In Chapter One, we examined GIS (geographic information systems) and GIScience, setting the stage for understanding how spatial (where data occurs) and non-spatial (information about that location) data combine in GIS to explore data distribution and solve spatial problems. In Chapter Two, we shifted our focus to geodesy (the science of measuring the Earth), geographic coordinate systems (a global "address" system for labeling locations on the Earth's surface), and projected coordinate systems (flat maps that allow us to measure in linear units vs. angular units but come at the cost of distortion). This chapter brings together vital concepts as we explore three key spatial data models: vector data, raster data, and data tables. Understanding these models is crucial for harnessing the power of GIS software. Just as a chef needs ingredients to create a dish, GIS software requires data to produce meaningful outputs, such as maps of the best mac 'n' cheese restaurants in the city.
Within the GIS framework, this chapter focuses on representation, exploring how we model the real world in a scaled-down, digital format that can be analyzed and downloaded as needed. Throughout the semester, we will categorize all GIS data into three primary data models: vector, raster, and data tables. A data model in GIS refers to the fundamental way spatial data is structured and stored, defining how geographic features, attributes, and relationships are represented in digital form. All three models are crucial for solving spatial problems. We will give each one equal emphasis, reflecting on how GIS integrates spatial and non-spatial elements.
These primary data models are deeply interconnected; utilizing one effectively often involves insights from the others. When you open a spatial file, it consists of multiple smaller files, including a table with measurements and descriptive data linked to specific locations. Vector files (map features) are often created by analyzing aerial images (raster data), which also serve as the background for completed maps. Additional non-spatial data is typically stored in tables, which are then connected to vector files. Raster images, in turn, can be paired with data tables to solve spatial problems.
In this chapter, we will examine vector files, raster files, and data tables, exploring their use in GIS, recognizing differences, reviewing unique models, and understanding their interactions. We will conclude with an overview of attribute tables and their vital role in GIS. In Chapters Four and Five, we will explore ArcGIS Pro, the most widely used GIS software, and delve deeper into attribute tables. For now, let's define and explore examples of spatial data, which are essential for understanding GIS.