factors (Meentemeyer & Rodman, 2006). The economic feasibility of wave energy in terms of cost to connect to the electricity grid and the challenges posed by physical and political constraints has been outlined in an Australian context (Prest et al, 2007). Additionally, the utility of GIS for the evaluation of the suitability of different forms of renewable energy technologies, such as wind, solar and biomass has been demonstrated (Yue & Wang, 2006). It is clear that the potential for GIS to assist in the decision making process in this field is being increasingly exploited. 6.2.1. Case Study: Renewable Energy Planning in Mayo County Council (adapted from Collier, 2010; Mayo County Council, 2011; Worsfold, 2012) The Renewable Energy Strategy (RES) implemented by Mayo County Council is underpinned by several assessments which gauge a wide range of environmental factors and identify areas of concern or importance. Specifically, the Strategic Environmental Assessment (SEA), Habitats Directive Assessment (HDA) and Flood Risk Assessment (FRA), these assessments assist in informing decision makers and interested parties of the likely impacts of implementing the strategy on different aspects of the environment. SEA is a statutory systematic process of predicting and evaluating the likely environmental effects of implementing a plan or programme in order to ensure that these effects are appropriately addressed at the earliest stage of decision making. In the context of Mayo, SEA production consisted of: screening, whereby the public and agencies were asked for their input; scoping, to determine the range of environmental issues and level of detail to be included; production of an environmental report, to identify, predict, evaluate and mitigate potential impacts; and, monitoring, in order to consult and revise activities after the adoption of the strategy. Once the environmental parameters and viable forms of renewable energy were identified from the SEA, an 'environmental vulnerability map' was created using GIS software FME. This process involved the input of key datasets, sourced from a
variety of different agencies and third parties. The key features were then filtered and any linear datasets were buffered where necessary. Sensitivity values were then assigned according to the findings of the SEA and attribute pre-fixers were used to tag input datasets, with the final step the spatial overlay of the datasets, thereby creating the environmental vulnerability map. This can then be used to strategically plan and make decisions as to where best to cite renewable energy technology without impinging on any of the areas of environmental sensitivity as identified at the assessment stage.
Fig.3. Map showing potential areas for wave energy technology in Mayo (Mayo County Council, 2011).
7. Conclusion
This paper has provided a broad overview of the methodological components of GIS in environmental management. Specifically, it has sought to address two main goals: to contextualise the use of GIS and related technologies both in terms of their historical development and in their use and application in the management of the Irish environment; secondly, to illustrate the significant potential utility that exists for GIS to revise approaches to environmental management and optimise strategies for sustainable development of natural resources. A review of literature revealed numerous studies examining GIS based approaches to environmental management in a range of different contexts and with a similarly broad variety of methodologies. The proliferation of freely available
environmental data through government organisations and other research bodies means that significant potential exists for more development in this area. Indeed, there is a surprisingly little amount of research conducted using freely available data sets, such as that collected for the Water Frameworks Directive, as a basis for inquiry. This is especially noteworthy given the considerable expense that has gone into compiling such datasets. Nevertheless, it is clear that GIS, particularly as spatial decision support tool, has a key role to play in the future development of the field of environmental management. This is particularly significant in the milieu of legislation and regulation that pervades the general area of environmental planning and natural resource management. As the use of GIS and related technologies allow for the management of the environment in a manner that complies with regulation and maintains sustainability. GIS is able to provide significant utility in this aspect and offers great potential for future development as technological capabilities increase. However, it is worth considering the criticality of the role played by the human user. GIS offers considerable capabilities in terms of data analysis and integration, however, without some form of human innovation in terms of management, interpretation and development this data is rendered redundant.
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