Select a session from the dropdown below to learn more:
A Geographic Information System is a tool used for building, managing, analyzing, and displaying geographic data. A map created using a GIS contains layers, which are collections of related geographic data. Based upon the purpose of the map you are creating, you can choose what layers to add and display.
Vector layers contain features, or geographic objects. For example, a layer of cities will contain different cities, or a layer of rivers will contain information on many different rivers. Geographic features can be presented in three ways- points, lines, or polygons. Points are generally used to represent small features on large maps, such as cities on a map of Europe. Lines are used to represent narrow features, such as rivers or highways. Polygons typically represent features with boundaries- such as countries or lakes. Data in point, line, or polygon form are collectively known as vector data.
Aside from vector data, layers in ArcMap can also come in raster format. Raster layers are not collections of geographic features, like vectors, but rather consist of continuous data (data that does not have a distinct ‘shape’- such as elevation, temperature, or rainfall). A raster is a matrix of cells, similar to the individual pixels in a digital photograph. Each cell represents a certain area on the ground, and contains the information for that location.
1. Explore the ArcGIS platform
2. Identify basic tools and their functions
3. Learn layer symbology
4. Create a high-quality map for publication
This lab will examine the importance of map projections and coordinate systems. We will explore how different global map projections change the size and distance of the continents, and then apply a projection to a map of the Democratic Republic of the Congo. The lab will also show how to add a tabular dataset with XY coordinates to ArcMap, and then how to export the layer to Google Earth for interactive viewing.
1. Understanding projections
2. Adding XY data
3. Exporting to Google Earth
In Lab 3 we will explore several different sources of data and practice downloading a tabular dataset for use in ArcMap. The lab discusses how to symbolize data on a map through different classifications (or the methods used to group different ranges of a dataset) according to the type of data that is being displayed.
1. Download Data
2. Perform a Table Join
3. Thematic Mapping
4. Data Symbology and Classifications
In this exercise, we will determine which types of land cover are most susceptible to fire in Ethiopia. We will use various geoprocessing tools to calculate the density of fire events (the number of fire events occurring per square kilometer). The final deliverable will be a map comparing land cover type to fire events that have occurred in Ethiopia, as well as a pie chart that shows the density of fire events for each land cover type.
1. Become familiar with geoprocessing techniques and tools
2. Calculate density values
3. Create a chart
In this lab, you will be working in ArcCatalog to manage multiple datasets. We will explore the program itself, discuss the importance of data organization, create a sample geodatabase, and learn how to edit metadata.
1. Become familiar with ArcCatalog and the ArcToolbox
2. Understand geodatabases
3. Learn about metadata and practice editing the information
In this exercise, we will learn how to create new, blank shapefiles, or templates, that can be edited to create new data. We will use satellite imagery to digitize (or essentially trace) specific features to create vector data. This is a useful technique in situations where data is unavailable or needs to be modified. In order to digitize in ArcMap, we will use the Editor Toolbar.
1. Creating a shapefile template in Arc Catalog
2. Exploring the Editor toolbar to digitize imagery
The goal of these two exercises is to become familiar with raster data and processing. In the first exercise, you have been asked to assess the effects of sea level rise on both the population and livelihood of Bangladesh. To do so, you will work with three raster datasets: A land cover classification derived from SPOT imagery, A Digital Elevation Model (DEM), and a raster of population count for the year 2015 created by WorldPop.
1. Become familiar with advanced spatial analysis tools
2. Experiment with raster tools and processing
3. Determine the answers to specific analytical questions