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by Agata Lo Tauro

 

Abstract.The objective of the research is the implementation of Geographic Information System (GIS) for the management of important guidelines related to the Environmental Impact Assessment (EIA) and Spatial data analysis. The Project-GIS is designed to assist the spatial planner with guidance in making land use decisions. For this reason we analysed different informative layers including metereological and air pollution data, cartographic data and thematic information relative to the database for the specialised GIS platform related to the management of regional airports. In particular metereological data including temperature and relative humidity measured at the Catania airport were also analysed according to the European Environment Agency and National and Regional Environmental Policy Acts. In this project we develop geodatabases and GIS specialised in the collection of large data for the implementation of  novel Spatial Decision Support Systems (SDSS). 

 

 

1. Introduction

The Environmental Impact Assessment (EIA) project (2000) was established by the national government to ensure that all agencies of the SAC prepared a project when they undertook major strategic actions, or funded or permitted lower government actions significantly affecting spatial analysis in Sicilian Airports.

In particular, the project was prepared as part of the (EIA) under the Town and Regional Planning Regulations under ISO 19115 and standard which followed the principles set out in the Società Aeroporto di Catania(SAC) White Paper.

The EIA was used: (1) to ensure that local agencies carefully consider significant environmental impacts arising from projects under agency jurisdiction; (2) to establish a procedure by which the public is given an opportunity for meaningful participation in the agency's consideration of the proposed action; and (3) to provide records for efficient spatial analysis. The EIA was designed to be a detailed and quantitative investigation which rigorously analysed the findings of potential environmental impact of the proposed project and also addressed the public concerns.

The inherent spatial requirements of an EIA (i.e., the need to assess the impact of a proposed project on spatial analysis) provides significant opportunities to apply GIS analysis for completing the EIA project. GIS analysis can greatly enhance the evaluation of EIA-required items. A case study of the use of GIS analysis for land, territorial resources (e.g. land use, infrastructures, etc.) and analysis of emissions and dispersion modelling system (e.g. metereological and air pollution data) was also analysed along with a discussion of the benefits of novel geomatic applications.

Addressing land use and territorial resources require the quantification of the land to be affected by the project. Specifically, morphological and land use analysis requires estimating the acreage of various types of land use to be impacted. Spatial analysis requires estimating the amount of available data for EIA.

(1) http://eionet.eu.int/gis/docs/EEA_metadataform_GIS:docand “Specifiche per la realizzazione dei Data Base Topografici di Interesse Generale”, http://www.intesagis.it

(2) SAC (Società Aeroporto di Catania) http://www.aeroporto.catania.it/

2   General background

 

Spatial multicriteria decision problems typically involve a set of geographically-defined alternatives (events) from which a choice of one or more alternatives is made with respect to a given set of evaluation criteria (Jankowski, 1995; Malczewski, 1999).

Two considerations are of paramount importance for spatial multicriteria decision analysis: (1) the GIS component such as data acquisition, storage, retrieval, manipulation, and analysis capability; and (2) the Spatial analysis component such as  aggregation of spatial data and decision makers’ preferences into discrete decision alternatives (Carver, 1991; Jankowski, 1995).

Densham (1991) lists the distinguishing capabilities and functions of Spatial Decision Support Systems (SDSS), which should be capable of: 1) providing mechanisms for the input of spatial data; 2) allowing representation of the spatial relations and structures; 3) including the analytical techniques of spatial and geographical analysis; and 4) providing output in a variety of spatial forms, including thematic cartography. SDSS typically have three components: a database management system and geographical database, a model-based management system (analytical modelling capabilities and analysis procedures), and a dialogue generation and management system (a user interface with display and report generators). Certain authors (e.g., Goodchild et al., 1992) look at the expert analyst required to operate the system as posing a barrier to decision makers who must translate the problem into a form that can be understood by experts who, in turn must translate their understanding of the problem into a form that can be evaluated and solved.

