Coastal flooding

Satellite(s) Sentinel-1.	Monitoring element SAR backscatter.

Satellite(s)

Sentinel-1.

Monitoring element

SAR backscatter.

Description technique

Cazals et al. (2016) used radar images in VV and HV polarizations with a hysteresis thresholding algorithm to distinguish open water, flooded vegetation and non-flooded grassland.

Accuracy / Resolution

Accuracy 70-94%.

Case study

Simple flood mapping approaches were developed as part of the EnviroSatTools project. Example of Google Earth Engine scripts:

https://gitlab.com/envirosattools/documentation/-/wikis/floods

Also fits domain

Freshwater.

Benefits

SAR microwave energy penetrates cloud, allowing data to be captured regardless of inclement weather conditions resulting in flooding events.

Limitations

SAR data is inherently noisy - aggregating multiple passes can improve the signal to noise ratio, but reduces the temporal resolution of the dataset. Orbit direction results in opposing layover, but given flood detection is required over flat land this issue is not significant.

Applicability for Northland

Yes.

In light of recent flooding events a simple monitoring system, built in Google Earth Engine (or similar), would be highly applicable to the Northland region.

Publication references

Cazals, Cécile, Sébastien Rapinel, Pierre-Louis Frison, Anne Bonis, Grégoire Mercier, Clément Mallet, Samuel Corgne, and Jean-Paul Rudant. 2016. “Mapping and Characterization of Hydrological Dynamics in a Coastal Marsh Using High Temporal Resolution Sentinel-1A Images.” Remote Sensing 8, no. 7: 570. doi:10.3390/rs8070570.

https://www.mdpi.com/2072-4292/8/7/570

Other references

Twelve, A., Cao, W., Plank, S. and Martinis, S., 2016. Sentinel-1-based flood mapping: a fully automated processing chain. International Journal of Remote Sensing, 37(13), pp.2990-3004.;

https://www.tandfonline.com/doi/abs/10.1080/01431161.2016.1192304?journalCode=tres20

Amitrano, D., Di Martino, G., Iodice, A., Riccio, D. and Ruello, G., 2018. Unsupervised rapid flood mapping using Sentinel-1 GRD SAR images. IEEE Transactions on Geoscience and Remote Sensing, 56(6), pp.3290-3299.
https://ieeexplore.ieee.org/document/8291019

Westerhoff RS, Kleuskens MPH, Winsemius HC, Huizinga HJ, Brakenridge GR, Bishop C. 2013. Automated global water mapping based on wide-swath orbital synthetic-aperture radar. Hydrol Earth Syst Sci. 17(2):651-663. doi:10.5194/hess-17-651-2013.

https://hess.copernicus.org/articles/17/651/2013/