Please use this identifier to cite or link to this item: https://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/1464
Title: Big Data Remote Sensing
Authors: Millard, Koreen
Knudby, Anders
Schultz, Samantha
Darling, Samantha
Scott, Phillip
Thambimuthu, Thanisan
Cizek, Erika
Hojjatzadeh, Negin
Richardson, Elisha
Wierdsma, Matthew
Sauro, Claudia
Ramey, Marisa
George, Genevieve
Mohuiddin, Adam
Schatkowsky, Mat
Gorra, Andrea
Keywords: Geographic information systems (GIS)
Geomatics
Remote sensing
Issue Date: 2022
Abstract: This course includes advanced topics in remote sensing using open-access tools and freely-accessible data. The focus of this course is on understanding and applying concepts in “big geospatial data analysis” to large-area and time series analysis problems. These techniques will allow students to analyze environmental conditions and phenomena using remotely-sensed imagery and perform spatial and statistical analysis. Students will be able to explore solutions to problems related to their own interests or objectives through an independent project. This course uses Google Earth Engine, a cloud based remote sensing progressing suite. Students will require access to the internet through a modern browser and a Google account (i.e. Gmail, Google Drive). No coding skills are required but students will be expected to use and develop their own Python scripts in the labs.
URI: https://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/1464
Other Identifiers: 6b455460-ebae-4fec-9322-0632570bb45c
Appears in Collections:Ontario OER Collection
VLS Collection

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