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DSD-INT 2019 Near real-time monitoring of Dutch floodplain vegetation - Rogers

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Presentation by Christine Rogers, Deltares, at the Data Science Symposium, during Delft Software Days - Edition 2019. Thursday, 14 November 2019, Delft.

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DSD-INT 2019 Near real-time monitoring of Dutch floodplain vegetation - Rogers

  1. 1. D a t a S c i e n c e S y m p o s i u m 2 0 1 9 Near real-time monitoring of Dutch floodplain vegetation Christine Rogers
  2. 2. DataScienceSymposium2019 2 Monitoring River Floodplain Vegetation • 500 km • 12000 land owners • Where should vegetation management efforts be focused to reduce flood risk?
  3. 3. DataScienceSymposium2019 3 Photointerpretation Maps • Produced every 6 years Water Built/paved Grass/fields Herbaceous Forest Shrubs
  4. 4. Water Built/paved Grasslands and fields Herbaceous vegetation Forest Shrubs Landcover classes DataScienceSymposium2019 4
  5. 5. DataScienceSymposium2019 5 Roughness 0 5 10 15 20 25 30 Water Built/paved Grass/fields Herbaceous Forest Shrubs Roughness Value Water Built/paved Grass/fields Herbaceous Forest Shrubs Class
  6. 6. DataScienceSymposium2019 6 Sentinel-2 data March 2017
  7. 7. DataScienceSymposium2019 7 Classified Maps Water Built/paved Grass/fields Herbaceous Forest Shrubs
  8. 8. DataScienceSymposium2019 8 https://vegetatiemonitor.netlify.com/ Water Built/paved Grass/fields Herbaceous Forest Shrubs
  9. 9. DataScienceSymposium2019 9 Team Ellis Penning Project Leader Gertjan Geerling Senior Researcher Valesca Harezlak Researcher Gennadii Donchyts Google Earth Engine, Full stack Christine Rogers Google Earth Engine, Back end Robyn Gwee Google Earth Engine Cindy van de Vries-Safavi Nic Front end Fedor Baart Front end Bart Adriaanse Front end
  10. 10. DataScienceSymposium2019 10 Google Earth Engine https://earthengine.google.com/ • > 600 public datasets • > 4000 images added daily • > 29 petabytes of data + 1 PB/month • Upload your own vector and raster data • Tensorflow integration
  11. 11. DataScienceSymposium2019 11 Input Data Landsat 5, 7, 8 (1984-Present) Sentinel-2 (2015-Present) AHN 0.5m DEM Photo interpretation maps 2013-07-21 2017-08-29 2017-08-29
  12. 12. DataScienceSymposium2019 12 Stratified Sampling + Random Forest
  13. 13. DataScienceSymposium2019 13 Validation Accuracy 0 Water 1 Built/paved 2 Grass/fields 3 Herbaceous 4 Forest 5 Shrubs 2017 – 86% PredictedClass Actual Class
  14. 14. DataScienceSymposium2019 14 Water Built/paved Grass/fields Herbaceous Forest Shrubs
  15. 15. DataScienceSymposium2019 15 Increase Decrease Roughness
  16. 16. DataScienceSymposium2019 16 Check per owner, download data
  17. 17. DataScienceSymposium2019 17 Vegetatiemonitor • Machine Learning applied to 35 years of satellite data • Provides accurate measure of current vegetation • Assists in discussions with stakeholders • Google Earth Engine – many other possibilities!

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