Google Earth Engine - Wrangling the Fire Hose

A short presentation about dealing with large datasets from Google Earth Engine, data organization, and a few examples of analysis/visualization

Transcript

1. Google Earth Engine: Wrangling the Firehose Examples of Dynamic Analysis Using R Ryan Peek 2017-Nov-05
2. The Map Matters 2 / 21
3. Modern Data 3 / 21
4. Modern Data Google Earth Engine (GEE) Is Awesome 3 / 21
5. Modern Data Google Earth Engine (GEE) Is Awesome As long as you can deal with this: 3 / 21
6. Tips, Tricks, & Examples 4 / 21
7. Tips, Tricks, & Examples Data Management/Organization 4 / 21
8. Tips, Tricks, & Examples Data Management/Organization Things to Consider with GEE Data 4 / 21
9. Tips, Tricks, & Examples Data Management/Organization Things to Consider with GEE Data Meadows Example 4 / 21
10. Tips, Tricks, & Examples Data Management/Organization Things to Consider with GEE Data Meadows Example Genomics & Riparian Habitat Example 4 / 21
11. Data Organization 5 / 21
12. Data Organization pick a pipeline and stick with it 5 / 21
13. Data Organization pick a pipeline and stick with it document for future you, not for today you 5 / 21
14. Data Organization pick a pipeline and stick with it document for future you, not for today you use existing frameworks/tools where possible! 5 / 21
15. Document at This Scale: (Slate Ck: North Yuba) 6 / 21
16. AND This Scale! 7 / 21
17. Using RStudio Projects 8 / 21
18. Using RStudio Projects See Data Carpentry for tips 8 / 21
19. Using RStudio Projects See Data Carpentry for tips RStudio has many things built in! 8 / 21
20. Using RStudio Projects See Data Carpentry for tips RStudio has many things built in! Pick a Directory Structure 8 / 21
21. Using RStudio Projects See Data Carpentry for tips RStudio has many things built in! Pick a Directory Structure USE PROJECTS 8 / 21
22. Using RStudio Projects See Data Carpentry for tips RStudio has many things built in! Pick a Directory Structure USE PROJECTS Software Carpentry lesson on RStudio Projects 8 / 21
23. Example Directory Structure 9 / 21
24. Version Control (Github) 10 / 21
25. Version Control (Github) It hurts (only a little) 10 / 21
26. Version Control (Github) It hurts (only a little) 10 / 21
27. Version Control (Github) It hurts (only a little) Many resources available: happygit ohshitgit github.com 10 / 21
28. Things to Consider with GEE Data 11 / 21
29. Things to Consider with GEE Data brainstorm (1 min) 11 / 21
30. Things to Consider with GEE Data brainstorm (1 min) Check this out: pixel assessment 11 / 21
31. Examples 12 / 21
32. Earth Imagery & CA Sensitive Ecosystems 13 / 21
33. Earth Imagery & CA Sensitive Ecosystems Using NDVI to assess resilience/sensitivity of Sierra Nevada meadows and CA serpentine grasslands 13 / 21
34. Earth Imagery & CA Sensitive Ecosystems Using NDVI to assess resilience/sensitivity of Sierra Nevada meadows and CA serpentine grasslands 13 / 21
35. Many Meadows1 but Condition/Hydrologic Drivers Unknown [1] Viers et al. 2013 14 / 21
36. NDVI vs. Snow/Groundwater Hydrology 15 / 21
37. NDVI vs. Snow/Groundwater Hydrology What is dominant hydrologic driver in meadow? 15 / 21
38. NDVI vs. Snow/Groundwater Hydrology What is dominant hydrologic driver in meadow? Important for Restoration/Conservation Design 15 / 21
39. Snow (CDEC: 1984-2015) 16 / 21
40. Max Growing Season NDVI (1984-2014) 17 / 21
41. Pull these Together into Shiny App 18 / 21
42. Dynamic & Interactive 19 / 21
43. Riparian Stream Habitat Example 20 / 21
44. Riparian Stream Habitat Example Remote Sensing & Freshwater Fisheries 20 / 21
45. Riparian Stream Habitat Example Remote Sensing & Freshwater Fisheries Integrating Genomics/Connectivity/River Regulation 20 / 21
46. Thank you! Links: Making Animated Plots in R Making Maps in R Mapping with sf package in R 21 / 21