  The development of Geographical Information Systems (GIS) analysis can serve as a valuable tool for E(I)A and Spatial Analysis. Geographical Information System (GIS) are computer systems that can store, integrate, analyze and display spatial data (João & Fonseca,1996). The first systems evolved in the late sixties, and by mid seventies they have been used for EIA. One of the main methods of analysis in GIS is the overlay technique, mentioned above. In 1972 a computerised version of the technique was used for siting power lines and roads (Munn, 1975). It is noteworthy that the so called "first GIS" (Canada GIS or CGIS) was used for EIA in the late 1970s for the preparation of an EIS for a dam on the river Thames (Griffith, 1980). GIS offers a special environment for dealing with the spatial properties of a project. Those special attributes of the GIS are very important for the analysis of environmental issues, since most of them are spatial by nature, and no other computerised system can handle them properly (Schaller,1990). In recent years two important developments have helped in reduce the complexity of spatial analysis. In the last decade, due to the evolution of computer technology, and especially their graphic capabilities, GISs have become more user friendly and powerful. In addition the availability and quality of digital spatial data sets improved, to the level where they are now adequate for routine analysis (Batty,1993). These two trends make possible the set up of and use of GIS at lower cost in terms of time and money then ever before. However, the use of GIS in EIA process in general, and for scoping in particular has been limited, due in part to their cost in terms of time and money relative to the time and budgets allocated for EIA preparation, and especially for scoping. Surveys of the use of GIS in EIA found that while GIS is widely utilised, its use is largely limited to the basic GIS functions such as map production, classic overlay or buffering (João, 1996). This utilisation does not make use of the key advantage of GIS for EIA, its ability to perform spatial analysis and modelling (João & Fonseca, 1996). Noteworthy are some more complex, though sporadic, reports on the uses of GIS for EIA - such as using GIS in complex modelling representation techniques (Schaller, 1990), or its potential as a repository of data and cumulative impact assessment (Johnston et al., 1988; Scott & Saulnier, 1993). Following the analysis in GIS systems they have been widely used for EIA in the last years, though these implementations have not made full use of current GIS capabilities (João, 1996). This may reflect the lack of comprehension of GIS capabilities by EIA practitioners. For example, in a major EIA textbook (Canter, 1996) GIS is mentioned only as a tool for land use and soil impact evaluation. Such oversight may contribute also to the lack of awareness of GIS capabilities within organisations manned by EIA practitioners. The fact that GIS is not used to the extent it can be, theoretically, may also be the outcome of a number of limitations of the GIS systems. Several such limitations were noted in a survey conducted by João and Fonseca (1996). The first limitation is the substantial time and cost required for setting up a GIS system, compiling the necessary data and analysing the systems output. These well-known features create economies of scale in the use of GIS systems (Huxhold & Levinsohn, 1995). Such economies may be of particular relevance for the use of GIS for EIA, as in many cases EIAs are conducted by private consultants operating in a highly competitive market. Many GIS systems are insufficiently accurate for legal purposes due to several reasons, such as: limitations of the photogrammetric process; errors in the process of digitising existing maps; inaccuracies inherent in the maps; maps of different scales; different levels of cartographic representation and cartographic generalisation; and so on.

GIS had an important role to play in improving Environmental Assessment effectiveness and SDSS for Local and Regional Institutions. Joao concludes that the full power of GIS has not been fully explored yet (Joao et al., 1996).

In an EIA framework, GIS can prove particularly useful for the evaluation of cumulative impacts. Smit and Spalding stress the potential of GIS for this type of analysis, arising from the ability to consider the spatial component and to allow the analysis of the temporal evolution (Smit et al., 1995).

GIS can be useful in crossing sectoral and provincial development, forexample in Catania Province, as a powerful tool to identify and analyse site and design alternatives for the implementation of new model of analysis with the support of the earth observation satellite programmes.

 

3   Criteria for selecting the case study and EIA strategies

The clash between development and environment is evident in Catania airport, near a UNESCO World Heritage Site, with a unique natural scenery of the Etna Park. Catania airport provides a fine example of conflicts to be analyzed in a framework of competition for control of (natural) resources (Fig. 1).

