4.6.5. Spatial Analysis

The strength of the GIS lies in its analytical capabilities. What distinguish the GIS from other information systems are its spatial analysis functions. The analysis functions use the spatial and non-spatial attributes in the database to answer questions about the real world. Geographic analysis facilitates the study of real-world processes by developing and applying models. Such models provide the underlying trends in geographic data and thus, make new possibilities available.

GIS, or Geographic Information Systems, are powerful tools that allow users to analyze geographical and spatial data. The analysis functions in GIS help to answer important questions about our world, such as understanding trends in data related to location. By developing models, GIS can show us patterns and relationships within the data, allowing for better decision-making based on geographical information.

Imagine a city planner who wants to know where to build new parks. Using GIS, they can analyze existing data about population density, current park locations, and pollution levels. The GIS can show them trends and areas that would benefit most from new parks, helping them make informed decisions.

The objective of geographic analysis is to transform data into useful information to satisfy the requirements of the decision-makers. For example, GIS may effectively be used to predict future trends over space and time related to a variety of phenomena. However, before undertaking any GIS-based analysis, one needs to identify the problem and define the purpose of the analysis. It requires step-by-step procedures to arrive at the conclusions.

Before using GIS for analysis, it's crucial to determine what problem you're trying to solve. For instance, predicting future trends might involve examining how urban growth is influenced by population changes. This process involves clear objectives and a series of steps to ensure accurate results, making it essential for decision-makers.

Consider a healthcare provider wanting to plan a new clinic. They must first identify the issue, such as access to healthcare in underserved areas. By defining their purpose and following a structured analysis process using GIS, they can determine the best locations for new clinics to serve those in need.

The following spatial analysis operation may be undertaken using GIS: (i) Overlay analysis (ii) Buffer analysis (iii) Network analysis (iv) Digital Terrain Model. However, under the constraints of time and space, only the overlay and buffer analysis operations will be dealt herewith.

Spatial analysis operations in GIS include techniques like overlay and buffer analysis. Overlay analysis allows users to combine multiple layers of information to create a new map, revealing relationships between data sets. Buffer analysis creates zones around specific geographic features to analyze their impact on surrounding areas.

Think of overlay analysis like layering different transparencies in an art project. Each layer shows different information—like roads, schools, and parks—allowing a clearer picture of how they interact. Buffer analysis could be visualized as drawing circles around trees to see which homes are affected by shade or falling leaves.

The hallmark of GIS is overlay operations. An integration of multiple layers of maps using overlay operations is an important analysis function. In other words, GIS makes it possible to overlay two or more thematic layers of maps of the same area to obtain a new map layer. The overlay operations of a GIS are similar to the sieve mapping, i.e., the overlaying of tracing of maps on a light table to make comparisons and obtain an output map.

Overlay analysis in GIS involves combining different data layers to produce a comprehensive view of the area. This technique is essential for understanding how various elements relate to each other spatially. For example, overlaying land-use data with environmental impact assessments helps in making effective land management decisions.

Imagine you are painting a landscape, where each color represents a different element, like trees, roads, and rivers. By layering these colors carefully, you create a cohesive picture of the environment. Overlay analysis in GIS works the same way, allowing various data layers to reveal complex interactions in geography.

Buffer operation is another important spatial analysis function in GIS. A buffer of a certain specified distance can be created along any point, line, or area feature. It is useful in locating the areas/population benefitted or denied of the facilities and services, such as hospitals, medical stores, post office, asphalt roads, regional parks, etc.

Buffer operations help GIS users create zones around geographic features. By establishing a specific distance from these features, analysts can determine which areas are affected by them. For instance, a buffer zone can indicate which populations have easy access to a hospital based on their distance.

Imagine you live near a popular café. If you draw a circle around it, everything within that circle might be considered 'close' to the café, meaning those people are likely to visit more frequently. In GIS, buffer analysis uses this concept to measure the impact of services like hospitals or schools on nearby populations.

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