File:NASA ARSET- Data Preparation of Imagery for Large-Scale ML Modeling, Part 1-3 (wwhb14hDhEQ).webm
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| Upload date | 2024-04-07T19:14:12Z |
| MIME type | video/webm |
| Dimensions | 1920 × 1080 px |
| File size | 367.4 MB |
Summary
| Description |
English: Large Scale Applications of Machine Learning using Remote Sensing for Building Agriculture Solutions
Part 1: Data Preparation of Imagery for Large-Scale ML Modeling Trainers: Sean McCartney Guest Instructors: John Just (Deere & Co.), Erik Sorensen (Deere & Co.) -Submit lists of boundaries to the NASS API and retrieve CDL rasters back -Subsample and visualize retrieved data from CDL with interactive spatial images and other statistical plots -Obtain Sentinel-2 raster files for a given area and timeframe corresponding to the retrieved CDL data and manipulate the sentinel-2 rasters into tables in preparation for analysis and model training. -Verify correct processing of data via various interactive plots (e.g. time series of pixels of various land covers). You can access all training materials from this webinar series on the training webpage: https://go.nasa.gov/41QtlBu This training was created by NASA's Applied Remote Sensing Training Program (ARSET). ARSET is a part of NASA's Applied Science's Capacity Building Program. Learn more about ARSET: https://appliedsciences.nasa.gov/what-we-do/capacity-building/arset |
| Date | 7 March 2024, 15:00:07 (upload date) |
| Source | NASA ARSET: Data Preparation of Imagery for Large-Scale ML Modeling, Part 1/3 |
| Author | NASA |
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