ABSTRACT
Tropical peatland across Southeast Asia is drained extensively for production of pulpwood, palm oil and other food crops. Associated increases in peat decomposition have led to widespread subsidence, deterioration of peat condition and CO2 emissions. However, quantification of subsidence and peat condition from these processes is challenging due to the scale and inaccessibility of dense tropical peat swamp forests. The development of satellite interferometric synthetic aperture radar (InSAR) has the potential to solve this problem. The Advanced Pixel System using Intermittent Baseline Subset (APSIS, formerly ISBAS) modelling technique provides improved coverage across almost all land surfaces irrespective of ground cover, enabling derivation of a time series of tropical peatland surface oscillations across whole catchments. This study aimed to establish the extent to which APSIS-InSAR can monitor seasonal patterns of tropical peat surface oscillations at North Selangor Peat Swamp Forest, Peninsular Malaysia. Results showed that C-band SAR could penetrate the forest canopy over tropical peat swamp forests intermittently and was applicable to a range of land covers. Therefore the APSIS technique has the potential for monitoring peat surface oscillations under tropical forest canopy using regularly acquired C-band Sentinel-1 InSAR data, enabling continuous monitoring of tropical peatland surface motion at a spatial resolution of 20 m.
Subject(s)
Forests , Radar , Soil , Asia, Southeastern , WetlandsABSTRACT
The cessation of dewatering following coalfield abandonment results in the rise of minewater, which can create significant changes in the local and regional hydrogeological regime. Monitoring such change is challenging but essential to avoiding detrimental consequences such as groundwater contamination and surface flooding. Inverse modelling methods using satellite radar interferometry (InSAR) have proven capable for retrospectively mapping minewater level changes, however, there is a need for the capability to remotely monitor changes as they occur. In this study, ground deformation measurements obtained from InSAR are used to develop a method to remotely monitor the spatio-temporal rise of minewater, which could be implemented in near real-time. The approach is demonstrated over the Horlivka mining agglomeration, Ukraine, where there is no other feasible approach possible due to a lack of safe ground access. The results were blindly validated against in-situ measurements before being used to forecast the time until minewater will reach the natural water table and Earth's surface. The findings reveal that, as a result of military conflict in Donbas, an environmental catastrophe could occur where potentially radioactive minewater is forecast to reach the natural water table between May and August of 2024.