Learn how to use drone imagery collections for creating maps and layers in a geographic information system (GIS).
Drone image collections are increasingly valued by scientists for mapping and analyzing natural landscapes and urban environments. Drone imagery can support environmental analysis, monitoring of forests and wetlands, assessments of agricultural productivity, and mapping changes in rivers and shorelines. Other drone collections can generate 3D immersive models of urban settings and depict changes in infrastructure.
This course teaches methods of computer analysis to manage and control hundreds (or thousands) of drone photographs for making accurate and detailed maps. The drone imagery layers can be combined to create innovative maps and interactive story maps, using GIS software provided by Esri, Inc. Each week students will create maps and 3D models of the landscape in a fully hands-on computer-learning experience. Evergreen faculty will teach the planning methods for conducting drone flight missions, and cover the integration of ground control points for maximizing spatial accuracy and ensuring the quality of the map layers. Students will use multispectral drone imagery to conduct spectral analysis that can be used to assess crop health and forest practice, and characterize vegetation properties in terrestrial and marine settings. Software licenses are provided (at no cost) for conducting the image processing workflows. The course is taught in Evergreen's scientific computing lab.
There is no prerequisite to take this course. No previous GIS knowledge is required to take this course. Students who are also taking the "Flying with Drones" course concurrently, will find this course to be a natural follow-on toward learning the scientific application of drone imagery and GIS integration.
Graduate students enrolled in this course will be required to design and execute an independent learning project on their chosen research topic.
In-person Class Format: This course is offered fully in-person. Students should expect to attend in-person for all class periods. We cannot promise to offer remote attendance options due to illness or other absences. Students should strategize methods for getting notes from class when attendance is not possible.
CLASS SCHEDULE: Saturday afternoons