Fig. 1.Location of the study area

 

 

Current conflicts of interest, between ministries, institutions and interest groups, and between the central and local governments, are expected to exacerbate in the near future. However, the coal mining sector has a poor environmental record. Catania airport is a priority area for tourism development; the number of visitors increased steadily in the 2000s and reached 400.000 tourists in 2007. Finally, planning also focuses on the development of Catania port, adjacent to Catania airport. With the ad hoc development of different economic sectors, the environmental situation deteriorated, while major industrial developments are planned for Catania airport, again with little environmental consideration. In response, a comprehensive environmental management plan for E(I)A is formulated. Geographical Information Systems (GIS) can serve as a valuable tool for E(I)A and has a role to play in improving Environmental Assessment effectiveness and in validating the multiple-source concept. Furthermore, the use of GIS in EIA helped to manage large data sets, data overlay and analysis of development and resources patterns, trend analysis, data sources for mathematical impact models, spatial analysis and public transportation system. In particular, the following strategies were analysed:

 

 

Topics	Indicators
Analysis of the transportation system	According to ENAV regulations.	1
Analysis of Emissions and Dispersion Modelling System	According to the European Environment Agency and National Environmental Policy Acts
Significant functional effect of the proposed development	Analysis of morphological development and brownfields	3
Significant spatial analysis effect of the proposed development	Land use change	4
Analysis of Infrastructures	Planning of airport services under D.C.A regulations (Direzione Circoscrizionale Aeroportuale)	5

 

Table 1.  Strategies proposed in the EIA.

 

 

The Geodatabase was used in EIA practice mainly as a tool to improve the GIS platform for  baseline information and was restricted to map production and report preparation. In particular we tried to develop a geodatabase to manage georeferenced quality assessment data from the Catania Province for various years.

The geodatabase’s relationships between various assessment unit features (metereological and air pollution data) cartographic data, thematic maps and detailed tables provide GIS staff with versatile analytical capability. By integrating province data formats into a common structure, the geodatabase enables much easier multi-year spatial analysis than before. The necessity of Geodatabase Establishment in EIA demonstrated that GIS can have a wide application in all EIA stages, acting as an integrative framework for the whole process, from the generation, storage and display of the thematic information relative to the vulnerability/sensitivity of the affected resources to impact prediction, and finally for their evaluation for decision support (Antunes et al, 1996). There are several advantages to developing this Geodatabase as a multi-source concept, applying data from various sources: the revisit time (e.i between subsequent acquisitions of affected areas); diachronic evolution of the transportation system; classification of the transportation system (internal, international routes, the marine transportation route etc.). Also, a number of coastal and marine environmental issues have been identified, that are of consequence to current and future investment and development patterns (Fig. 2).

 

Fig. 2.The thematic map

 

3.1 The significance of the approach

Geodatabases and GIS can be viewed as a part of a broader field of spatial decision support systems (SDSS) which have been extensively covered in the literature (e.g., Goodchild and Densham, 1990; Craig and Moyer, 1991; Densham, 1991). The need for using such systems was derived from situations where complex spatial problems are semi-structured, and decision makers cannot define their problem or fully articulate their objectives.

In general SDSS offer a flexible, problem solving environment where the decision problem can be explored, understood and redefined; tradeoffs between multiple and conflicting objectives investigated; and priority actions set. In addition, SDSS should have the ability to support both single-user and group decision-making processes. Systems in this category are termed SDSS, and usually provide multiple-user/single-model and multiple-user/multiple-model support (Carver et al., 1996).

In 1999, we started to explore the possibility of using geodatabases to better manage EIA data and the GIS technologies including assorted shapefiles, tables and access databases. EAI and GIS data were reformatted by Local Institutions into consistent formats in the SAC system respectively. The idea was to develop geodatabases and GIS populating them with several sources.

Despite differences in geodatabases, GIS capabilities and SDSS techniques, the generic or “blanket” framework contained three major components: user interfaces, models (includes tools for generating value structure, preference modelling, multiattribute or multiobjective decision rules), geographical data analysis and management (includes DBMS/RDBMS, GIS analytical tools, simulation modelling routines, etc.).  In particular, we generated tables and thematic maps detailing the status of several data (e.g. metereological, air pollution data, land use, etc.).

We briefly review these components in the next sections.

