1. Identification of potential Dynamic Cover Types with Sentinel-1
Javier Muro Martín 1

2. Dynamic Cover Types Use time series of SAR images to id potential DCT
The some other aplications came up 2

3. Change detection
Most of the change detection studies use optical sensors
Clouds and intra annual dynamics are obstacles
Sentinel-1 offers a great opportunity to study intra annual dynamics regarless of clouds or illumination conditions
Wetlands, very dynamic 3

4. Test sites: Two different wetlands:
Small seasonal endorreic lagoon: Herbaceous crops, olive grooves, some irrigation
Bigger coastal permanent wetland part of a more complex system of lagoons: rice, salt production, pumping of water 4

5. S1-based change detection
Freeware and open source
Python based
Uses Docker containers and Jupyter notebooks
Based on wishart distribution (Conradsen et al & 2016)

6. Change detection I: preprocessing
More info on the matrix in Conradsen et al. (2015)
Multilook 2 x 8 to remove the speckle noise 6

7. Change detection II: Docker
Docker allows you to store in a virtual container:
Scripts and libraries
Data
System tools
Bridges the gap between code developers and users generating new applications
Open source Codes
Users community

8. Change detection III: Jupyter notebooks
The Jupyter Notebook is a web application that allows you to create and share docs that contain live code, equation, visualizations and explanatory text

9. Results I: time series of changes
Cloud proof change detection at 30 m and weakly resolution
Process all the time series at the same time and you can know when a change was produced
Even slow changes (veg. growth) 9

10. Results II: Frequency of change map
Rates of change in Fuente de Piedra (left) and Camargue (right)

11. Results III: rates of change per class
Once
Twice
Thrice
4 times
No change

13. Other applications
Dissaster management, land slide movement, damage assessment after storms in forestry, illegal and fast urban sprawl 13

14. Other applications
Dissaster management, land slide movement, damage assessment after storms in forestry, illegal and fast urban sprawl 14

15. Sentinel-1 vs Landsat

16. Thank you for your attention
References:
Javier Muro, Morton Canty, Knut Conradsen, Christian Hüttich, Allan Aasbjerg Nielsen, Henning Skriver, Florian Remy, Adrian Strauch, Frank Thonfeld, and Gunter Menz (2016). Short-Term Change Detection in Wetlands Using Sentinel-1 Time Series; Remote Sens. 2016, 8(10), 795;
Knut Conradsen; Allan Aasbjerg Nielsen; Henning Skriver (2016). Determining the Points of Change in Time Series of Polarimetric SAR Data. IEEE Transactions on Geoscience and Remote Sensing Year: 2016, Volume: 54, Issue: 5
Iryna Dronova, Peng Gong, Lin Wang, Liheng Zhong, Mapping dynamic cover types in a large seasonally flooded wetland using extended principal component analysis and object-based classification (2015), Remote Sensing of Environment, Volume 158