An Effective Method for InSAR Mapping of Tropical Forest Degradation in Hilly Areas - Harry Carstairs; Edward T. A. Mitchard; Iain McNicol; Chiara Aquino; Andrew Burt; Médard Obiang Ebanega; Anaick Modinga Dikongo; José-Luis Bueso-Bello; Mathias Disney (Remote Sensing, 2022)
Current satellite remote sensing methods struggle to detect and map forest degradation, which is a critical issue as it is likely a major and growing source of carbon emissions and biodiveristy loss. TanDEM-X InSAR phase height (<semantics>hϕ</semantics>) is a promising variable for measuring forest disturbances, as it is closely related to the mean canopy height, and thus should decrease if canopy trees are removed. However, previous research has focused on relatively flat terrains, despite the fact that much of the world’s remaining tropical forests are found in hilly areas, and this inevitably introduces artifacts in sideways imaging systems. In this paper, we find a relationship between <semantics>hϕ</semantics> and aboveground biomass change in four selectively logged plots in a hilly region of central Gabon. We show that minimising multilooking prior to the calculation of <semantics>hϕ</semantics> strengthens this relationship, and that degradation estimates across steep slopes in the surrounding region are improved by selecting data from the most appropriate pass directions on a pixel-by-pixel basis. This shows that TanDEM-X InSAR can measure the magnitude of degradation, and that topographic effects can be mitigated if data from multiple SAR viewing geometries are available.