 

3.2   Metereological and Air Pollution Data

 

The release of amount of air pollutants into the atmosphere by human activities was considered a major driver of climate change. Brownfields played an important role, both in the release of carbon through land use change and deforestation (Intergovernmental Panel on Climate Change, IPCC, 2007).For this reason several analyses such as metereological model configuration within the ENEL and Aeronautica Militare standards in Catania province on air pollution, Indoor Air Quality (IAQ) and climatic effects, collected according toDirective 2001/81/EC (NECD) were tested.Data from January 1950 to December 1991 were also used.  In particular hourly metereological data including temperature, relative humidity, and barometric pressure measured at the Catania airport were also analysed according to the European Environment Agency and National Environmental Policy Acts.

The following data were available: a) time of short term evaluation for the worst case in relation to hourly exposures and concentration of air pollution for screening evaluation, b) time of long term evaluation for emission factors. Air pollutant emission factors were representative values that attempted to relate the quantity of a pollutant released to the ambient air with an activity associated with the release of that pollutant. These factors were usually expressed as the weight of pollutant divided by a unit weight, volume, distance, or duration of the activity emitting the pollutant (e.g., kilograms of particulate emitted per megagram of coal burned). Such factors facilitated estimation of emissions from various sources of air pollution. In most cases, these factors were simply averages of all available data of acceptable quality, and were generally assumed to be representative of long-term averages. Air pollutant emission factors were representative values that attempted to relate the quantity of a pollutant released to the ambient air with an activity associated with the release of that pollutant.

The equation for the estimation of emissions, before emission reduction controls were applied, was:

 

E = A× EF .

(1)

 

and for emissions after reduction controls were applied:

 

E = A× EF × (1-ER/100) .

(2)

 

Table 2.  Emission factors

where:	Example
E	= emissions, in units of pollutant per unit of time	1
A	= activity rate, in units of weight, volume, distance or duration per unit of time	2
EF	= emission factor, in units of pollutant per unit of weight, volume, distance or duration	3
ER	= overall emission reduction efficiency, in %	4

 

 

Emission factors were used by atmospheric dispersion modelersand others to determine the amount of air pollutants being emitted from sources within industrial facilities. We also obtained average annual values from data collected by the Catania Province. These data were obtained according to the National Reference Method (NRM) based on collection of all metereological data required by the model. In particular hourly meteorologic data including temperature, relative humidity and barometric pressure measured at the Catania airport were also obtained from the Regional Climate Center. Metereological analysis were based on the collection of a set of 8760 samples (hourly values in one year such as 8760 hours in a“virtual year”). The validity of this measurement system could be affected by atmospheric conditions, particularly temperature, humidity and precipitation. In extreme cases, these effects resulted in the monitor indicating negative values. At time points close to these negative values, readings were sometimes unusually high or low. Before the initiation of this study, the hourly data were partially analysed by SAC staffs and data points that appeared invalid either by negativity or lack of continuity with neighboring values were deleted. Approximately 3% of the hourly exposure values during the study period were missing in the database. The short term scenario were based on the Emissions and Dispersion Modelling System (EDMS) and developed from 1998 to 2005as a complex source microcomputer model designed to assess the air quality impacts of proposed airport development projects. In particular the Emissions and Dispersion Modelling System (EDMS) analysed the conditions producing worst-case.

 

Table 3.  Emissions and Dispersion Modelling System (EDMS)

Case	Temperature C	Wind speed	Wind direction	Cat. stability
Worst  case	20	1	270	F

 

The climatology of the study-area should be also studied to help define the worst-case meteorologicalconditions. Further metereologicalvalues were adjusted and based on themaximumcomponent frequencyfor several years.

 

3.3   Thematic cartography

 

The objectives of the project "Capacity Building for Environmental Management in Catania airport" fitted into these priorities.

Table 4.  Fundamental trade off betweenissues for EIA

 

	Topics
1	Infrastructure transportation typologies (TabTransportation)
2	Typologies of services (TabServices)
3	Land use analysis (TabLandUse)

 

Next to strengthening project level EIA, the project aimed to conduct an SAC study. As such, the project supported Capacity Building in EIA in Catania Province.Thematic maps were analysed for the study area. As such, the SEA, which aims at investigating the cumulative impacts of the development of peculiar sectors (infrastructures, services, etc.), was structurally organised. Basically, the SAC addressed the development activities as outlined in the Master Plan of Catania City.

