1. U.S. Department of the Interior U.S. Geological Survey Web Presence, Data Sharing, Real- time Analysis and Crowdsourcing GFSAD30 Sixth Workshop – July 2015 Justin Poehnelt, Student Developer jpoehnelt@usgs.gov

2. Overview  Reference Data Collection  Mobile Application  Google Street View Imagery  Other Sources  Croplands Website  Maps and Layers  Image Classification  Reference Data Management

3. Achievements  Mobile application has been released for Android and iOS devices.  Continued improvements to Croplands website bringing stability, scalability and an improved aesthetic.

4. Mobile Application Overview A mobile application can facilitate easy collection of reference data using common mobile devices from anywhere in the world.

5. Mobile Application Specifications  Work without network access  User captured photos  Collect minimum of crop type and water source  Handle inaccuracies and patterns of field data collection

6. Data Collection Patterns User may only have a few seconds to take photo and collect location.  Allow user to separate location collection from form completion. User is likely to be on edge of area of interest.  Capture bearing and distance to center of area. Bearing is more important and can use built-in compass. User may be poor judge of area and distance.  Use qualitative measures when possible with a generalized definition.  High resolution imagery can be used to verify.

7. Mobile App Demo For more information on the app: https://croplands.org/mobile

8. Other Sources of Data  Google Street View Imagery  Very High Resolution Imagery  Other Projects  LUCAS  geoWiki These sources require a greater amount of processing to hopefully fit our project’s needs.

9. Google Street View Imagery

11.  Challenges  Extracting street view coverage  Big data problem  Remaining Tasks  Download portion of 4 trillion tiles having showing street view coverage… less than 5%  Extract polylines from tiles  Sample polylines for locations  Verify images exist at location  Modification of image classification page

12. LUCAS Data (Europe)  Includes crop type, detailed location data and 5 photos for each site.  Covers EU members  2006: 150,000 sites  2009: 200,000 sites  2012: 250,000 sites  2015: 270,000 sites (in progress)

13. LUCAS Data (Europe)  Challenges:  Over two terabytes of photos  Slight variations in data structure year to year require careful conversion of data to GFSAD structure  Tracking the uploading and merging of this data requires persistent data structures and careful rate- limiting  Mixed pixel issues

14. LUCAS Data Mixed Pixels

15. Croplands Website  Primary method for viewing and interacting with GFSAD30 products through a web browser  Additional tools and structure for storing and managing reference data

16. Maps and Layers  Dynamic map tiles generated through Google Earth Engine  Created and cached as to improve speed  Allows user to select specific years, classes etc.  2E17 unique tiles summing to millions of petabytes can be available for request  Supporting layers such as NDVI can now easily be incorporated

17. Example Layer

18. Other Tools and Processing  Image Classification  Mixed Pixel Review/Adjustment  Sampling Training and Validation Data  Generating Phenology Patterns  Email alerts for new reference data with download links  Additional analysis tools to compare different GFSAD products

19. Image Classification

20. Mixed Pixels

21. Training or Validation

22. Web App Demo For more information on the app: https://croplands.org

23. Open Source Software github.com/justinwp/croplands github.com/justinwp/croplands-web github.com/justinwp/croplands-mobile

24. Thank you