The Evolution of Remote Sensing Education in Canada’s Universities and Colleges: Decades of Innovation and Expansion
Bibliographic record
Abstract
During the rapid development of remote sensing technology and applications in the 1970’s in Canada, the Canadian Advisory Committee on Remote Sensing conducted a nation-wide review of relevant activities in post-secondary teaching and research. This was updated in the 1980’s. Similar reviews were solicited for the radar community in 2009 by the Canadian Space Agency and for the Geospatial community in Canada in 2016 by Natural Resources Canada. In this paper we report on a new Canadian survey conducted in 2021 which is discussed within the context of the previous profiles. In Canada today there are 65 post-secondary institutions directly involved in remote sensing teaching and 63 academic research centers in this field. At these institutions and others worldwide, significant changes were brought about in education practice in the spring of 2020 with shutdowns in many sectors of the economy in response to the rapid expansion of the COVID-19 virus. Classroom teaching transitioned to on-line communication. These experiences may have a direct influence on how teaching and training practice of ‘hands-on’ disciplines such as remote sensing may evolve and contribute to future growth. We discuss the potential impact of this upheaval for the future of remote sensing education within the remote sensing community in Canada based upon personal experience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".