Actively monitoring ground motion is of the highest importance in The Netherlands, a country in
which many of its regions lie below sea level. Water tables in the country have been managed
for centuries by using a system of dams, dikes and canals through which excess water can be
pumped away to allow for the prevention of flooding, and for the reclamation of submerged land.
However, the effects of centuries of active water management in the region have resulted in
significant land subsidence, and its effects are being felt as it is becoming a significant threat to
the future of the country as sea levels continue to rise [1].
This has created the need to monitor land surface motion at large spatial scales with frequent
temporal sampling. While InSAR is a promising candidate for such a task, the technique often
suffers from drastic losses of signal quality in the spring and summer months when used to
produce time series observations of peatlands. This significantly limits the effectiveness of
InSAR as a tool to monitor peatland surface dynamics [2,3,4].
We present the preliminary results of peatland surface motion using a novel InSAR processing
method which is designed to overcome the issues which have prevented its application over
northern peatlands in the past [5]. This work is the first large scale analysis of the Dutch Green
Heart region made with InSAR, providing land surface motion time series data at the parcel
scale for a 2000 km2 region with sub-weekly sampling over the period Jan. 2015 to Oct. 2023.
Our presentation will briefly outline the results, validation efforts and the various challenges
involved.
References
[1] G. Erkens, M. J. van der Meulen, and H. Middelkoop, “Double Trouble: Subsidence and CO2 Respiration Due to
1,000 Years of Dutch Coastal Peatlands Cultivation,” Hydrogeology Journal, vol. 24, no. 3, pp. 551–568, 2016.
[2] Y. Morishita and R. F. Hanssen, “Temporal decorrelation in L-, C-, and X-band satellite radar interferometry for
pasture on drained peat soils,” IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 2, pp. 1096–
1104, 2015.
[3] Y. Morishita and R. F. Hanssen, “Deformation parameter estimation in low coherence areas using a multisatellite
InSAR approach,” IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 8, pp. 4275–4283, 2015.
[4] L. Alshammari, D. J. Large, D. S. Boyd, A. Sowter, R. Anderson, R. Andersen, and S. Marsh, “Long-term peatland
condition assessment via surface motion monitoring using the ISBAS DInSAR technique over the flow country,
Scotland,” Remote Sensing, vol. 10, no. 7, 2018.
[5] P. Conroy, S. A. N. van Diepen, F. J. van Leijen, and R. F. Hanssen, “Bridging loss-of-lock in InSAR time series of
distributed scatterers,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1–11, 2023