Suitability analysis is the process and procedure used to establish the suitability of a system. In GIS it is used to determine the appropriateness of a given area for a particular use. One of the most useful application of GIS for planning and management is the land use suitability mapping and analysis (McHarg,1969; Brail and Klosterman, 2001; Collin et al.,2001). Land use suitability analysis amis at identifying the most appropriate spatial pattern for future land uses according to specify requirements, preferences, or predictors of some activity (Hopkins,1997; Collins et al.,2001). The GIS based land use suitability analysis has been applied in a wide variety of situations including ecological approaches for defining land suitability/habitant for animals and plant species(Pereira and Duckstein,1993; Store and Kangas,2001), geological favorability (Bonham-Carter,1994), suitability of land for agricultural activities (Cambell et al.,1992;Kalogirou,2002),landscape evaluation and planning (Miller et al., 1998), environmental impact assessment (Moreno and Seigel, 1988), selecting the best site for the public and private sector facilities (Eastman et al., 1993;Church, 2002), and regional planning (Janssen and Rietveld,1990).
GIS based land use suitability analysis:
The GIS based approaches to land use suitability analysis have their roots in the applications of hand drawn overlay techniques used by American landscape architects in the late nineteenth and early 20th century(Steinitz et al., 1976;Collins et al., 2001). The overlay procedures play a central role in many GIS applications (O’Sullivan and Unwin, 2003) including techniques that are in the forefront of the advances in the land-use suitability analysis such as: multicriteria decision analysis (MCDA) (Diamond and Wright, 1988; Carver, 1991; Malczewski, 1999; Thill, 1999), artiﬁcial intelligence (AI) (geocomputation) methods (Sui, 1993; Zhou and Civco, 1996; Ligtenberg et al., 2001; Xiao et al., 2002), visualization methods (Jankowski et al., 2001), and Web-GIS (Carver and Peckham, 1999; Zhu and Dale, 2001; Rinner and Malczewski, 2003). Over the last forty years or so GIS-based land-use suitability techniques have increasingly become integral components of urban, regional and environmental planning activities (Brail and Klosterman, 2001; Collins et al., 2001). There are several fundamental trends in computer supported approaches to land-use suitability analysis.
1. Computer assisted overlay mapping
2. Multicriteria evaluation methods, and
3. AI( soft computing or geocomputation) methods
1. Computer –assisted overlay mapping:
The computer-assisted overlay techniques were developed as a response to the manual method’s limitations of mapping and combining large datasets (MacDougall, 1975;Steinitz et al., 1976). Rather than manually mapping the values of a series of suitability factors in gray—or color scales, the models are stored in numerical form as matrices in the computer. The individual suitability maps can then be analyzed and combined to obtain an overall suitability map. The development of computer-assisted mapping techniques in the Harvard Laboratory (see Chapter 2) was instrumental for advancing the land-use suitability analysis (Lyle and Stutz, 1983). The Harvard’s SYMAP and GRID systems included a set of modules allowing for performing land-use suitability analysis. One of the early applications the Harvard’s systems focused on evaluating a proposed ﬂood-control reservoir and parkway for their suitability for recreation and other land uses (Murray et al.,1971). Miller and Niemann (1972) employed GRID-based overlay analysis for developing alternative interstate corridors. Similarly, Turner and Miles (1971) proposed a computer system for identifying the transportation corridor selection based on the suitability map overlay technique. Massam (1980) provides an overview of the earlier applications ofcomputer-assisted overlay mapping approaches to the corridor location analysis. Lyle andStutz (1983) demonstrated the application the land suitability analysis for developing an urban land use plan.
2. Multicriteria decision making methods:
The integration of MCDM techniques with GIS has considerably advanced the conventional map overlay approaches to the land-use suitability analysis (Carver, 1991; Banai, 1993; Eastman, 1997; Malczewski, 1999; Thill, 1999). GIS-based MCDA can be thought of as a process that combines and transforms spatial and aspatial data (input) into a resultant decision (output). The MCDM procedures (or decision rules) deﬁne a relationship between the input maps and the output map. The procedures involve the utilization of geographical data, the decision maker’s preferences and the manipulation of the data and preferences according to speciﬁed decision rules. Accordingly, two considerations are of critical importance for spatial MCDA: (i) the GIS capabilities of data acquisition, storage, retrieval, manipulation and analysis, and (ii) the MCDM capabilities for combining the geographical data and the decision maker’s preferences into unidimensional values of alternative decisions. A number of multicriteria decision rules have been implemented in the GIS environment for tackling land-use suitability problems. The decision rules can be classiﬁed into multiobjective and multiattribute decision making methods (Malczewski, 1999). The multiobjective approaches are mathematical programming model oriented methods, while multiattribute decision making methods are dataoriented. Multiattribute techniques are also referred to as the discrete methods becausethey assume that the number of alternatives (plans) is given explicitly, while in the multiobjective methods the alternatives must be generated (they are identiﬁed by solving a multiobjective mathematical programming problem).
3. Artificial intelligence methods:
Recent developments in spatial analysis show that AI (computational intelligence) offers new opportunities to the land-use suitability analysis and planning (Openshaw and Abrahart, 2000).
Selection of land fill site in Bharatpur Municipality:
The role of GIS in solid waste management is very large as many aspects of its planning and operations are highly dependent on spatial data. Using ArcGIS software solid waste departments can enhance
1. Landfill management
2. Trash collection
3. Environmental monitoring
5. Asset management
GIS is a tool that not only reduce time and cost of site selection but also provides a digital data back up for future monitoring programme of the site
Bharatpur Municipality covers an area of 77891317.3774 sq. meters with total population of 86208, total cultivated land 44264660.830 sq.meters and total built up area 3904058.729 sq.meters.
Suitable criteria for selection of landfill site:
Following criteria are made
1. 300 meters away from the main road
2. 300 meters away from the water bodies
3. Located in area not crossed by major roads
4. Not located in areas of active agricultural land or near land under development and
5. 1.5 kilometers away from the nearest population centers
GIS Tools used for analysis:
• Buffer : Buffer zone of various elements like road, water bodies, etc. was created according to the criteria mentioned above
• Union : Different Buffer zone were combined using Union tool
• Merge : Different categories of water bodies such as pond, rivers , rivuletes etc. were merged in a single element for analysis.
The suitable location was identified and shown in the map. The area of land suitable for landfill site is 3247097.987sq. meters.
Allen, A.R., Dillon, A.M. & O’Brien, M. 1997. Approaches to landfill site selection in Ireland. In: Marinos, P.G., Koukis, G.C., Tsiambaos, G.C., Stournaras, G.C. (Eds.), Engineering Geology and the Environment. Balkema, Rotterdam, pp 1569-1574.
Ball, J., 2002. Towards a methodology for mapping regions for sustainability using PPGIS. Progress in Planning 58 (2), 81–140