Floods extent

Satellite(s) e.g., Sentinel-1.	Monitoring element Surface water SAR backscatter.

Satellite(s)

e.g., Sentinel-1.

Monitoring element

Surface water SAR backscatter.

Description technique

Twelve et al. (2016) used SAR data to provide rapid updates on flooding extent.

Accuracy / Resolution

~95%

Case study

Mapping extent of flooded areas during/following event. Flooding alerts in known risk areas.

Also fits domain

Land

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

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

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://doi.org/10.1080/01431161.2016.1192304

Other comments or information

In some cases applying ML or OBIA is not required - using a simple pre and during event difference thresholding approach can give useful results.
Tools such as google earth engine and ESA SNAP have significantly reduced the burden of preparing Sentinel-1 data by offering pre-processed datasets and streamlined workflows.

Other references

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/abstract/document/8291019