Geographic Information Systems (GIS)

GIS stands for Geographic Information System, which is a computer-based system that enables the compilation, visualization, management, storage, and analysis of digital geographic information. The system is comprised of computer hardware and software, geographic data, procedures or techniques, and skilled personnel to operate it all and ensure its smooth running.

GIS is based on layers of data. Different layers depicting different phenomena (such as streets, land parcels, buildings, land cover, etc.) can be overlaid on top of each other to produce meaningful analyses and visualizations. Two main types of GIS data exist: vector and raster. Vector data, composed of points, lines, and polygons, is best suited for representing features with known and definable exact locations and boundaries; in other words, discrete objects. Every individual point in a vector layer has a defined XY coordinate associated with it. Raster data, on the other hand, uses a pixel-based grid where every individual pixel or cell has a defined value or class associated with it. As opposed to vectors, rasters are suited for representing data that varies continuously, such as elevation, precipitation, temperature, or groundwater levels. If this concept is tricky to understand, please refer to this excellent explainer from GISGeography.

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GIS is used at all levels of government—city, county, state, national, and even international level. It is also used extensively by private industry, including by household names such as Uber, Starbucks, and Walgreens. Why? The answer is due to the significant benefits that GIS, and geographic analysis in general, provide:

1. More efficient decision-making

GIS provides efficient ways in deciding where to locate facilities or services. It can assess the suitability of a location based on various factors using spatial data. For example, a grocery store chain may assess various factors such as household income, population density, property crime rates, proximity to parking space, and others to assess the best place to build a store in an urban area.

2. Improved communication of information

The ability to create highly detailed and informative maps has become even more impactful with the integration of GIS into the Internet; interactive web maps, connected and integrated to a GIS infrastructure, have become a key way for governments and NGOs to communicate crucial information to the public in a massively accessible way. For example, during the COVID-19 pandemic, Johns Hopkins University’s groundbreaking COVID dashboard (featuring interactive GIS-powered maps) was one of the most important sources of information for billions of people during a difficult and uncertain time.

3. Cost efficiency

The comprehensive and multidisciplinary nature of GIS helps cut down on the cost of acquiring various tools or functions due to the sheer amount of different analyses it can run. For example, a civil engineering company can do basic transportation planning, utility mapping, and groundwater management workflows in ArcGIS without having to purchase a separate software package for each task.

4. Better data management

GIS offers a relatively easy way of manipulating, managing, and storing datasets. For example, data can be edited, queried, integrated, or merged, copied, categorized, and even converted into other formats within GIS without the need of separate, third-party software. Modern, cloud-based enterprise GIS ecosystems can also support collaboration and integration across desktop and mobile, allowing for both spatial and non-spatial data to be shared practically instantly across an entire organization. This removes the need to manually share data between stakeholders in a project through a separate cloud storage service or email.

• Agriculture: conduct capability / suitability analysis for certain crops.
• Archaeology: map and also find potential archeological sites.
• Biology & Wildlife: determine or predict potential habitats of certain plant and animal species.
• Criminal Justice: conduct crime hot-spot analysis.
• Engineering: determine best locations for building facilities.
• Public health: analyze spatial patterns of a disease outbreak or a health issue.
• History: map or reconstruct historical events.
• Marketing: determine coverage areas of businesses, map market segments and estimate market shares and sales potential.
• Mass Communication & Journalism: analyze geographic patterns of social media data.
• Political Science: assess voting patterns and make predictions.
• Sociology: analyze social inequalities in the distribution of social services and facilities such as health centers and food banks.

Remote sensing involves the acquisition of information about an object, location, or phenomenon without making physical contact with it. In layman's terms, it involves using sensors (acquired by satellites, planes, or drones) to learn about the Earth by studying the electromagnetic energy that is reflected or emitted from the target. This is captured in imagery or other formats (such as LiDAR point clouds), where it can then be analyzed by humans or machines to learn more about what is going on in the targeted location.

Remote sensing is considered a different sub-field of geography than GIS but it is closely related and uses many similar methods and software packages. Like GIS, remote sensing is an extremely interdisciplinary field, combining aspects of the following: 

• Physics: building and operating satellite sensors effectively requires knowledge of light, optics, and electromagnetic energy
• Computer Science: various algorithms are used to process imagery, extract and classify features, and managing large amounts of data. Additionally, the software packages (such as ERDAS) require significant software engineering knowledge to develop. 
• Statistics: statistical methods are used to perform the analytical processes to extract information from the images. 
• Math: various common tasks, such as image filtering, enhancement, or classification, require the use of matrices, geometry, trigonometry, etc.

Remote sensing has a wide variety of applications, especially in the environmental and earth sciences. Examples include: monitoring wildfires, quantifying deforestation and glacier retreat, analyzing vegetation health, and monitoring soil moisture content for cropland. 

Texas State community members have access to ERDAS Imagine, an industry-leading remote sensing. Click here for more information.