Week 02 - Making and Collecting Data
Week 02 shifts the course from working with existing spatial data toward creating it. This is an important transition. A great deal of GIS work is not just analyzing data someone else prepared. It is deciding what should count as data in the first place, how it should be structured, how accurately it should be captured, and how to document it so other people can use it later.
The Week 02 labs approach data creation from four different angles:
- Georeferencing turns a scanned historical map into usable spatial data by aligning it to a reference system.
- Digitizing in QGIS creates new vector features from imagery and teaches careful interpretation of boundaries.
- Field data collection with ArcGIS Online and Field Maps shows how to design and deploy a mobile workflow for collecting new observations directly in the field.
- Raster collections and pixels in Google Earth Engine introduce how satellite-derived datasets are structured, filtered, masked, and visualized.
By the end of Week 02, you should be able to:
- Explain the difference between using existing spatial data and creating new spatial data
- Explain why schema design, naming conventions, and organization matter in GIS projects
- Explain what georeferencing is and why projection and control point choice affect the result
- Create new vector data through digitizing and mobile field collection workflows
- Explain how raster datasets are built from collections, images, bands, and pixels
- Filter, mask, and threshold image data in Google Earth Engine
- Build cleaner, more reproducible project structures for data creation work
- Evaluate data creation choices in terms of accuracy, consistency, and fitness for use
Week 02 Labs
These Week 02 labs include material that must be turned in for grading.
02 - TURN IN - Georeferencing with QGIS and AllMaps.org
This lab introduces georeferencing through a historical map of Wyoming. You will work with a scanned map image, a PLSS reference layer, and the QGIS Georeferencer to align the historical map to real-world coordinates. The lab emphasizes not only the mechanics of the tool, but the conceptual ideas behind reference data, projection choice, and control point placement.
01 - TURN IN - Data Creation in QGIS
This lab introduces vector data creation through a tree crown labeling exercise in QGIS. You will work from aerial imagery, create new polygon features, and document your work in a map layout. The main lesson is that digitizing is an interpretive act: you are making decisions about where features begin and end, and those decisions affect the quality of the resulting dataset.
03 - TURN IN - Introducing ArcGIS Field Maps and ArcGIS Online for Data Collection
This lab introduces mobile field data collection. You will create hosted feature layers in ArcGIS Online, design a field form, configure offline use, and collect data with ArcGIS Field Maps. The purpose is to help you think carefully about field schema design, controlled vocabularies, usability, and the realities of collecting data away from a desktop GIS.
04 - TURN IN - Introducing Collections, Images, Bands, and Pixels in Google Earth Engine
This lab introduces raster and remote sensing ideas through Google Earth Engine. You will work with Dynamic World, Sentinel-2, and the Hansen forest change dataset to understand how collections become images, how images contain bands, and how bands store pixel values that can be filtered, masked, thresholded, and visualized. The lab is meant to help students move from seeing satellite imagery as a picture toward seeing it as structured spatial data.