The analysis did not focus on scientific aspects of the establishment and operation of a GIS-database, but on the demonstration of how GIS and Remote Sensing  (RS) could be useful to support Spatial Analysis.

 

Fig. 3.Figure shows land use analysis.

 

Drawings realised land use analysis with dynamic 2D and 3D visualization and were compatible to all popular CAD drafting software and AutoCAD MAP for the analysis of RS data. We also used different softaware and in particular a new free plug-in for the analysis RS data under ECW and JPEG 2000 for AutoCAD Map.

Those data were compared with Corine Land Cover (CLC) and ESA’s global land cover map (ten times sharper than any previous global satellite map).  ESA’s global land cover map is now available to the public online from the GlobCover website. It is the highest resolution land cover map that has been completely validated ever released, it had an overall accuracy of 73% weighted by area for its 22 land cover classes. The map’s legend was developed using the United Nation Food and Agriculture Organisation’s (FAO) Land Cover Classification System (LCCS).  

Thematic cartography was also generated from RS data from Envisat’s Medium Resolution Imaging Spectrometer (MERIS) instrument working in Full Resolution Mode to provide a spatial resolution of 300 m. Data were collected between December 2004 and June 2006. The output also focuses at producing different development scenarios for the authorities and objectifying present environmental conflicts. We also tried to  develop geospatial technology (called LBS in the mobile phone world) and novel geomatic applications (such as mobile social mapping and RFID, Wi-Fi, and other Wireless applications). Much like Personal Navigation Devices (PNDs) have opened the world’s eyes to the value of GPS, LBS will open the world’s eyes to the value of geospatial technology, which in turn will spur more creative ideas and product development (Gakstatter, E, 2010).

Recent researches analysed the vital role played by Earth observation satellites and smartphones in providing the information needed by governments and policymakers to make well-informed decisions for a sustainable future in real time.

In particular prepared under the auspices of ESA on behalf of the Committee on Earth Observation Satellites (CEOS), the research provided an overview of existing Earth observation (EO) technologies for novel EIA strategies. It is the most up-to-date and comprehensive statement of governmental EO programmes available (Volker, 2008).

 

4. Results

Theresults of the research were developed in an official SAC report with thematic maps. Detailed projects were defined as pilot projects for the solution of typical problems of the Catania Airport such as metereological and air pollution data, cartographic data and thematic information. Models for alternative land use strategies in EIA were developed and have been partially implemented with the support of remote sensing analysis and wireless applications. The project proposals to implement solutions for Catania Airport  were based on the thematic information for the specialised GIS platform. Some of the project should be initiated with the financial assistance of Regional and National grants.

In particular, usingremote sensing data and in situ analysis, it was evident that the predominant land use of the study area was the urban sprawl and brownfields. The analysis showed the areas beyond the study area are a mix of suburban areas. The ironic aspect of this is that despite the high increase in the density of trasportation systems, the amount of infrastructures hasmarkedly decreased. In some areas, even taking streets into account, the air pollution dataapproaches 40%. The land use/land cover map does not distinguish suburban areas, but the thematic map quite clearly demonstrates the higher “brownfield density” in the case study. Air pollution data also confirms that the number of brownfields per acre was about 40% more than in the hinterland. This is probably due to how the data has been interpreted. The land sat image shows more infrastructures for the hinterland than in the case study. Data from the ground truthing shows that the transportation system occupies 0.4 acres and brownfields 0.6 acres.

We also tested wireless systems. Wireless Systems were satellite-based, wireless communications networks providing a robust suite of data (ground control points, geo-referencedphotos, videos, etc) to virtually any destination anywhere on the case study. As the result of GPS positioning by wireless technologies, the standard deviation was about +-2 cm in horizontal components and +- 3 to 4 cm in vertical component. It is considered that there is no remarkable difference between different types of traditional GPS receiver and smartphones.No comparison figures were gathered for transportation systems or brownfields. In conclusion, increasing transportation system does not necessarily increase the development of other typologies of infrastructures. In the case of Catania Airport, the conversion of agriculture to transportation systems has actually increased brownfields and air pollution.

 

Identifying sensitive areas early in the process through Spatial Analysis for Spatial DecisionSupport Systems, rather than waiting for traditional field testing, analysis, and reporting to be completed, was the greatest benefit to industry and local institutions.

