Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

An Effective Method for InSAR Mapping of Tropical Forest Degradation in Hilly Areas

Version 1 : Received: 4 November 2021 / Approved: 9 November 2021 / Online: 9 November 2021 (15:43:37 CET)

How to cite: Carstairs, H.; Mitchard, E.T.A.; McNicol, I.; Aquino, C.; Burt, A.; Ebanega, M.O.; Dikongo, A.M.; Bueso-Bello, J.; Disney, M. An Effective Method for InSAR Mapping of Tropical Forest Degradation in Hilly Areas. Preprints 2021, 2021110189 (doi: 10.20944/preprints202111.0189.v1). Carstairs, H.; Mitchard, E.T.A.; McNicol, I.; Aquino, C.; Burt, A.; Ebanega, M.O.; Dikongo, A.M.; Bueso-Bello, J.; Disney, M. An Effective Method for InSAR Mapping of Tropical Forest Degradation in Hilly Areas. Preprints 2021, 2021110189 (doi: 10.20944/preprints202111.0189.v1).

Abstract

Current satellite remote sensing methods struggle to detect and map forest degradation, a critical issue as it is likely a major and growing source of carbon emissions and biodiveristy loss. TanDEM-X InSAR phase height (hϕ) is a promising variable for measuring forest disturbances, as it is closely related to mean canopy height, and thus should decrease if canopy trees are removed. However, previous research has focused on relatively flat terrain, despite the fact that much of the worlds’ 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 hϕ and aboveground biomass change in four selectively logged plots in a hilly region of central Gabon. We show that minimising the level of multilooking in the interferometric processing chain 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.

Keywords

InSAR; TanDEM-X; forest degradation; biomass change; Synthetic Aperture Radar; SAR; Carbon cycle; Satellite data; Earth Observation; DLR; X-band

Subject

EARTH SCIENCES, Environmental Sciences

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