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GIS-based Spatial Analysis for the

Geosciences: Geospatial Correlative

Integration

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Advantages

The geographic location of each cell is implied by its position in the cell matrix. Accordingly, other than an origin point, e.g. bottom left corner, no geographic coordinates are stored.
Due to the nature of the data storage technique data analysis is usually easy to program and quick to perform.
The inherent nature of raster maps, e.g. one attribute maps, is ideally suited for mathematical modeling and quantitative analysis.
Discrete data, e.g. forestry stands, is accommodated equally well as continuous data, e.g. elevation data, and facilitates the integrating of the two data types.
Grid-cell systems are very compatible with raster-based output devices, e.g. electrostatic plotters, graphic terminals.

Disadvantages

The cell size determines the resolution at which the data is represented.;
It is especially difficult to adequately represent linear features depending on the cell resolution. Accordingly, network linkages are difficult to establish.
Processing of associated attribute data may be cumbersome if large amounts of data exists. Raster maps inherently reflect only one attribute or characteristic for an area.
Since most input data is in vector form, data must undergo vector-to-raster conversion. Besides increased processing requirements this may introduce data integrity concerns due to generalization and choice of inappropriate cell size.
Most output maps from grid-cell systems do not conform to high-quality cartographic needs
There are a number of ways of forcing a computer to store and reference the individual grid cell values, their attributes, coverage names and legends.

2.3 Application of GIS

Today, GIS is used not only in the geosciences but also in environmental, civil and urban, agricultural, forestry, business, military, government, and educational research and applications. There are no limitations in the use of GIS, and it is expanding into new areas. Here, we confine our focus to applications in the geosciences.

2.3.1 Geological Mapping

One of the most fundamental GIS applications is geologic mapping. In geologic mapping, it is often necessary to bring various existing geologic maps, often in different scales, to one uniform scale. This has traditionally been done using graph sheets or a reflecting projector, which is extremely time consuming as it requires the retracing of maps to the desired scale, often compromising quality. With the help of GIS, maps of any scale can be scanned, georeferenced, and reproduced at any scale and thereby brought to one scale. Additional information can be collected either by field investigation or remote sensing techniques to prepare a final updated geologic map. For example, the Indian Institute of Remote Sensing, transformed published geologic maps at 1:250,000 and 1:50,000 scales from different sources to a single scale of 1:25,000. All of the maps were then compared, and a final composite map was prepared at a 1:25,000 scale. The final map was later updated using merged Indian Remote Sensing Satellite (IRS) Linear Imaging Self-scanning Sensor (LISS) III and Panchromatic Sensor (PAN) imagery at the 1:25,000 scale and was supported by ground investigation.

A geologic map is a specialized map that displays the geologic features of an area. Different colors are used to show rock formations, canyons, valleys, plains, and other features of the area being mapped. Lines are used in these maps to convey characteristics of the land. These lines help in estimating the height of terrain structures. Height is displayed relative to sea level. The lines in geologic maps may be followed by a number indicating the incline of the structures.

Before the entry of GIS into the field of geologic mapping, it was very difficult to map any area with high precision. Numerous techniques, which involved multiple complex devices and thereby multiple calculations, were used to obtain precise data.

The following sections offer brief summaries of the specialized use of GIS in geologic mapping and how application of GIS to geologic mapping results in accurate measurements that are helpful in several fields. Figure 2-9 shows an example of a geologic map of an area in Nepal.

Figure 2-9. Geology map of Nepal (Upreti and Le Fort, 1999)

Geologic features are dependent on space and time, which a GIS is capable of defining. The signals from satellites allow the GIS to read information in terms of longitude, latitude, and elevation (compared to sea level). This information helps in determining all three of the planes that guide GIS tools in creating a three-dimensional (3-D) image of the area under survey, such as a geologic map (Figure 2-10).

Figure 2-10. 3D geological map (Jachens et al., 2001)

The satellite signals also include information about the time at which the satellite released its signals, clock redundancy of the transmitters in the satellites, and coefficients of error through the speed of the signal in space as well in the different layers of the atmosphere. On the basis of these four factors, surveyors can create accurate geologic maps of the area under survey.