 

5. Conclusion and future perspectives 

A key purpose of the EIA and Spatial analysis was to use the environmental information that are gathered to contribute to the evolution of the design of the development, with the objectives of reducing any adverse environmental effects that could be caused by the development and increasing its positive effects with the support of traditional and novel geomatic technologies. This study included the collaboration and review of all publicity available and relevant spatial information including previous work in the field of Remote Sensing analysis (such as brownfield analysis and increase of pollution transmitted, etc.) together with some consultation with key stakeholders and site visits for the construction and permanent land use change. This information allowed the identification of potentially sensitive and valued spatial data at an early stage in the design process. This information has been used to identify likely effects from the developers proposals and measures that could be adopted to avoid and minimise potential effects. The information may be used to take into account spatial issues in subsequent interaction of Catania International Airport’s draft airport master plan implementing National and International projects regarding Global Navigation Satellite Systems (GNSS) and Wireless applications, along with improving mobile devices and capabilities. Further RS Support Systems, such as instruments aboard ESA’s Envisat may allowed us to observe various features of metereological data, including cloud structure, wind and wave fields, sea-surface cloud structure, land and sea-surface temperature and sea-surface height. Envisat’s Medium Resolution Imaging Spectrometer (MERIS) optical instrument acquired images working in Full Resolution mode.

On the other hand, the record-holding Meteosat-6 is running low on fuel and destined to be re-orbited around the end of 2010. The excellence of these weather satellites illustrates Europe’s role in providing the essential data to monitor and understand the dynamics of Earth’s atmosphere and improve everyday life. Following on from the first two second-generation satellites, the Meteosat programme is set to continue with MSG-3, which will be launched mid-2012 on an Ariane 5 and followed by MSG-4 in 2014. In October 2006, the Meteosat weather satellites in geostationary orbit were joined by the first of a brand new generation of polar-orbiting meteorological satellites with the launch of MetOp-A. The MetOp series is Europe’s contribution to a new cooperative venture with the US providing data to monitor climate and improve weather forecasting. MetOp is a series of three satellites to be launched sequentially to deliver data until at least 2021.

Despite the fact that Spatial Decision Support Systems and technologies have been successfully applied to “real-world” problem solving, relatively novel full-featured SDSS have been developed, implemented, and evaluated in Sicily. Rapid growth of these systems has occurred in the past decade; however, the field of SDSS is far from mature. Continued changes in computer hardware, software technology and geomatic applications are fundamentally altering the way that decision makers, stakeholders, policy makers, and analysts interact with Spatial data analysis. In a systematic way the complex topics and techniques can be assembled under Geomatics namely, Geodesy, Cartography, Photogrammetry, Remote Sensing (RS), Informatics, Acquisition Systems, Global Positioning Systems (GPS), Digital Image Processing (DIP), Geographic Information Systems (GIS), Decision Support Systems, and WebGIS and more Telecommunications, Geo-spatial Information, Information Technologies. This field of research is mainly influenced by an interdisciplinary approach (geoscientists and geographers, engineers, architects, computer scientists, urban planners, specialists in GIS, remote sensing, forestry, agricultural science, soil science geometry, environmental scientists, civil protection scientists and managers). Spatial analysis and EIAapplications are moving to a more exploratory, interactive emphasis with new decision analysis tools; at the same time GIS prototypes are moving to a wide range of spatial decision support with exciting new applications.

On large projects, this labour intensive effort of EIA analysis is timely and costly. If novel GIS models are used at this stage (e.g. open sources and low cost wireless applications), the project can get a feeling for sensitive areas associated with a modification and select a preferred modification without costly, large-scale analysis.

 

Acknowledgments

 

Thanks to Staff in Catania Province, to SAC, ENAV team (Centre for EIA – Catania Airport) and ESA for providing raw data and Spatial Analysis data. Part of the collaboration with the SAC team started in 2000 during the Master Course in History and Analysis of the Territory at Catania University.

I also appreciate the help of Trimble Sicilia, CGT srl and Dott. Geol. N. Costa for technologies and data processing and V. Clark (NAVY, USA Sigonella) for reading the draft of my manuscript.

 

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