GIS Analysis

 GIS technology has the sophistication to go beyond mapping and serve a larger purpose of a data management and analysis tool. GIS technology aggregates the spatial data you need to make good decisions for your organization.  GIS can integrate georeferenced imagery as data layers or themes and link them to other data sets to produce geospatial representations of data. These geographical pictures not only depict geographic boundaries but also offer special insight to researchers across disciplines such as health, economics, agriculture, and transportation. By using GIS, our researchers are able to establish the patterns and interactions between health, environmental, and socio-economic variables with real world geographic locations.  GIS technology has greatly advanced in the last 30 years, and is capable of performing sophisticated analysis of data.  GIS analysis can answer questions like:

  •  Where are things in geographic space?

  •  Mapping variations in amount: least and most

  •  Mapping density

  •  Finding what is inside

  •  Finding what is nearby

  •  Mapping change

Good GIS applications use data analysis to benefit municipal, county and state governments as well as commercial industry.  Some examples are:

Municipal authorities, Central and state governments can use GIS to answer important questions such as:

  • Which roads should we plan to resurface this year?

  • Which lots are vacant?

  • How should we rezone?

  • How much road salt should we budget for this winter?

Real estate developers can use GIS to make informed decisions about where to build a development, office complex or mall using analysis on:

  • Population projections

  • Demographic trends

  • Natural resources

Retail can use GIS analysis to find an optimal new store location.  Analysis of GIS data can yield a desirable demographic with respect to:

  • Geographic distance

  • Appropriate zoning

  • Existing infrastructure

Analytical Approaches

Commercially available GIS application packages offer a wide range of analytical approaches.  These include:

  1. 1. Neighborhood Analysis evaluates the characteristics of an area surrounding a specific location.  The analysis of topographic features, e.g. the relief of the landscape, is normally categorized as being a neighbourhood operation. This involves a variety of point interpolation techniques including slope and aspect calculations, contour generation, etc.

    a.       Elevation data usually takes the form of irregular or regular spaced points. Irregularly space points are stored in a Triangular Irregular Network (TIN).

    b.      An alternative in storing elevation data is the regular point Digital Elevation Model (DEM). The term DEM usually refers to a grid of regularly space elevation points. These points are usually stored with a raster data model. Most GIS software offerings provide three dimensional analysis capabilities in a separate module of the software.

    c.       Without doubt the most common neighborhood function is buffering. Buffering involves the ability to create distance buffers around selected features, be it points, lines, or areas. Buffers are created as polygons because they represent an area around a feature. Buffering is also referred to as corridor or zone generation with the raster data model.

  2. 2. Connectivity Analysis  The distinguishing feature of connectivity operations is that they use functions that accumulate values over an area being traversed. Most often these include the analysis of surfaces and networks. Connectivity functions include proximity analysis, network analysis, spread functions, and three dimensional surface analysis such as visibility and perspective viewing.

  3. 3. Proximity analysis 3. Proximity analysis techniques are primarily concerned with the proximity of one feature to another. Usually proximity is defined as the ability to identify any feature that is near any other feature based on location, attribute value, or a specific distance. A simple example is identifying all the forest lands that are within 100 metres of a gravel road, but not necessarily adjacent to it.

  4. 4. Network analysis is a widely used analysis technique used for route optimization. Two example network analysis techniques are the allocation of values to selected features within the network to determine capacity zones, and the determination of shortest path between connected points or nodes within the network based on attribute values. Attribute values may be as simple as minimal distance, or more complex involving a model using several attributes defining rate of flow, impedance, and cost.

  5. 5. Three dimensional analysis involves a range of different capabilities. The most utilized is the generation of perspective surfaces. Perspective surfaces are usually represented by a wire frame diagram reflecting profiles of the landscape, e.g. every 100 metres. These profiles viewed together, with the removal of hidden lines, provide a three dimensional view. Most GIS software packages offer 3-D capabilities in a separate module. Several other functions are normally available. These include the following functions:

  • User definable vertical exaggeration, viewing azimuth, and elevation angle;

  • Identification of viewsheds, e.g. seen versus unseen areas;

  •  The draping of features, e.g. point, lines, and shaded polygons onto the perspective surface;

  •  Generation of shaded relief models simulating illumination;

  •  Generation of cross section profiles;

  •  Presentation of symbology on the 3-D surface; and

  •  Line of sight perspective views from user defined viewpoints.

Practical Steps to Performing GIS Analysis

1. Frame the Question:

        Where are endangered ecosystems in Delaware County?

        Where are potential recreational trail corridors in Delaware County?

        How can we understand the tangible state of environmental justice in Delaware County OH?

        Who is your audience? what is your final goal? What is your final product?

2. Understand your Data

What is the context of your question? who are the experts? literature, people

        What do you have to know about the context of the question to answer it?

        What is an endangered ecosystem? what are specific examples?

        What are the goals of recreational trails? what do they connect?

        What is Environmental Justice and what kind of data helps us understand it?

        What or who can help you to understand the issue: literature, people

3. Choose a Method

        What data is available to help answer your question? cost? compatibility?

        What data do you have to generate yourself? easy vs. difficult vs impossible

4. Process the Data: specific analysis

        Example: Generate endangered areas by comparing areas defined as important ecosystems to their closeness to recent development

        Example: Generate potential trails by generating important points and areas to connect; and determining feasible paths between those points; relate potential trails to property ownership and other factors

5. Look at the Results

        Generate a map (with a database) and use it to present results

        Map of endangered ecosystems in Uttarakhand: distribute to??

        Map of potential trails in Corbett National Park: planners, bike clubs, etc.

Notes & Handouts

The Himalayas

Kumaon Himalayas

Askot Basemetals

University

   


This website is hosted by

S. Farooq

Department of Geology

Aligarh Muslim University, Aligarh - 202 002 (India)

Phone: 91-571-2721150

email: farooq.amu@gmail.com