Although old geologic methods (based on multivariate statistics) are still in use in some countries, GIS is now the most preferred method because it is cost-effective and offers more accurate data, thereby easing the scaling process when studying geologic maps. GIS helps in the scanning, referencing, and reproduction of older maps at any desired scale. Using GIS, several archeological geologic maps (having different scales) were combined into a single map (with single scaling) with even more accuracy. Thus, the valuable time of scientists, engineers, and researchers who needed to study the area was saved.

2.3.2 Groundwater

GIS can be used for multiple applications related to the occurrence and movement of groundwater. One of the main benefits of using GIS with groundwater modeling programs is that simulation results can be displayed geo-referenced, allowing further analysis and display of topological relationships between the model and other spatial features.

Groundwater is a dynamic system formed by combinations and interactions of various factors, including weather, hydrology, surface topography, and geologic characteristics (Park et al., 2000). To understand aquifer productivity and composite mechanisms in groundwater systems, the physical characteristics of the related factors that configure the system should be identified. Without field surveys it is not possible to directly understand the distribution of groundwater using remote sensing and GIS technologies; however, groundwater potential can be inferred from surface attributes such as geology, soil texture, land use, and drainage systems (Todd, 1980; Jha and Peiffer, 2006).

GIS and remote sensing technologies have great potential for use in groundwater analyses. Many studies have applied these techniques along with thematic layers such as those representing the geomorphology, drainage patterns, lineaments, lithology, and soils (e.g., Jaiswal et al., 2003; Solomon and Quiel, 2006; Kim et al., 2010; Jasmin and Mallikarjuna, 2011).

Some studies have used personal judgments or local information to assign weights to different thematic layers and their features (Madrucci et al., 2008; Pradhan, 2009; Yeh et al., 2009; Dar et al., 2010; Saud, 2010; Singh et al., 2011). Other studies have applied probabilistic models, such as frequency ratio and weight of evidence models, for groundwater potential mapping (Corsini et al., 2009; Oh et al., 2011; Lee et al., 2012b). Oh et al. (2011) and Lee et al. (2012b) applied frequency ratio and weight of evidence models for groundwater potential mapping and sensitivity analysis in the same area. More sophisticated assessments have used numerical modeling, decision trees, fuzzy logic, and analytic hierarchy process analysis (Srivastava and Bhattacharya, 2006; Vijay et al., 2007; Murthy and Mamo, 2009; Chenini and Mammou, 2010; Kiesel at al., 2010). Some researchers have also integrated GIS, remote sensing, and geophysical surveys to derive additional thematic layers of various parameters, such as resistivity, aquifer thickness, and fault maps (Israil et al., 2006; Srivastava and Bhattacharya, 2006; Ranganai and Ebinger, 2008; Kumar et al., 2009).

Several examples of the application of GIS and remote sensing technologies illustrate their usefulness in groundwater potential analyses. Figures 2-11 and 2-12 present thematic maps and the resulting map of a GIS-based model that considered local conditions/variations in mapping groundwater prospects in India (Jaiswal et al., 2003). In order to ensure "Health for All," the government of India has launched many programs to provide potable drinking water to every settlement in the country, including rural villages with no water source and those with water-quality problems. To reach this goal, groundwater resources and their location relative to settlements must be understood. Thus, GIS maps were generated by overlaying village boundary maps on the map of groundwater prospect zones.

Figure 2-11. Thematic maps prepared using remote sensing and conventional data: (a) geological map; (b) landforms map; (c) soil type map; (d) slope map; (e) drainage density map; and (f) land use/land cover map (Jaiswal et al., 2003)

Figure 2-12. Village-wise groundwater prospect zones (Jaiswal et al., 2003)

Saud (2010) presented a method for integrating the physical and anthropogenic factors governing groundwater storage in the Wadi Aurnah Basin of Saudi Arabia. The resulting map-format spatial data (Figure 2-13) indicated that 12–15% of the Wadi Aurnah Basin is suitable for groundwater storage and that this portion is concentrated mainly in the eastern, mountainous region (Figure 2-14).