GEOG315

INTRO DEEP LEARNING EARTH OBS

Offered in a current or upcoming term. Official schedule
Other titles (2)
  • APPLY'G DEEP LEARN'G EARTH OBS
  • PROFESSIONAL TRAINING
Department
Geography
Terms offered
13
Data refreshed
Sep 1, 2026

Description

Focusing on convolutional and recurrent neural networks, this course will provide an in-depth overview of key machine learning algorithms and their application to satellite imagery (especially for the task of semantic segmentation), including the full workflow required to acquire and process imagery, develop and train a model, and make and critically evaluate the resulting maps. The course will be strongly hands-on, and emphasize the use of programming (python), open image archives and EO analytical platforms (e.g. Google Earth Engine), and tools for creating open and reproducible workflows (git and GitHub).

Syllabi

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Offerings and forecast 2016–2026

2005
2026
Sections by year and season
YearFallSpringSummerIntersession
2030 2030 Fall: not enough history to forecast. 2030 Spring: 47% chance, low confidence. Offered in every spring term since 2023. Department course count falling about 2% per year. 2030 Summer: 7% chance, medium confidence. Offered in 0 of 9 summer terms since 2018. 2030 Intersession: 8% chance, medium confidence. Offered in 0 of 6 intersession terms since 2020.
2029 2029 Fall: not enough history to forecast. 2029 Spring: 56% chance, low confidence. Offered in every spring term since 2023. 2029 Summer: 6% chance, medium confidence. Offered in 0 of 10 summer terms since 2017. 2029 Intersession: 7% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017.
2028 2028 Fall: not enough history to forecast. 2028 Spring: 60% chance, low confidence. Offered in every spring term since 2023. 2028 Summer: 5% chance, medium confidence. Offered in 0 of 11 summer terms since 2016. 2028 Intersession: 7% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017.
2027 2027 Fall: not enough history to forecast. 2027 Spring: 59% chance, low confidence. Offered in every spring term since 2023. Department course count falling about 2% per year. 2027 Summer: 5% chance, high confidence. Offered in 0 of 12 summer terms since 2015. 2027 Intersession: 6% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017.
2026 1 section 1 section Not offered No data
2025 Not offered 1 section Not offered Not offered
2024 Not offered 1 section Not offered Not offered
2023 Not offered 1 section Not offered Not offered
2022 Outside range Outside range Outside range Outside range
Forecast Under 15% 15–39% 40–69% 70–89% 90%+ Not enough history
Fall Spring Summer Intersession More sections Not offered No data

Meeting times

Recent first
  • Mon, Wed, 4:15 PM–5:30 PM JC215 2026-22026-22025-1
  • Fri, 2:50 PM–4:05 PM JC215 2026-12026-1
  • Thu, 4:15 PM–5:30 PM MACD002 2025-2
  • Thu, 9:00 AM–10:15 AM Jefferson Academic Center JF202 2009
  • Thu, 1:25 PM–2:40 PM Geography Building G104 2008
  • Wed, 4:15 PM–5:30 PM Geography Building G104 2008
  • Wed, 4:15 PM–5:45 PM Geography Building G104 20072006
  • Wed, 4:00 PM–6:00 PM Geography Building G104 200720062005
Credit-bearing sections of GEOG315
TermProfessorTypeCreditsEnrollmentCRN
Fall 2026Lyndon D. EstesLecture1 3 of 30 enrolled24811
Spring 2026Lyndon D. EstesLecture1 8 of 30 enrolled32503
Spring 2025Lyndon D. EstesLecture1 5 of 15 enrolled32503
Spring 2024Lyndon D. EstesLecture1 7 of 15 enrolled32503
Spring 2023Kenneth J. BasyeLecture1 14 of 15 enrolled32503

No-credit sessions

No-credit sections of GEOG315
TermProfessorTypeCreditsEnrollmentCRN
Spring 2009Colin PolskyLecture- 10 of 12 enrolled34593
Fall 2008Colin PolskyLecture- 10 of 15 enrolled23663
Spring 2008Douglas L. JohnsonLecture- 8 of 8 enrolled34593
Fall 2007Douglas L. JohnsonLecture- 8 of 10 enrolled23663
Spring 2007Douglas L. JohnsonLecture- 7 of 8 enrolled34593
Fall 2006Douglas L. JohnsonLecture- 8 of 10 enrolled23663
Spring 2006Douglas L. JohnsonLecture- 7 of 8 enrolled34593
Fall 2005Douglas L. JohnsonLecture- 8 of 7 enrolled23663